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  • 1. Order onlineBuy this publication >>
    Kunz, Jenny
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Understanding Large Language Models: Towards Rigorous and Targeted Interpretability Using Probing Classifiers and Self-Rationalisation2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Large language models (LLMs) have become the base of many natural language processing (NLP) systems due to their performance and easy adaptability to various tasks. However, much about their inner workings is still unknown. LLMs have many millions or billions of parameters, and large parts of their training happen in a self-supervised fashion: They simply learn to predict the next word, or missing words, in a sequence. This is effective for picking up a wide range of linguistic, factual and relational information, but it implies that it is not trivial what exactly is learned, and how it is represented within the LLM. 

    In this thesis, I present our work on methods contributing to better understanding LLMs. The work can be grouped into two approaches. The first lies within the field of interpretability, which is concerned with understanding the internal workings of the LLMs. Specifically, we analyse and refine a tool called probing classifiers that inspects the intermediate representations of LLMs, focusing on what roles the various layers of the neural model play. This helps us to get a global understanding of how information is structured in the model. I present our work on assessing and improving the probing methodologies. We developed a framework to clarify the limitations of past methods, showing that all common controls are insufficient. Based on this, we proposed more restrictive probing setups by creating artificial distribution shifts. We developed new metrics for the evaluation of probing classifiers that move the focus from the overall information that the layer contains to differences in information content across the LLM. 

    The second approach is concerned with explainability, specifically with self-rationalising models that generate free-text explanations along with their predictions. This is an instance of local understandability: We obtain justifications for individual predictions. In this setup, however, the generation of the explanations is just as opaque as the generation of the predictions. Therefore, our work in this field focuses on better understanding the properties of the generated explanations. We evaluate the downstream performance of a classifier with explanations generated by different model pipelines and compare it to human ratings of the explanations. Our results indicate that the properties that increase the downstream performance differ from those that humans appreciate when evaluating an explanation. Finally, we annotate explanations generated by an LLM for properties that human explanations typically have and discuss the effects those properties have on different user groups. 

    While a detailed understanding of the inner workings of LLMs is still unfeasible, I argue that the techniques and analyses presented in this work can help to better understand LLMs, the linguistic knowledge they encode and their decision-making process. Together with knowledge about the models’ architecture, training data and training objective, such techniques can help us develop a robust high-level understanding of LLMs that can guide decisions on their deployment and potential improvements. 

    List of papers
    1. Classifier Probes May Just Learn from Linear Context Features
    Open this publication in new window or tab >>Classifier Probes May Just Learn from Linear Context Features
    2020 (English)In: Proceedings of the 28th International Conference on Computational Linguistics, 2020, Vol. 28, p. 5136-5146, article id 450Conference paper, Published paper (Refereed)
    Abstract [en]

    Classifiers trained on auxiliary probing tasks are a popular tool to analyze the representations learned by neural sentence encoders such as BERT and ELMo. While many authors are aware of the difficulty to distinguish between “extracting the linguistic structure encoded in the representations” and “learning the probing task,” the validity of probing methods calls for further research. Using a neighboring word identity prediction task, we show that the token embeddings learned by neural sentence encoders contain a significant amount of information about the exact linear context of the token, and hypothesize that, with such information, learning standard probing tasks may be feasible even without additional linguistic structure. We develop this hypothesis into a framework in which analysis efforts can be scrutinized and argue that, with current models and baselines, conclusions that representations contain linguistic structure are not well-founded. Current probing methodology, such as restricting the classifier’s expressiveness or using strong baselines, can help to better estimate the complexity of learning, but not build a foundation for speculations about the nature of the linguistic structure encoded in the learned representations.

    Keywords
    Natural Language Processing, Machine Learning, Neural Language Representations
    National Category
    Language Technology (Computational Linguistics) Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-175384 (URN)10.18653/v1/2020.coling-main.450 (DOI)
    Conference
    International Conference on Computational Linguistics (COLING), Barcelona, Spain (Online), December 8–13, 2020
    Available from: 2021-04-30 Created: 2021-04-30 Last updated: 2024-04-02Bibliographically approved
    2. Test Harder Than You Train: Probing with Extrapolation Splits
    Open this publication in new window or tab >>Test Harder Than You Train: Probing with Extrapolation Splits
    2021 (English)In: Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP / [ed] Jasmijn Bastings, Yonatan Belinkov, Emmanuel Dupoux, Mario Giulianelli, Dieuwke Hupkes, Yuval Pinter, Hassan Sajjad, Punta Cana, Dominican Republic, 2021, Vol. 5, p. 15-25, article id 2Conference paper, Published paper (Refereed)
    Abstract [en]

    Previous work on probing word representations for linguistic knowledge has focused on interpolation tasks. In this paper, we instead analyse probes in an extrapolation setting, where the inputs at test time are deliberately chosen to be ‘harder’ than the training examples. We argue that such an analysis can shed further light on the open question whether probes actually decode linguistic knowledge, or merely learn the diagnostic task from shallow features. To quantify the hardness of an example, we consider scoring functions based on linguistic, statistical, and learning-related criteria, all of which are applicable to a broad range of NLP tasks. We discuss the relative merits of these criteria in the context of two syntactic probing tasks, part-of-speech tagging and syntactic dependency labelling. From our theoretical and experimental analysis, we conclude that distance-based and hard statistical criteria show the clearest differences between interpolation and extrapolation settings, while at the same time being transparent, intuitive, and easy to control.

    Place, publisher, year, edition, pages
    Punta Cana, Dominican Republic: , 2021
    Keywords
    Natural Language Processing, Neural Language Models, Interpretability, Probing, BERT, Extrapolation
    National Category
    Language Technology (Computational Linguistics) Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-182166 (URN)10.18653/v1/2021.blackboxnlp-1.2 (DOI)
    Conference
    BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, November 11, 2021
    Available from: 2022-01-10 Created: 2022-01-10 Last updated: 2024-04-02Bibliographically approved
    3. Where Does Linguistic Information Emerge in Neural Language Models?: Measuring Gains and Contributions across Layers
    Open this publication in new window or tab >>Where Does Linguistic Information Emerge in Neural Language Models?: Measuring Gains and Contributions across Layers
    2022 (English)In: Proceedings of the 29th International Conference on Computational Linguistics / [ed] Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na, 2022, p. 4664-4676, article id 1.413Conference paper, Published paper (Refereed)
    Abstract [en]

    Probing studies have extensively explored where in neural language models linguistic information is located. The standard approach to interpreting the results of a probing classifier is to focus on the layers whose representations give the highest performance on the probing task. We propose an alternative method that asks where the task-relevant information emerges in the model. Our framework consists of a family of metrics that explicitly model local information gain relative to the previous layer and each layer’s contribution to the model’s overall performance. We apply the new metrics to two pairs of syntactic probing tasks with different degrees of complexity and find that the metrics confirm the expected ordering only for one of the pairs. Our local metrics show a massive dominance of the first layers, indicating that the features that contribute the most to our probing tasks are not as high-level as global metrics suggest.

    Keywords
    NLP, AI, Language Technology, Computational Linguistics, Machine Learning
    National Category
    Language Technology (Computational Linguistics)
    Identifiers
    urn:nbn:se:liu:diva-191000 (URN)
    Conference
    COLING, October 12–17, 2022
    Available from: 2023-01-12 Created: 2023-01-12 Last updated: 2024-04-02Bibliographically approved
    4. Human Ratings Do Not Reflect Downstream Utility: A Study of Free-Text Explanations for Model Predictions
    Open this publication in new window or tab >>Human Ratings Do Not Reflect Downstream Utility: A Study of Free-Text Explanations for Model Predictions
    2022 (English)In: Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022, Vol. 5, p. 164-177, article id 2022.blackboxnlp-1.14Conference paper, Published paper (Refereed)
    Abstract [en]

    Models able to generate free-text rationales that explain their output have been proposed as an important step towards interpretable NLP for “reasoning” tasks such as natural language inference and commonsense question answering. However, the relative merits of different architectures and types of rationales are not well understood and hard to measure. In this paper, we contribute two insights to this line of research: First, we find that models trained on gold explanations learn to rely on these but, in the case of the more challenging question answering data set we use, fail when given generated explanations at test time. However, additional fine-tuning on generated explanations teaches the model to distinguish between reliable and unreliable information in explanations. Second, we compare explanations by a generation-only model to those generated by a self-rationalizing model and find that, while the former score higher in terms of validity, factual correctness, and similarity to gold explanations, they are not more useful for downstream classification. We observe that the self-rationalizing model is prone to hallucination, which is punished by most metrics but may add useful context for the classification step.

    Keywords
    Large Language Models, Neural Networks, Transformers, Interpretability, Explainability
    National Category
    Language Technology (Computational Linguistics) Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-195615 (URN)
    Conference
    BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, December 8, 2022
    Available from: 2023-06-22 Created: 2023-06-22 Last updated: 2024-04-02Bibliographically approved
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  • 2.
    Li, Huanyu
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Abd Nikooie Pour, Mina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Li, Ying
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Lindecrantz, Mikael
    Ragn-Sells AB, Sweden.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. University of Gävle, Sweden.
    A Survey of General Ontologies for the Cross-Industry Domain of Circular Economy2023In: WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023, New York, NY, United States: Association for Computing Machinery (ACM), 2023, p. 731-741Conference paper (Refereed)
    Abstract [en]

    Circular Economy has the goal to reduce value loss and avoid waste by extending the life span of materials and products, including circulating materials or product parts before they become waste. Circular economy models (e.g., circular value networks) are typically complex and networked, involving different cross-industry domains. In the context of a circular value network, multiple actors, such as suppliers, manufacturers, recyclers, and product end-users, may be involved. In addition, there may be various flows of resources, energy, information and value throughout the network. This means that we face the challenge that the data and information from cross-industry domains in a circular economy model are not built on common ground, and as a result are difficult to understand and use for both humans and machines. Using ontologies to represent domain knowledge can enable actors and stakeholders from different industries in the circular economy to communicate using a common language. The knowledge domains involved include circular economy, sustainability, materials, products, manufacturing, and logistics. The objective of this paper is to investigate the landscape of current ontologies for these domains. This will enable us to in the future explore what existing knowledge can be adapted or used to develop ontologies for circular value networks.

  • 3.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Li, Huanyu
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    Keskisärkkä, Robin
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Human-Centered systems.
    Lindecrantz, Mikael
    Ragn-Sells AB, Sweden.
    Abd Nikooie Pour, Mina
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques. Swedish e-Science Research Centre.
    Li, Ying
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Database and information techniques. Swedish e-Science Research Centre.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre.
    Cross-domain Modelling - A Network of Core Ontologies for the Circular Economy2023In: Proceedings of the 14th Workshop on Ontology Design and Patterns (WOP 2023): co-located with the 22nd International Semantic Web Conference (ISWC 2023) / [ed] Raghava Mutharaju, Agnieszka Ławrynowicz, Pramit Bhattacharyya, Eva Blomqvist, Luigi Asprino, Gunjan Singh, Aachen, Germany: CEUR Workshop Proceedings , 2023Conference paper (Refereed)
    Abstract [en]

    Circular Economy (CE) aims to reduce value loss and avoid waste by extending the life of products,components, and materials. Circular value networks (CVN), i.e. networks of actors realising partsof the CE, are often complex and involving a multitude of actors, such as suppliers, manufacturers,recyclers, and end-users, from different industry sectors. In addition, the networks enable and managevarious flows of resources, energy, information and value. To set up and operate such networks, datasharing is essential, however, one of the main challenges is semantic interoperability, and as a resultdata are difficult to understand, integrate, and use. Ontologies support semantic interoperability, andcan represent domain knowledge and enable stakeholders to communicate. However, the knowledgedomains involved are many, including sustainability, materials, products, manufacturing, and logistics,where well-established ontologies already exist. In addition, these domains need to be connected torelevant industry sectors. In order to bridge these domains we propose a set of core ontology modules,allowing to express links between existing ontologies as well as filling gaps related to core CE concepts.

  • 4.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Poveda-Villalon, Maria
    Univ Politecn Madrid, Spain.
    Garcia-Castro, Raul
    Univ Politecn Madrid, Spain.
    Hitzler, Pascal
    Kansas State Univ, KS 66506 USA.
    Lindecrantz, Mikael
    Ragn Sells AB, Sweden.
    The First International Workshop on Knowledge Graphs for Sustainability-KG4S Foreword2023In: COMPANION OF THE WORLD WIDE WEB CONFERENCE, WWW 2023, ASSOC COMPUTING MACHINERY , 2023, p. 723-723Conference paper (Refereed)
  • 5.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Lindecrantz, Mikael
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Blomsma, Fenna
    Universität Hamburg, Germany.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Högskolan i Gävle.
    De Meester, Ben
    IMEC - Ghent University, Belgium.
    Decentralized Digital Twins of Circular Value Networks - A Position Paper2022In: Proceedings of the Third International Workshop on Semantic Digital Twins: co-located with the 19th Extended Semantic Web Conference (ESWC 2022) / [ed] Raúl García-Castro and John Davies, CEUR Workshop Proceedings , 2022Conference paper (Refereed)
    Abstract [en]

    Circular economy aims at reducing value loss and avoiding waste, by circulating material or productparts before they become waste. Today, lack of support for sharing data in a secure, quality assured, andautomated way is one of the main obstacles that industry actors point to when attempting to create newcircular value networks. Together with using different terminologies and not having explicit definitions ofthe concepts that appear in data, this makes it very difficult to create new ecosystems of actors in Europetoday. A solution to these challenges needs to leverage open standards for semantic data interoperabilityin establishing a shared vocabulary (ontology network) for data documentation, as well as create adecentralized digital platform that enables collaboration in a secure and confidentiality-preservingmanner. This vocabulary can then be used to construct digital twins of circular value networks to furtherenable open collaboration. Once defined, the blueprints of these digital twins will be reusable as templatesand can be reused with a different set of actors, or used within a different industry domain. This visionincludes a number of open research problems, including the development of ontologies that need to modela wide range of different materials and products, not only providing vertical interoperability but alsohorizontal interoperability, for cross-industry value networks. As well as transdisciplinary research onmethods to find, analyse and assess new circular value chain configurations, and form their decentralizeddigital twins. The solutions will allow for automation of planning, management, and execution of circularvalue networks, at a European scale, and beyond. Thereby supporting the acceleration of the digitaland green transitions, automating the discovery and formation of new collaborations in the circulareconomy.

  • 6.
    Spreco, Armin
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Society and Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Regionledningskontoret, Enheten för folkhälsa.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Psychology. Linköping University, Faculty of Arts and Sciences.
    Jöud, Anna
    Lund Univ, Sweden; Skane Univ Hosp, Sweden.
    Nordvall, Dennis
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences. Reg Jonkoping Cty, Sweden.
    Fagerström, Cecilia
    Reg Kalmar Cty, Sweden.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hinkula, Jorma
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Molecular Medicine and Virology. Linköping University, Faculty of Medicine and Health Sciences.
    Schön, Thomas
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Medicine Center, Department of Infectious Diseases.
    Timpka, Toomas
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Society and Health. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering. Region Östergötland, Regionledningskontoret, Enheten för folkhälsa.
    Effectiveness of the BNT162b2 mRNA Vaccine Compared with Hybrid Immunity in Populations Prioritized and Non-Prioritized for COVID-19 Vaccination in 2021-2022: A Naturalistic Case-Control Study in Sweden2022In: Vaccines, E-ISSN 2076-393X, Vol. 10, no 8, article id 1273Article in journal (Refereed)
    Abstract [en]

    The term hybrid immunity is used to denote the immunological status of vaccinated individuals with a history of natural infection. Reports of new SARS-CoV-2 variants of concern motivate continuous rethought and renewal of COVID-19 vaccination programs. We used a naturalistic case-control study design to compare the effectiveness of the BNT162b2 mRNA vaccine to hybrid immunity 180 days post-vaccination in prioritized and non-prioritized populations vaccinated before 31 July 2021 in three Swedish counties (total population 1,760,000). Subjects with a positive SARS-CoV-2 test recorded within 6 months before vaccination (n = 36,247; 6%) were matched to vaccinated-only controls. In the prioritized population exposed to the SARS-CoV-2 Alpha and Delta variants post-vaccination, the odds ratio (OR) for breakthrough infection was 2.2 (95% CI, 1.6-2.8; p < 0.001) in the vaccinated-only group compared with the hybrid immunity group, while in the later vaccinated non-prioritized population, the OR decreased from 4.3 (95% CI, 2.2-8.6; p < 0.001) during circulation of the Delta variant to 1.9 (95% CI, 1.7-2.1; p < 0.001) with the introduction of the Omicron variant (B.1.617.2). We conclude that hybrid immunity provides gains in protection, but that the benefits are smaller for risk groups and with circulation of the Omicron variant and its sublineages.

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  • 7. Order onlineBuy this publication >>
    Keskisärkkä, Robin
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Complex Event Processing under Uncertainty in RDF Stream Processing2021Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The Semantic Web provides a framework for representing, sharing, and integrating data on the Web using a set of specifications promoted by the World Wide Web Consortium (W3C). These specifications include RDF as the model for data inter-change on the Web and languages (e.g., RDFS and OWL) for defining schemas and ontologies. While the Semantic Web has traditionally focused on static or slowly changing data, information on the Web is becoming increasingly dynamic, with sources such as Internet-of-Things devices, sensor networks, smart cities, social me-dia, and more. RDF Stream Processing (RSP) extends Semantic Web technologies to support streaming data and continuous queries and has been suggested as a candidate for bridging the gap between Complex Event Processing (CEP), which focuses on identifying meaningful events and event patterns from streaming data, and the Semantic Web standards. Systems that operate on real-world data must often deal with uncertainty, which can arise from, for example, missing information, incomplete domain knowledge, sensor noise, or linguistic vagueness. Uncertainty has received attention in both Semantic Web and CEP research, but little is known about how it can be managed in RSP and how it might impact performance. The contributions of this thesis are threefold. First, the issue of supporting a general model of CEP in RSP is addressed. A set of requirements for CEP is identified and used to define an event ontology for use in RSP. An approach is then proposed for creating a CEP framework that can scale processing beyond the limitations of a single RSP instance. Second, an extension of the RSP-QL data model is defined for representation of statement-level annotations. The data model is then used as a basis for capturing different types of uncertainty in a use case inspired by a research project in electronic healthcare. Finally, the performance impact of explicitly managing different types of uncertainty is evaluated in a prototype implementation and a set of optimization strategies is introduced with a goal of reducing the impact of uncertainty on query execution performance. The results show that the proposed approach to representing statement-level metadata reduces required data transfer bandwidth and that it can improve query execution performance com-pared with using RDF reification. The optimization strategies produce improved query execution performance overall, but the impact of the heuristic depends on multiple factors, including the selectivity of filters, join cardinalities, and the cost of evaluating uncertainty functions.

    List of papers
    1. Event Processing in RDF
    Open this publication in new window or tab >>Event Processing in RDF
    2013 (English)In: Proceedings of the 4th Workshop on Ontology and Semantic Web Patterns co-located with 12th International Semantic Web Conference (ISWC 2013), CEUR-WS , 2013, Vol. 1188Conference paper, Published paper (Refereed)
    Abstract [en]

    In this study we look at new requirements for event models based on concepts dened for complex event processing. A corresponding model for representing heterogeneous event objects in RDF is dened, building on pre-existing work and focusing on structural aspects, which have not been addressed before, such as composite event objects encapsulating other event objects. SPARQL querying of event objects is also considered, to demonstrate how event objects based on the model can be recognized and processed in a straightforward way with SPARQL 1.1 Query-compliant tools.

    Place, publisher, year, edition, pages
    CEUR-WS, 2013
    Series
    CEUR Workshop Proceedings, ISSN 1613-0073 ; 1188
    Keywords
    Complex Event Processing, Ontology Design Patterns
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-112235 (URN)
    Conference
    4th Workshop on Ontology and Semantic Web Patterns (WOP 2013) co-located with 12th International Semantic Web Conference (ISWC 2013), Sydney, Australia, October 21, 2013
    Available from: 2014-11-19 Created: 2014-11-19 Last updated: 2021-09-21
    2. Supporting Real-Time Monitoring in Criminal Investigations
    Open this publication in new window or tab >>Supporting Real-Time Monitoring in Criminal Investigations
    2015 (English)In: SEMANTIC WEB: ESWC 2015 SATELLITE EVENTS, SPRINGER INT PUBLISHING AG , 2015, Vol. 9341, p. 82-86Conference paper, Published paper (Refereed)
    Abstract [en]

    Being able to analyze information collected from streams of data, generated by different types of sensors, is becoming increasingly important in many domains. This paper presents an approach for creating a decoupled semantically enabled event processing system, which leverages existing Semantic Web technologies. By implementing the actor model, we show how we can create flexible and robust event processing systems, which can leverage different technologies in the same general workflow. We argue that in this context RSP systems can be viewed as generic systems for creating semantically enabled event processing agents. In the demonstration scenario we show how real-time monitoring can be used to support criminal intelligence analysis, and describe how the actor model can be leveraged further to support scalability.

    Place, publisher, year, edition, pages
    SPRINGER INT PUBLISHING AG, 2015
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743 ; 9341
    Keywords
    Semantic event processing; Event processing; RDF stream processing; Actor model; Criminal intelligence
    National Category
    Embedded Systems
    Identifiers
    urn:nbn:se:liu:diva-129183 (URN)10.1007/978-3-319-25639-9_16 (DOI)000374570000016 ()9783319256399 (ISBN)9783319256382 (ISBN)
    Conference
    12th European Semantic Web Conference (ESWC)
    Available from: 2016-06-13 Created: 2016-06-13 Last updated: 2021-09-21
    3. RSP-QL*: Enabling Statement-Level Annotations in RDF Streams
    Open this publication in new window or tab >>RSP-QL*: Enabling Statement-Level Annotations in RDF Streams
    2019 (English)In: Semantic Systems. The Power of AI and Knowledge Graphs - 15th International Conference, SEMANTiCS 2019, Karlsruhe, Germany, September 9-12, 2019, Proceedings, Germany, 2019, p. -55Conference paper, Published paper (Refereed)
    Abstract [en]

    RSP-QL was developed by the W3C RDF Stream Processing (RSP) community group as a common way to express and query RDF streams. However, RSP-QL does not provide any way of annotating data on the statement level, for example, to express the uncertainty that is often associated with streaming information. Instead, the only way to provide such information has been to use RDF reification, which adds additional complexity to query processing, and is syntactically verbose. In this paper, we define an extension of RSP-QL, called RSP-QL*, that provides an intuitive way for supporting statement-level annotations in RSP. The approach leverages the concepts previously described for RDF* and SPARQL*. We illustrate the proposed approach based on a scenario from a research project in e-health. An open-source implementation of the proposal is provided and compared to the baseline approach of using RDF reification. The results show that this way of dealing with statement-level annotations offers advantages with respect to both data transfer bandwidth and query execution performance.

    Place, publisher, year, edition, pages
    Germany: , 2019
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11702
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-168645 (URN)10.1007/978-3-030-33220-4_11 (DOI)978-3-030-33219-8 (ISBN)
    Conference
    15th SEMANTiCS Conference
    Projects
    E-care@homeCENIIT project no. 17.05
    Note

    This paper won the Best Paper Award in the conference.

    Available from: 2020-08-27 Created: 2020-08-27 Last updated: 2022-02-09
    4. Capturing and Querying Uncertainty in RDF Stream Processing
    Open this publication in new window or tab >>Capturing and Querying Uncertainty in RDF Stream Processing
    2020 (English)In: Knowledge Engineering and Knowledge Management - 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020, Proceedings / [ed] C. Maria Keet and Michel Dumontier, 2020Conference paper, Published paper (Refereed)
    Abstract [en]

    RDF Stream Processing (RSP) has been proposed as a candidate for bringing together the Complex Event Processing (CEP) paradigm and the Semantic Web standards. In this paper, we investigate the impact of explicitly representing and processing uncertainty in RSP for the use in CEP. Additionally, we provide a representation for capturing the relevant notions of uncertainty in the RSP-QL* data model and describe query functions that can operate on this representation. The impact evaluation is based on a use case within electronic healthcare, where we compare the query execution overhead of different uncertainty options in a prototype implementation. The experiments show that the influence on query execution performance varies greatly, but that uncertainty can have noticeable impact on query execution performance. On the otherhand, the overhead grows linearly with respect to the stream rate for all uncertainty options in the evaluation, and the observed performance is sufficient for many use cases. Extending the representation and operations to support more uncertainty options and investigating different query optimization strategies to reduce the impact on execution performance remain important areas for future research.

    Series
    Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 12387
    Keywords
    RSP, CEP, Uncertainty, RSP-QL
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-179250 (URN)10.1007/978-3-030-61244-3_3 (DOI)
    Conference
    22nd International Conference on Knowledge Engineering and Knowledge Management (EKAW 2020)
    Available from: 2021-09-15 Created: 2021-09-15 Last updated: 2021-09-21
    5. Optimizing RDF Stream Processing for Uncertainty Management
    Open this publication in new window or tab >>Optimizing RDF Stream Processing for Uncertainty Management
    2021 (English)In: Further with Knowledge Graph, IOS Press, 2021, Vol. 53, p. 118-132Conference paper, Published paper (Refereed)
    Abstract [en]

    RDF Stream Processing (RSP) has been proposed as a way of bridging the gap between the Complex Event Processing (CEP) paradigm and the Semantic Web standards. Uncertainty has been recognized as a critical aspect in CEP, but it has received little attention within the context of RSP. In this paper, we investigate the impact of different RSP optimization strategies for uncertainty management. The paper describes (1) an extension of the RSP-QL* data model to capture bind expressions, filter expressions, and uncertainty functions; (2) optimization techniques related to lazy variables and caching of uncertainty functions, and a heuristic for reordering uncertainty filters in query plans; and (3) an evaluation of these strategies in a prototype implementation. The results show that using a lazy variable mechanism for uncertainty functions can improve query execution performance by orders of magnitude while introducing negligible overhead. The results also show that caching uncertainty function results can improve performance under most conditions, but that maintaining this cache can potentially add overhead to the overall query execution process. Finally, the effect of the proposed heuristic on query execution performance was shown to depend on multiple factors, including the selectivity of uncertainty filters, the size of intermediate results, and the cost associated with the evaluation of the uncertainty functions.

    Place, publisher, year, edition, pages
    IOS Press, 2021
    Series
    Studies on the Semantic Web, ISSN 1868-1158, E-ISSN 2215-0870
    Keywords
    RSP; CEP; Uncertainty, ; RSP-QL
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-179364 (URN)10.3233/SSW210039 (DOI)978-1-64368-200-6 (ISBN)978-1-64368-201-3 (ISBN)
    Conference
    SEMANTiCS 2021
    Note

    This paper has won the Best Paper Award in the conference.

    Available from: 2021-09-20 Created: 2021-09-20 Last updated: 2024-02-01
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    Errata
  • 8.
    Hogan, Aidan
    et al.
    DCC, Universidad de Chile; IMFD .
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Cochez, Michael
    Vrije Universiteit Amsterdam and Discovery Lab, Elsevier .
    d'Amato, Claudia
    University of Bari.
    Melo, Gerard de
    HPI, University of Potsdam and Rutgers University.
    Gutierrez, Claudio
    DCC, Universidad de Chile; IMFD .
    Kirrane, Sabrina
    WU Vienna.
    Gayo, José Emilio Labra
    Universidad de Oviedo.
    Navigli, Roberto
    Sapienza University of Rome.
    Neumaier, Sebastian
    St. Pölten University of Applied Sciences.
    Ngomo, Axel-Cyrille Ngonga
    DICE, Universität Paderborn.
    Polleres, Axel
    WU Vienna.
    Rashid, Sabbir M.
    Tetherless World Constellation.
    Rula, Anisa
    University of Brescia.
    Schmelzeisen, Lukas
    Universität Stuttgart.
    Sequeda, Juan
    data.world .
    Staab, Steffen
    Universität Stuttgart and University of Southampton.
    Zimmermann, Antoine
    École des mines de Saint-Étienne.
    Knowledge Graphs2021Book (Other academic)
    Abstract [en]

    This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale.

    The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve.

    This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.

  • 9.
    Hogan, Aidan
    et al.
    Univ Chile, Chile; IMFD, Chile.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Cochez, Michael
    Vrije Univ Amsterdam, Netherlands; Elsevier, Netherlands.
    DAmato, Claudia
    Univ Bari, Italy.
    de Melo, Gerard
    Rutgers State Univ, NJ USA; HPI, Germany.
    Gutierrez, Claudio
    Univ Chile, Chile; IMFD, Chile.
    Kirrane, Sabrina
    WU Vienna, Austria; Vienna Univ Econ & Business, Austria.
    Labra Gayo, Jose Emilio
    Univ Oviedo, Spain.
    Navigli, Roberto
    Sapienza Univ Rome, Italy.
    Neumaier, Sebastian
    WU Vienna, Austria; FH St Polten, Austria.
    Ngomo, Axel-Cyrille Ngonga
    Paderborn Univ, Germany.
    Polleres, Axel
    WU Vienna, Austria.
    Rashid, Sabbir M.
    Rensselaer Polytech Inst, MA 01603 USA.
    Rula, Anisa
    Univ Milano Bicocca, Italy; Univ Bonn, Germany; Dept Informat Engn, Italy.
    Schmelzeisen, Lukas
    Univ Stuttgart, Germany.
    Sequeda, Juan
    Dataworld, TX 78731 USA.
    Staab, Steffen
    Univ Stuttgart, Germany; Univ Southampton, England.
    Zimmermann, Antoine
    Ecole Mines St Etienne, France.
    Knowledge Graphs2021In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 54, no 4, article id 71Article in journal (Refereed)
    Abstract [en]

    In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.

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  • 10.
    Keskisärkkä, Robin
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Hartig, Olaf
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Optimizing RDF Stream Processing for Uncertainty Management2021In: Further with Knowledge Graph, IOS Press, 2021, Vol. 53, p. 118-132Conference paper (Refereed)
    Abstract [en]

    RDF Stream Processing (RSP) has been proposed as a way of bridging the gap between the Complex Event Processing (CEP) paradigm and the Semantic Web standards. Uncertainty has been recognized as a critical aspect in CEP, but it has received little attention within the context of RSP. In this paper, we investigate the impact of different RSP optimization strategies for uncertainty management. The paper describes (1) an extension of the RSP-QL* data model to capture bind expressions, filter expressions, and uncertainty functions; (2) optimization techniques related to lazy variables and caching of uncertainty functions, and a heuristic for reordering uncertainty filters in query plans; and (3) an evaluation of these strategies in a prototype implementation. The results show that using a lazy variable mechanism for uncertainty functions can improve query execution performance by orders of magnitude while introducing negligible overhead. The results also show that caching uncertainty function results can improve performance under most conditions, but that maintaining this cache can potentially add overhead to the overall query execution process. Finally, the effect of the proposed heuristic on query execution performance was shown to depend on multiple factors, including the selectivity of uncertainty filters, the size of intermediate results, and the cost associated with the evaluation of the uncertainty functions.

    Download full text (pdf)
    fulltext
  • 11.
    Davarakis, Costas
    et al.
    SPIRIT, Greece.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Tiemann, Marco
    Innova Integra Ltd, England.
    Casanovas, Pompeu
    La Trobe Univ, Australia; Autonomous Univ Barcelona, Spain.
    SPIRIT: Semantic and Systemic Interoperability for Identity Resolution in Intelligence Analysis2021In: Ai Approaches to the Complexity of Legal Systems XI-XII, SPRINGER INTERNATIONAL PUBLISHING AG , 2021, Vol. 13048, p. 247-259Conference paper (Refereed)
    Abstract [en]

    This paper introduces the SPIRIT H2020 Project. The SPIRIT identity resolution service has been designed to learn about identity patterns, to build up a social graph related to them, and thereby facilitate LEAs investigation work. The paper will briefly discuss the main task of identity resolution, the privacy controller system, the SPIRIT prototype that will realise the solution, and the ontology to embed privacy into the system. It also discusses a specific technical and legal challenge-i.e., semantic interoperability when integrating SPIRIT dataand its coordination at the agency level with human decision making-systemic interoperability. This paper takes into account the SPIRIT testing prototype and the first revision version (proof of concept prototype).

  • 12.
    Keskisärkkä, Robin
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Hartig, Olaf
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Capturing and Querying Uncertainty in RDF Stream Processing2020In: Knowledge Engineering and Knowledge Management - 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020, Proceedings / [ed] C. Maria Keet and Michel Dumontier, 2020Conference paper (Refereed)
    Abstract [en]

    RDF Stream Processing (RSP) has been proposed as a candidate for bringing together the Complex Event Processing (CEP) paradigm and the Semantic Web standards. In this paper, we investigate the impact of explicitly representing and processing uncertainty in RSP for the use in CEP. Additionally, we provide a representation for capturing the relevant notions of uncertainty in the RSP-QL* data model and describe query functions that can operate on this representation. The impact evaluation is based on a use case within electronic healthcare, where we compare the query execution overhead of different uncertainty options in a prototype implementation. The experiments show that the influence on query execution performance varies greatly, but that uncertainty can have noticeable impact on query execution performance. On the otherhand, the overhead grows linearly with respect to the stream rate for all uncertainty options in the evaluation, and the observed performance is sufficient for many use cases. Extending the representation and operations to support more uncertainty options and investigating different query optimization strategies to reduce the impact on execution performance remain important areas for future research.

  • 13.
    Vestin, Sanna
    et al.
    Flyktinggruppernas Riksråd, FARR.
    Lundberg, Anna
    Linköping University, Department of Social and Welfare Studies, Social Work. Linköping University, Faculty of Arts and Sciences.
    Asyllagen – ett stort socialt experiment: Asylkommissionen: Vårt mål är att ge dem som drabbats upprättelse2019In: Aftonbladet, ISSN 1103-9000, no 19 juniArticle in journal (Other (popular science, discussion, etc.))
    Abstract [sv]

    Efter flera år av snabba lagändringar på asylområdet kommer allt fler alarmerande rapporter om att människor på flykt, inte minst barn och unga, far illa efter att ha sökt asyl i Sverige.

    Därför bildas nu en granskningskommission för att undersöka vad det är som hänt och hur situationen kan förbättras.

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    Asyllagen – ett stort socialt experiment: Asylkommissionen: Vårt mål är att ge dem som drabbats upprättelse
  • 14.
    Tommasini, Riccardo
    et al.
    Politecn Milan, Italy.
    Keskisärkkä, Robin
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Calbimonte, Jean-Paul
    HES SO, Switzerland.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Della Valle, Emanuele
    Politecn Milan, Italy.
    Bifet, Albert
    Telecom ParisTech, France.
    Continuous Analytics of Web Streams Half-Day Tutorial at The Web Conference 20192019In: COMPANION OF THE WORLD WIDE WEB CONFERENCE (WWW 2019 ), ASSOC COMPUTING MACHINERY , 2019, p. 1323-1325Conference paper (Refereed)
    Abstract [en]

    This half-day tutorial provides a comprehensive introduction to web stream processing, including the fundamental stream reasoning concepts, as well as an introduction to practical implementations and how to use them in concrete web applications. To this extent, we intend to (1) survey existing research outcomes from Stream Reasoning / RDF Stream Processing that arise in querying, reasoning on and learning from a variety of highly dynamic data, (2) introduce deductive and inductive stream reasoning techniques as powerful tools to use when addressing a data-centric problem characterized both by variety and velocity, (3) present a relevant use-case, which requires to address data velocity and variety simultaneously on the web, and guide the participants in developing a web stream processing application.

  • 15.
    Santini, Marina
    et al.
    RISE Research Institutes of Sweden, Sweden.
    Jönsson, Arne
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. RISE Research Institutes of Sweden, Sweden.
    Strandqvist, Wiktor
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. RISE Research Institutes of Sweden, Sweden.
    Cederblad, Gustav
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. RISE Research Institutes of Sweden, Sweden.
    Alirezaie, Marjan
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Lind, Leili
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. RISE Research Institutes of Sweden, Sweden.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. RISE Research Institutes of Sweden, Sweden.
    Lindén, Maria
    Mälardalen University, Sweden.
    Kristoffersson, Annica
    Institutionen för naturvetenskap och teknik, Örebro universitet.
    Designing an Extensible Domain-Specific Web Corpus for “Layfication”: A Case Study in eCare at Home2019In: Cyber-Physical Systems for Social Applications / [ed] Maya Dimitrova and Hiroaki Wagatsuma, Hershey, PA, USA: IGI Global, 2019, p. 98-155Chapter in book (Refereed)
    Abstract [en]

    In the era of data-driven science, corpus-based language technology is an essential part of cyber physical systems. In this chapter, the authors describe the design and the development of an extensible domain-specific web corpus to be used in a distributed social application for the care of the elderly at home. The domain of interest is the medical field of chronic diseases. The corpus is conceived as a flexible and extensible textual resource, where additional documents and additional languages will be appended over time. The main purpose of the corpus is to be used for building and training language technology applications for the “layfication” of the specialized medical jargon. “Layfication” refers to the automatic identification of more intuitive linguistic expressions that can help laypeople (e.g., patients, family caregivers, and home care aides) understand medical terms, which often appear opaque. Exploratory experiments are presented and discussed.

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    Designing an Extensible Domain-Specific Web Corpus for “Layfication”: A Case Study in eCare at Home
  • 16.
    Dórea, Fernanda C.
    et al.
    Department of Disease Control and Epidemiology, National Veterinary Institute, Sweden.
    Vial, Flavie
    Epi-Connect, Skogås, Sweden.
    Hammar, Karl
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. Department of Computer Science and Informatics, Jönköping University, Sweden.
    Lindberg, Ann
    Department of Disease Control and Epidemiology, National Veterinary Institute, Sweden.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Revie, Crawford W.
    Atlantic Veterinary College, University of Prince Edward Island, Canada.
    Drivers for the development of an Animal Health Surveillance Ontology (AHSO)2019In: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 166, no 1, p. 39-48Article in journal (Refereed)
    Abstract [en]

    Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems when data emerge from different sources. Discussions with syndromic surveillance experts in the fields of animal and public health, as well as computer scientists from the field of information management, have led to the conclusion that a major component of any solution will involve the adoption of ontologies. Here we describe the advantages of such an approach, and the steps taken to set up the Animal Health Surveillance Ontological (AHSO) framework. The AHSO framework is modelled in OWL, the W3C standard Semantic Web language for representing rich and complex knowledge. We illustrate how the framework can incorporate knowledge directly from domain experts or from data-driven sources, as well as by integrating existing mature ontological components from related disciplines. The development and extent of AHSO will be community driven and the final products in the framework will be open-access.

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  • 17.
    Keskisärkkä, Robin
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Lind, Leili
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Hartig, Olaf
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    RSP-QL*: Enabling Statement-Level Annotations in RDF Streams2019In: Semantic Systems. The Power of AI and Knowledge Graphs - 15th International Conference, SEMANTiCS 2019, Karlsruhe, Germany, September 9-12, 2019, Proceedings, Germany, 2019, p. -55Conference paper (Refereed)
    Abstract [en]

    RSP-QL was developed by the W3C RDF Stream Processing (RSP) community group as a common way to express and query RDF streams. However, RSP-QL does not provide any way of annotating data on the statement level, for example, to express the uncertainty that is often associated with streaming information. Instead, the only way to provide such information has been to use RDF reification, which adds additional complexity to query processing, and is syntactically verbose. In this paper, we define an extension of RSP-QL, called RSP-QL*, that provides an intuitive way for supporting statement-level annotations in RSP. The approach leverages the concepts previously described for RDF* and SPARQL*. We illustrate the proposed approach based on a scenario from a research project in e-health. An open-source implementation of the proposal is provided and compared to the baseline approach of using RDF reification. The results show that this way of dealing with statement-level annotations offers advantages with respect to both data transfer bandwidth and query execution performance.

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  • 18.
    Alirezaie, Marjan
    et al.
    Orebro Univ, Sweden.
    Hammar, Karl
    RCS East Swedish ICT, Linkoping, Sweden; Jonkoping Univ, Sweden.
    Blomqvist, Eva
    RCS East Swedish ICT, Linkoping, Sweden.
    SmartEnv as a network of ontology patterns2018In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 9, no 6, p. 903-918Article in journal (Refereed)
    Abstract [en]

    In this article we outline the details of an ontology, called SmartEnv, proposed as a representational model to assist the development process of smart (i.e., sensorized) environments. The SmartEnv ontology is described in terms of its modules representing different aspects including physical and conceptual aspects of a smart environment. We propose the use of the Ontology Design Pattern (ODP) paradigm in order to modularize our proposed solution, while at the same time avoiding strong dependencies between the modules in order to manage the representational complexity of the ontology. The ODP paradigm and related methodologies enable incremental construction of ontologies by first creating and then linking small modules. Most modules (patterns) of the SmartEnv ontology are inspired by, and aligned with, the Semantic Sensor Network (SSN) ontology, however with extra interlinks to provide further precision and cover more representational aspects. The result is a network of 8 ontology patterns together forming a generic representation for a smart environment. The patterns have been submitted to the ODP portal and are available on-line at stable URIs.

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  • 19.
    Alirezaie, Marjan
    et al.
    Institutionen för naturvetenskap och teknik , Örebro Universitet.
    Hammar, Karl
    Högskolan i Jönköping, JTH, Datateknik och informatik.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Ivanova, Valentina
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    SmartEnv Ontology in E-care@home2018In: SSN 2018 - Semantic Sensor Networks Workshop: Proceedings of the 9th International Semantic Sensor Networks Workshopco-located with 17th International Semantic Web Conference (ISWC 2018) / [ed] Maxime Lefrançois, Raúl Garcia Castro, Amélie Gyrard, Kerry Taylor, CEUR-WS , 2018, Vol. 2213, p. 72-79Conference paper (Refereed)
    Abstract [en]

    In this position paper we briefly introduce SmartEnv ontology which relies on SEmantic Sensor Network (SSN) ontology and is used to represent different aspects of smart and sensorized environments. We will also talk about E-carehome project aiming at providing an IoT-based health-care system for elderly people at their homes. Furthermore, we refer to the role of SmartEnv in Ecarehome and how it needs to be further extended to achieve semantic interoperability as one of the challenges in development of autonomous health care systems at home.

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    SmartEnv Ontology in E-care@home
  • 20.
    Zhang, Ziqi
    et al.
    University of Sheffield, England.
    Gentile, Anna Lisa
    University of Sheffield, England.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Augenstein, Isabelle
    University of Sheffield, England.
    Ciravegna, Fabio
    University of Sheffield, England.
    An Unsupervised Data-driven Method to Discover Equivalent Relations in Large Linked Datasets2017In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 8, no 2Article in journal (Refereed)
    Abstract [en]

    This article addresses a number of limitations of state-of-the-art methods of Ontology Alignment: 1) they primarily address concepts and entities while relations are less well-studied; 2) many build on the assumption of the well-formedness of ontologies which is unnecessarily true in the domain of Linked Open Data; 3) few have looked at schema heterogeneity from a single source, which is also a common issue particularly in very large Linked Dataset created automatically from heterogeneous resources, or integrated from multiple datasets. We propose a domain-and language-independent and completely unsupervised method to align equivalent relations across schemata based on their shared instances. We introduce a novel similarity measure able to cope with unbalanced population of schema elements, an unsupervised technique to automatically decide similarity threshold to assert equivalence for a pair of relations, and an unsupervised clustering process to discover groups of equivalent relations across different schemata. Although the method is designed for aligning relations within a single dataset, it can also be adapted for cross-dataset alignment where sameAs links between datasets have been established. Using three gold standards created based on DBpedia, we obtain encouraging results from a thorough evaluation involving four baseline similarity measures and over 15 comparative models based on variants of the proposed method. The proposed method makes significant improvement over baseline models in terms of F1 measure (mostly between 7% and 40%), and it always scores the highest precision and is also among the top performers in terms of recall. We also make public the datasets used in this work, which we believe make the largest collection of gold standards for evaluating relation alignment in the LOD context.

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  • 21. Order onlineBuy this publication >>
    Hammar, Karl
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. Tekniska Högskolan i Jönköping.
    Content Ontology Design Patterns: Qualities, Methods, and Tools2017Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Ontologies are formal knowledge models that describe concepts and relationships and enable data integration, information search, and reasoning. Ontology Design Patterns (ODPs) are reusable solutions intended to simplify ontology development and support the use of semantic technologies by ontology engineers. ODPs document and package good modelling practices for reuse, ideally enabling inexperienced ontologists to construct high-quality ontologies. Although ODPs are already used for development, there are still remaining challenges that have not been addressed in the literature. These research gaps include a lack of knowledge about (1) which ODP features are important for ontology engineering, (2) less experienced developers' preferences and barriers for employing ODP tooling, and (3) the suitability of the eXtreme Design (XD) ODP usage methodology in non-academic contexts.

    This dissertation aims to close these gaps by combining quantitative and qualitative methods, primarily based on five ontology engineering projects involving inexperienced ontologists. A series of ontology engineering workshops and surveys provided data about developer preferences regarding ODP features, ODP usage methodology, and ODP tooling needs. Other data sources are ontologies and ODPs published on the web, which have been studied in detail. To evaluate tooling improvements, experimental approaches provide data from comparison of new tools and techniques against established alternatives.

    The analysis of the gathered data resulted in a set of measurable quality indicators that cover aspects of ODP documentation, formal representation or axiomatisation, and usage by ontologists. These indicators highlight quality trade-offs: for instance, between ODP Learnability and Reusability, or between Functional Suitability and Performance Efficiency. Furthermore, the results demonstrate a need for ODP tools that support three novel property specialisation strategies, and highlight the preference of inexperienced developers for template-based ODP instantiation---neither of which are supported in prior tooling. The studies also resulted in improvements to ODP search engines based on ODP-specific attributes. Finally, the analysis shows that XD should include guidance for the developer roles and responsibilities in ontology engineering projects, suggestions on how to reuse existing ontology resources, and approaches for adapting XD to project-specific contexts.

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    Content Ontology Design Patterns: Qualities, Methods, and Tools
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  • 22.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Maynard, DianaUniversity of Sheffield.Gangemi, AldoParis Nord University.Hoekstra, RinkeVrije Universiteit Amsterdam.Hitzler, PascalWright State University.Hartig, OlafLinköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    The Semantic Web - 14th International Conference, ESWC 2017, Portorož, Slovenia, May 28 - June 1, 2017, Proceedings, Part I2017Conference proceedings (editor) (Refereed)
  • 23.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Maynard, DianaUniversity of Sheffield.Gangemi, AldoParis Nord University.Hoekstra, RinkeVrije Universiteit Amsterdam.Hitzler, PascalWright State University.Hartig, OlafLinköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    The Semantic Web - 14th International Conference, ESWC 2017, Portorož, Slovenia, May 28 - June 1, 2017, Proceedings, Part II2017Conference proceedings (editor) (Refereed)
  • 24.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Hose, KatjaAalborg University.Paulheim, HeikoUniversity of Mannheim.Ławrynowicz, AgnieszkaPoznan University of Technology.Ciravegna, FabioUniversity of Sheffield.Hartig, OlafLinköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    The Semantic Web: ESWC 2017 Satellite Events - ESWC 2017 Satellite Events, Portorož, Slovenia, May 28 - June 1, 2017, Revised Selected Papers2017Conference proceedings (editor) (Refereed)
  • 25. Order onlineBuy this publication >>
    Keskisärkkä, Robin
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Towards Semantically Enabled Complex Event Processing2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The Semantic Web provides a framework for semantically annotating data on the web, and the Resource Description Framework (RDF) supports the integration of structured data represented in heterogeneous formats. Traditionally, the Semantic Web has focused primarily on more or less static data, but information on the web today is becoming increasingly dynamic. RDF Stream Processing (RSP) systems address this issue by adding support for streaming data and continuous query processing. To some extent, RSP systems can be used to perform complex event processing (CEP), where meaningful high-level events are generated based on low-level events from multiple sources; however, there are several challenges with respect to using RSP in this context. Event models designed to represent static event information lack several features required for CEP, and are typically not well suited for stream reasoning. The dynamic nature of streaming data also greatly complicates the development and validation of RSP queries. Therefore, reusing queries that have been prepared ahead of time is important to be able to support real-time decision-making. Additionally, there are limitations in existing RSP implementations in terms of both scalability and expressiveness, where some features required in CEP are not supported by any of the current systems. The goal of this thesis work has been to address some of these challenges and the main contributions of the thesis are: (1) an event model ontology targeted at supporting CEP; (2) a model for representing parameterized RSP queries as reusable templates; and (3) an architecture that allows RSP systems to be integrated for use in CEP. The proposed event model tackles issues specifically related to event modeling in CEP that have not been sufficiently covered by other event models, includes support for event encapsulation and event payloads, and can easily be extended to fit specific use-cases. The model for representing RSP query templates was designed as an extension to SPIN, a vocabulary that supports modeling of SPARQL queries as RDF. The extended model supports the current version of the RSP Query Language (RSP-QL) developed by the RDF Stream Processing Community Group, along with some of the most popular RSP query languages. Finally, the proposed architecture views RSP queries as individual event processing agents in a more general CEP framework. Additional event processing components can be integrated to provide support for operations that are not supported in RSP, or to provide more efficient processing for specific tasks. We demonstrate the architecture in implementations for scenarios related to traffic-incident monitoring, criminal-activity monitoring, and electronic healthcare monitoring.

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    Towards Semantically Enabled Complex Event Processing
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  • 26.
    Hammar, Karl
    et al.
    Jönköping University.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Carral, David
    Technische Universität Dresden, Germany.
    van Erp, Marieke
    Fokkens, Antske
    Gangemi, Aldo
    van Hage, Willem Robert
    Hitzler, Pascal
    Janowicz, Krzysztof
    Karima, Nazifa
    Krisnadhi, Adila
    Narock, Tom
    Segers, Roxane
    Solanki, Monika
    Svátek, Vojtech
    Collected Research Questions Concerning Ontology Design Patterns2016In: Ontology Engineering with Ontology Design Patterns: Foundations and Applications / [ed] Pascal Hitzler, Aldo Gangemi, Krzysztof Janowicz, Adila Krisnadhi, Valentina Presutti, IOS Press, 2016, p. 189-198Chapter in book (Other academic)
  • 27.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Arts and Sciences.
    Hitzler, Pascal
    Wright State University, OH 45435 USA.
    Janowicz, Krzysztof
    University of Calif Santa Barbara, CA 93106 USA.
    Krisnadhi, Adila
    Wright State University, OH 45435 USA; University of Indonesia, Indonesia.
    Narocke, Tom
    Marymount University, VA USA.
    Solanki, Monika
    University of Oxford, England.
    Considerations regarding Ontology Design Patterns in SEMANTIC WEB, vol 7, issue 1, pp2016In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 7, no 1Article in journal (Other academic)
    Abstract [en]

    n/a

  • 28.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Hammar, Karl
    Computer Science and Informatics, School of Engineering, Jönköping University, Sweden.
    Presutti, Valentina
    Institute of Cognitive Sciences and Technologies, Italy.
    Engineering Ontologies with Patterns: The eXtreme Design Methodology2016In: Ontology Engineering with Ontology Design Patterns: Foundations and Applications / [ed] Pascal Hitzler, Aldo Gangemi, Krzysztof Janowicz, Adila Krisnadhi, Valentina Presutti, IOS Press, 2016, p. 23-50Chapter in book (Other academic)
    Abstract [en]

    When using Ontology Design Patterns (ODPs) for modelling new parts of an ontology, i.e., new ontology modules, or even an entire ontology from scratch, ODPs can be used both as inspiration for different modelling solutions, as well as concrete templates or even “building blocks” reused directly in the new solution. This chapter discusses how ODPs, and in particular Content ODPs

    In fact, throughout this chapter when mentioning ODPs, this mainly refers to Content ODPs if not specified further.

    , can be used in ontology engineering. In particular, a specific ontology engineering methodology is presented, which was originally developed for supporting ODP use. However, this methodology, the eXtreme Design (XD), also has some characteristics that set it apart from most other ontology engineering methodologies, and which may be interesting to consider regardless of how much emphasis is put on the ODP usage. Towards the end of the chapter some XD use cases are also reported and discussed, as well as lessons learned from applying XD. The chapter is concluded through a summary and discussion about future work.

  • 29.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Arts and Sciences.
    Thollander, Patrik
    Linköping University, Department of Management and Engineering, Energy Systems. Linköping University, Faculty of Science & Engineering.
    An integrated dataset of energy efficiency measures published as linked open data2015In: Energy Efficiency, ISSN 1570-646X, E-ISSN 1570-6478, Vol. 8, no 6, p. 1125-1147Article in journal (Refereed)
    Abstract [en]

    Despite an extensive energy efficiency potential, measures are sometimes not adopted due to barriers, such as lack of information. An integrated database of available energy efficiency measures, which has not existed previously, is one step towards overcoming such barriers. To address this, we present a dataset (i.e., data-base) integrating energy efficiency data from Sweden (from the Swedish Energy Agency) and the USA (from the Department of Energys Industrial Assessment Centers), and publishing the data on the Web, using standardized Web languages and following the principles and best practices of so-called linked data. Additionally, several demonstration interfaces to access the data are provided, in order to show the potential of the result. These are entirely novel results, since this is the first dataset we are aware of that publishes this type of data using linked data principles and standards, thus integrating data from entirely different sources making them jointly searchable and reusable. Our results show that such data integration is possible, and that the integrated dataset has several benefits for different categories of users, e.g., supporting industry and energy efficiency auditors in overcoming the information barrier for investment in energy efficiency measures, and supporting application developers to more easily integrate such data into support tools for energy efficiency assessment.

  • 30.
    Dragisic, Zlatan
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Integrating Ontology Debugging and Matching into the eXtreme Design Methodology2015In: Proceedings of the 6th Workshop on Ontology and Semantic Web Patterns (WOP 2015) / [ed] Eva Blomqvist; Pascal Hitzler; Adila Krisnadhi; Tom Narock; Monika Solanki, Rheinisch-Westfaelische Technische Hochschule Aachen University , 2015Conference paper (Refereed)
    Abstract [en]

    Ontology design patterns (ODPs) and related ontology development methodologies were designed as ways of sharing and reusing best practices in ontology engineering. However, while the use of these reduces the number of issues in the resulting ontologies defects can still be introduced into the ontology due to improper use or misinterpretation of the patterns. Thus, the quality of the developed ontologies is still a major concern. In this paper we address this issue by describing how ontology debugging and matching can be integrated in a state-of-the-art ontology development methodology based on ontology design patterns- the eXtreme Design methodology, and show the advantages in a case study based on a real world ontology.

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  • 31.
    Lambrix, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Hyvönen, EeroAalto University, Finland.Blomqvist, EvaLinköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.Presutti, ValentinaSTLab ISTC-CNR, Italy.Qi, GuilinSoutheast University, China.Sattler, UliUniversity of Manchester, UK.Ding, YingIndiana University Bloomingtom, USA.Ghidini, ChiaraFondazione Bruno Kessler, Italy.
    Knowledge Engineering and Knowledge Management: EKAW 2014 Satellite Events, VISUAL, EKM1, and ARCOE-Logic, Linköping, Sweden, November 24-28, 2014. Revised Selected Papers2015Conference proceedings (editor) (Refereed)
    Abstract [en]

    This volume contains the Satellite Events proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2014), held in Linköping, Sweden, during November 24–28, 2014. This was the first EKAW conference in a Nordic country. It was concerned with all aspects of eliciting, acquiring, modeling, and managing knowledge, the construction of knowledge-intensive systems and services for the Semantic Web, knowledge management, e-business, natural language processing, intelligent information integration, personal digital assistance systems, and a variety of other related topics. The special focus of EKAW2014 was Diversity.

  • 32.
    Keskisärkkä, Robin
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Supporting Real-Time Monitoring in Criminal Investigations2015In: SEMANTIC WEB: ESWC 2015 SATELLITE EVENTS, SPRINGER INT PUBLISHING AG , 2015, Vol. 9341, p. 82-86Conference paper (Refereed)
    Abstract [en]

    Being able to analyze information collected from streams of data, generated by different types of sensors, is becoming increasingly important in many domains. This paper presents an approach for creating a decoupled semantically enabled event processing system, which leverages existing Semantic Web technologies. By implementing the actor model, we show how we can create flexible and robust event processing systems, which can leverage different technologies in the same general workflow. We argue that in this context RSP systems can be viewed as generic systems for creating semantically enabled event processing agents. In the demonstration scenario we show how real-time monitoring can be used to support criminal intelligence analysis, and describe how the actor model can be leveraged further to support scalability.

  • 33.
    Timpka, Toomas
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Health and Developmental Care, Center for Public Health.
    Spreco, Armin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research.
    Eriksson, Olle
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Gursky, Elin
    National Strategies Support Directorate, ANSER/Analytic Services Inc., Arlington, VA, USA.
    Ekberg, Joakim
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Strömgren, Magnus
    Department of Geography and Economic History, Umeå University, Sweden.
    Karlsson, David
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Eriksson, Henrik
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Nyce, James
    Department of Anthropology, Ball State University, Muncie, IN, USA.
    Hinkula, Jorma
    Linköping University, Department of Clinical and Experimental Medicine, Division of Microbiology and Molecular Medicine. Linköping University, Faculty of Health Sciences.
    Holm, Einar
    Department of Geography and Economic History, Umeå University, Sweden.
    Performance of eHealth data sources in local influenza surveillance: a 5-year open cohort study2014In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 16, no 4, p. e116-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: There is abundant global interest in using syndromic data from population-wide health information systems--referred to as eHealth resources--to improve infectious disease surveillance. Recently, the necessity for these systems to achieve two potentially conflicting requirements has been emphasized. First, they must be evidence-based; second, they must be adjusted for the diversity of populations, lifestyles, and environments.

    OBJECTIVE: The primary objective was to examine correlations between data from Google Flu Trends (GFT), computer-supported telenursing centers, health service websites, and influenza case rates during seasonal and pandemic influenza outbreaks. The secondary objective was to investigate associations between eHealth data, media coverage, and the interaction between circulating influenza strain(s) and the age-related population immunity.

    METHODS: An open cohort design was used for a five-year study in a Swedish county (population 427,000). Syndromic eHealth data were collected from GFT, telenursing call centers, and local health service website visits at page level. Data on mass media coverage of influenza was collected from the major regional newspaper. The performance of eHealth data in surveillance was measured by correlation effect size and time lag to clinically diagnosed influenza cases.

    RESULTS: Local media coverage data and influenza case rates showed correlations with large effect sizes only for the influenza A (A) pH1N1 outbreak in 2009 (r=.74, 95% CI .42-.90; P<.001) and the severe seasonal A H3N2 outbreak in 2011-2012 (r=.79, 95% CI .42-.93; P=.001), with media coverage preceding case rates with one week. Correlations between GFT and influenza case data showed large effect sizes for all outbreaks, the largest being the seasonal A H3N2 outbreak in 2008-2009 (r=.96, 95% CI .88-.99; P<.001). The preceding time lag decreased from two weeks during the first outbreaks to one week from the 2009 A pH1N1 pandemic. Telenursing data and influenza case data showed correlations with large effect sizes for all outbreaks after the seasonal B and A H1 outbreak in 2007-2008, with a time lag decreasing from two weeks for the seasonal A H3N2 outbreak in 2008-2009 (r=.95, 95% CI .82-.98; P<.001) to none for the A p H1N1 outbreak in 2009 (r=.84, 95% CI .62-.94; P<.001). Large effect sizes were also observed between website visits and influenza case data.

    CONCLUSIONS: Correlations between the eHealth data and influenza case rates in a Swedish county showed large effect sizes throughout a five-year period, while the time lag between signals in eHealth data and influenza rates changed. Further research is needed on analytic methods for adjusting eHealth surveillance systems to shifts in media coverage and to variations in age-group related immunity between virus strains. The results can be used to inform the development of alert-generating eHealth surveillance systems that can be subject for prospective evaluations in routine public health practice.

  • 34.
    Presutti, Valentina
    et al.
    ISTC-CNR.
    Blomqvist, EvaLinköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.Troncy, RaphaëlSack, HaraldPapadakis, IoannisTordai, Anna
    The Semantic Web: ESWC 2014 Satellite Events - ESWC 2014 Satellite Events, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers2014Conference proceedings (editor) (Other academic)
  • 35.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    The use of Semantic Web technologies for decision support – a survey2014In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 5, no 3, p. 177-201Article in journal (Refereed)
    Abstract [en]

    The Semantic Web shares many goals with Decision Support Systems (DSS), e.g., being able to precisely interpret information, in order to deliver relevant, reliable and accurate information to a user when and where it is needed. DSS have in addition more specific goals, since the information need is targeted towards making a particular decision, e.g., making a plan or reacting to a certain situation. When surveying DSS literature, we discover applications ranging from Business Intelligence, via general purpose social networking and collaboration support, Information Retrieval and Knowledge Management, to situation awareness, emergency management, and simulation systems. The unifying element is primarily the purpose of the systems, and their focus on information management and provision, rather than the specific technologies they employ to reach these goals. Semantic Web technologies have been used in DSS during the past decade to solve a number of different tasks, such as information integration and sharing, web service annotation and discovery, and knowledge representation and reasoning. In this survey article, we present the results of a structured literature survey of Semantic Web technologies in DSS, together with the results of interviews with DSS researchers and developers both in industry and research organizations outside the university. The literature survey has been conducted using a structured method, where papers are selected from the publisher databases of some of the most prominent conferences and journals in both fields (Semantic Web and DSS), based on sets of relevant keywords representing the intersection of the two fields. Our main contribution is to analyze the landscape of semantic technologies in DSS, and provide an overview of current research as well as open research areas, trends and new directions. An added value is the conclusions drawn from interviews with DSS practitioners, which give an additional perspective on the potential of Semantic Web technologies in this field; including scenarios for DSS, and requirements for Semantic Web technologies that may attempt to support those scenarios.

  • 36.
    Keskisärkkä, Robin
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Event Object Boundaries in RDF Streams2013In: Proceedings of the 2nd International Workshop on Ordering and Reasoning, Co-located with the 12th International Semantic Web Conference (ISWC 2013), CEUR-WS , 2013, Vol. 1059, p. 37-42Conference paper (Refereed)
    Abstract [en]

    The amount of information available as online streams is increasing steadily. A number of RDF stream processing systems have been developed in an attempt to leverage existing Semantic Web technologies, and to support typical stream operations, but very little attention has been paid to the way in which event objects (i.e. data records representing events) are streamed. In this position paper, we present the issue of respecting event object boundaries in RDF streams, and discuss some pros and cons of the various solutions

  • 37.
    Rinne, Mikko
    et al.
    Aalto University, Finland.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Keskisärkkä, Robin
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Nuutila, Esko
    Aalto University, Finland.
    Event Processing in RDF2013In: Proceedings of the 4th Workshop on Ontology and Semantic Web Patterns co-located with 12th International Semantic Web Conference (ISWC 2013), CEUR-WS , 2013, Vol. 1188Conference paper (Refereed)
    Abstract [en]

    In this study we look at new requirements for event models based on concepts dened for complex event processing. A corresponding model for representing heterogeneous event objects in RDF is dened, building on pre-existing work and focusing on structural aspects, which have not been addressed before, such as composite event objects encapsulating other event objects. SPARQL querying of event objects is also considered, to demonstrate how event objects based on the model can be recognized and processed in a straightforward way with SPARQL 1.1 Query-compliant tools.

  • 38. Sabou, Marta
    et al.
    Blomqvist, EvaLinköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.Noia, Tommaso DiSack, HaraldPellegrini, Tassilo
    I-SEMANTICS 2013 - 9th International Conference on Semantic Systems, ISEM ’13, Graz, Austria, September 4-6, 20132013Conference proceedings (editor) (Other academic)
  • 39.
    Zhang, Ziqi
    et al.
    University of Sheffield, UK.
    Gentile, Anna Lisa
    University of Sheffield, UK.
    Augenstein, Isabelle
    University of Sheffield, UK.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Ciravegna, Fabio
    University of Sheffield, UK.
    Mining Equivalent Relations from Linked Data2013In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Volume 2: Short Papers, Association for Computational Linguistics, 2013, p. 289-293Conference paper (Refereed)
    Abstract [en]

    Linking heterogeneous resources is a major research challenge in the Semantic Web. This paper studies the task of mining equivalent relations from Linked Data, which was insufficiently addressed before. We introduce an unsupervised method to measure equivalency of relation pairs and cluster equivalent relations. Early experiments have shown encouraging results with an average of 0.75~0.87 precision in predicting relation pair equivalency and 0.78~0.98 precision in relation clustering.

  • 40.
    Timpka, Toomas
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Health and Developmental Care, Center for Public Health.
    Spreco, Armin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences.
    Dahlström, Örjan
    Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences.
    Eriksson, Henrik
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Gursky, Elin
    ANSER/Analytic Services Inc, Arlington, Virginia, USA.
    Ekberg, Joakim
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Arts and Sciences.
    Strömgren, Magnus
    Umeå University, Sweden.
    Karlsson, David
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Eriksson, Henrik
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Nyce, Jim
    Ball State University, Muncie, IN, USA.
    Hinkula, Jorma
    Linköping University, Department of Clinical and Experimental Medicine, Division of Microbiology and Molecular Medicine. Linköping University, Faculty of Health Sciences.
    Holm, Einar
    Umeå University, Sweden.
    Performance of eHealth data sources in local influenza surveillance: a 5-year open cohort study using data from Google Flu Trends, telenursing call centres, health service provider web-pages, and mass media coverage2013Conference paper (Other academic)
  • 41.
    Timpka, Toomas
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Health and Developmental Care, Center for Public Health.
    Spreco, Armin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Health and Developmental Care, Center for Public Health.
    Dahlström, Örjan
    Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences.
    Eriksson, Olle
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Gursky, Elin
    ANSER/Analytic Services Inc, Arlington, Virginia, USA.
    Ekberg, Joakim
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Arts and Sciences.
    Strömgren, Magnus
    Umeå University, Sweden.
    Karlsson, David
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Eriksson, Henrik
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Nyce, Jim
    Ball State University, Muncie, IN, USA.
    Hinkula, Jorma
    Linköping University, Department of Clinical and Experimental Medicine, Division of Microbiology and Molecular Medicine. Linköping University, Faculty of Health Sciences.
    Holm, Einar
    Umeå University, Sweden.
    Predictive value of telenursing complaints in influenza surveillance: a prospective cohort study in Sweden2013Conference paper (Other academic)
  • 42.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Groza, Tudor
    Proceedings of the ISWC 2013 Posters & Demonstrations Track, Sydney, Australia, October 23, 20132013Conference proceedings (editor) (Other academic)
  • 43.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Zhang, Ziqi
    University of Sheffield, UK.
    Gentile, Anna Lisa
    University of Sheffield, UK.
    Augenstein, Isabelle
    University of Sheffield, UK.
    Ciravegna, Fabio
    University of Sheffield, UK.
    Statistical Knowledge Patterns for Characterising Linked Data2013In: Proceedings of the 4th Workshop on Ontology and Semantic Web Patterns (WOP 2013)  co-located with 12th International Semantic Web Conference (ISWC 2013), CEUR-WS , 2013, Vol. 1188Conference paper (Refereed)
    Abstract [en]

    Knowledge Patterns (KPs), and even more specifically Ontology Design Patterns (ODPs), are no longer only generated in a top-down fashion, rather patterns are being extracted in a bottom-up fashion from online ontologies and data sources, such as Linked Data. These KPs can assist in tasks such as making sense of datasets and formulating queries over data, including performing query expansion to manage the diversity of properties used in datasets. This paper presents an extraction method for generating what we call Statistical Knowledge Patterns (SKPs) from Linked Data. SKPs describe and characterise classes from any reference ontology, by presenting their most frequent properties and property characteristics, all based on analysis of the underlying data. SKPs are stored as small OWL ontologies but can be continuously updated in a completely automated fashion. In the paper we exemplify this method by applying it to the classes of the DBpedia ontology, and in particular we evaluate our method for extracting range axioms from data. Results show that by setting appropriate thresholds, SKPs can be generated that cover (i.e. allow us to query, using the properties of the SKP) over 94% of the triples about individuals of that class, while only needing to care about 27% of the total number of distinct properties that are used in the data.

  • 44.
    Zhang, Ziqi
    et al.
    University of Sheffield, UK.
    Gentile, Anna Lisa
    University of Sheffield, UK.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Augenstein, Isabelle
    University of Sheffield, UK.
    Ciravegna, Fabio
    University of Sheffield, UK.
    Statistical Knowledge Patterns: Identifying Synonymous Relations in Large Linked Datasets2013In: The Semantic Web – ISWC 2013: 12th International Semantic Web Conference, Sydney, NSW, Australia, October 21-25, 2013, Proceedings, Part I, Springer Berlin/Heidelberg, 2013, Vol. 8218, p. 703-719Conference paper (Refereed)
    Abstract [en]

    The Web of Data is a rich common resource with billions of triples available in thousands of datasets and individual Web documents created by both expert and non-expert ontologists. A common problem is the imprecision in the use of vocabularies: annotators can misunderstand the semantics of a class or property or may not be able to find the right objects to annotate with. This decreases the quality of data and may eventually hamper its usability over large scale. This paper describes Statistical Knowledge Patterns (SKP) as a means to address this issue. SKPs encapsulate key information about ontology classes, including synonymous properties in (and across) datasets, and are automatically generated based on statistical data analysis. SKPs can be effectively used to automatically normalise data, and hence increase recall in querying. Both pattern extraction and pattern usage are completely automated. The main benefits of SKPs are that: (1) their structure allows for both accurate query expansion and restriction; (2) they are context dependent, hence they describe the usage and meaning of properties in the context of a particular class; and (3) they can be generated offline, hence the equivalence among relations can be used efficiently at run time.

  • 45.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Rinne, Mikko
    Aalto University, Finland.
    The Event Processing ODP2013In: Proceedings of the 4th Workshop on Ontology and Semantic Web Patterns co-located with 12th International Semantic Web Conference (ISWC 2013), CEUR-WS , 2013, Vol. 1188Conference paper (Refereed)
    Abstract [en]

    In this abstract we present a model for representing heterogeneous event objects in RDF, building on pre-existing work and focusing on structural aspects, which have not been addressed before, such as composite event objects encapsulating other event objects. The model extends the SSN and Event-F ontologies, and is available for download in the ODP portal.

  • 46. Order onlineBuy this publication >>
    Hammar, Karl
    Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
    Towards an Ontology Design Pattern Quality Model2013Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The use of semantic technologies and Semantic Web ontologies in particular have enabled many recent developments in information integration, search engines, and reasoning over formalised knowledge. Ontology Design Patterns have been proposed to be useful in simplifying the development of Semantic Web ontologies by codifying and reusing modelling best practices.

    This thesis investigates the quality of Ontology Design Patterns. The main contribution of the thesis is a theoretically grounded and partially empirically evaluated quality model for such patterns including a set of quality characteristics, indicators, measurement methods and recommendations. The quality model is based on established theory on information system quality, conceptual model quality, and ontology evaluation. It has been tested in a case study setting and in two experiments.

    The main findings of this thesis are that the quality of Ontology Design Patterns can be identified, formalised and measured, and furthermore, that these qualities interact in such a way that ontology engineers using patterns need to make tradeoffs regarding which qualities they wish to prioritise. The developed model may aid them in making these choices.

    This work has been supported by Jönköing University.

    Download full text (pdf)
    Towards an Ontology Design Pattern Quality Model
    Download (pdf)
    omslag
  • 47.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Seil Sepour, Azam
    Jönköping University, Department of Computer and Electrical Engineering.
    Presutti, Valentina
    ISTC-CNR.
    Ontology Testing - Methodology and Tool2012Conference paper (Other academic)
    Abstract [en]

    Ontology engineering is lacking methods for verifying that ontological requirements are actually fulfilled by an ontology. There is a need for practical and detailed methodologies and tools for carrying out testing procedures and storing data about a test case and its execution. In this paper we first describe a methodology for conducting ontology testing, as well as three examples of this methodology for testing specic types of requirements. Next, we describe a tool that practically supports the methodology.We conclude that there is a need to support users in this crucial part of ontology engineering, and that our proposed methodology is a step in this direction.

  • 48.
    Presutti, Valentina
    et al.
    ISTC-CNR.
    Blomqvist, Eva
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Daga, Enrico
    ISTC-CNR.
    Gangemi, Aldo
    ISTC-CNR.
    Pattern-Based Ontology Design2012In: Ontology Engineering in a Networked World / [ed] Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez, Enrico Motta and Aldo Gangemi, Springer Berlin/Heidelberg, 2012, p. 35-64Chapter in book (Other academic)
    Abstract [en]

    In this chapter, we present ontology design patterns (ODPs), which are reusable modeling solutions that encode modeling best practices. ODPs are the main tool for performing pattern-based design of ontologies, which is an approach to ontology development that emphasizes reuse and promotes the development of a common “language” for sharing knowledge about ontology design best practices. We put specific focus on content ODPs (CPs) and show how they can be used within a particular methodology. CPs are domain-dependent patterns, the requirements of which are expressed by means of competency questions, contextual statements, and reasoning requirements. The eXtreme Design (XD) methodology is an iterative and incremental process, which is characterized by a test-driven and collaborative development approach. In this chapter, we exemplify the XD methodology for the specific case of CP reuse. The XD methodology is also supported by a set of software components named XD Tools, compatible with the NeOn Toolkit, which assist users in the process of pattern-based design.

  • 49.
    Blomqvist, Eva
    et al.
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    Gangemi, AldoISTC-CNR.Hammar, KarlJönköping University.Suárez-Figueroa, María del Carmen
    Proceedings of the 3rd Workshop on Ontology Patterns, Boston, USA, November 12, 20122012Conference proceedings (editor) (Other academic)
  • 50. Cudré-Mauroux, Philippe
    et al.
    Heflin, JeffSirin, EvrenTudorache, TaniaEuzenat, JérômeHauswirth, ManfredParreira, Josiane XavierHendler, JimSchreiber, GuusBernstein, AbrahamBlomqvist, EvaLinköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, The Institute of Technology.
    The Semantic Web - ISWC 2012 - 11th International Semantic Web Conference, Boston, MA, USA, November 11-15, 2012, Proceedings, Part I2012Conference proceedings (editor) (Other academic)
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