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  • 1.
    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.

  • 2.
    Gunnarsson, Cecilia
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Oncology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Diagnostics, Department of Clinical Pathology and Clinical Genetics.
    Jerevall, Piiha-Lotta
    Linköping University, Department of Clinical and Experimental Medicine, Oncology. Linköping University, Faculty of Health Sciences.
    Hammar, Karl
    Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
    Olsson, Birgit
    Linköping University, Department of Clinical and Experimental Medicine, Oncology. Linköping University, Faculty of Health Sciences.
    Nordenskjöld, Bo
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Oncology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Oncology UHL.
    Jansson, Agneta
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Oncology.
    Stål, Olle
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Oncology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Oncology UHL.
    Amplification of HSD17B1 has prognostic significance in postmenopausal breast cancer2008In: Breast Cancer Research and Treatment, ISSN 0167-6806, E-ISSN 1573-7217, Vol. 108, no 1, p. 35-41Article in journal (Refereed)
    Abstract [en]

    In situ synthesis of estrogens is believed to be of great importance for the progression of breast cancer. In postmenopausal women most estrogens are synthesized in peripheral hormone-target tissues from circulating precursor steroids, by the enzymes involved in formation of active estrogens. One of the enzymes involved in this process is 17β-hydroxysteroid dehydrogenase (17β-HSD) type 1. This enzyme catalyzes the interconversion of estrone (E1) to the biologically more potent estradiol (E2). The gene coding for 17β-HSD type 1 (HSD17B1) is located at 17q12-21. The aim of this study was to investigate altered gene copy number of HSD17B1 in breast cancer. We used real-time PCR and examined 387 postmenopausal breast tumors for amplification of HSD17B1, and if an increased mRNA level of this enzyme is associated with amplification of the gene. We also investigated whether amplification of HSD17B1 has a prognostic value. There was a significant correlation between gene copy number of HSD17B1 and mRNA expression level (P = 0.00002). ER-positive patients with amplification of HSD17B1 showed lower breast cancer survival than patients without amplification (P = 0.025). Among ER-negative patients there was no significant correlation between increased gene copy number of HSD17B1 and prognosis. Furthermore, we found that amplification of the gene had prognostic significance in multivariate analysis adjusting for other clinicopathological variables. © 2007 Springer Science+Business Media, LLC.

  • 3.
    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.

  • 4.
    Hammar, Karl
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Content Ontology Design Patterns: Qualities, Methods, and Tools - Supplementary Materials2017Data set
    Abstract [en]

    Data and code supporting Karl Hammar's 2017 PhD dissertation.

  • 5.
    Hammar, Karl
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. Information Engineering Group, Jönköping University, Sweden.
    Ontology Design Pattern Property Specialisation Strategies2014In: KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT, EKAW 2014, SPRINGER-VERLAG BERLIN , 2014, Vol. 8876, p. 165-180Conference paper (Refereed)
    Abstract [en]

    Ontology Design Patterns (ODPs) show potential in enabling simpler, faster, and more correct Ontology Engineering by laymen and experts. For ODP adoption to take off, improved tool support for ODP use in Ontology Engineering is required. This paper studies and evaluates the effects of strategies for object property specialisation in ODPs, and suggests tool improvements based on those strategies. Results indicate the existence of three previously unstudied strategies for ODP specialisation, the uses of which affect reasoning performance and integration complexity of resulting ontologies.

  • 6.
    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.

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