Results for 'interoperability'

48 found
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  1. Joint Doctrine Ontology: A Benchmark for Military Information Systems Interoperability.Peter Morosoff, Ron Rudnicki, Jason Bryant, Robert Farrell & Barry Smith - 2015 - In Semantic Technology for Intelligence, Defense and Security (STIDS). CEUR vol. 1325. pp. 2-9.
    When the U.S. conducts warfare, elements of a force are drawn from different services and work together as a single team to accomplish an assigned mission. To achieve such unified action, it is necessary that the doctrines governing the actions of members of specific services be both consistent with and subservient to joint Doctrine. Because warfighting today increasingly involves not only live forces but also automated systems, unified action requires that information technology that is used in joint warfare must be (...)
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  2. The HL7 Approach to Semantic Interoperability.Jobst Landgrebe & Barry Smith - 2011 - In Proceedings of the 2nd International Conference on Biomedical Ontology. CEUR, vol. 833. pp. 139-146.
    Health Level 7 (HL7) is an international standards development organisation in the domain of healthcare information technology. Initially the mission of HL7 was to enable data exchange via the creation of syntactic standards which supported point-to-point messaging. Currently HL7 sees its mission as one of creating standards for semantic interoperability in healthcare IT on the basis of its flagship “version 3” (v3). Unfortunately, v3 has been plagued by quality and consistency issues, and it has not been able to keep (...)
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  3.  71
    ARGOS Policy Brief on Semantic Interoperability.Dipak Kalra, Mark Musen, Barry Smith & Werner Ceusters - 2011 - Studies in Health Technology and Informatics 170 (1):1-15.
    Semantic interoperability requires the use of standards, not only for Electronic Health Record (EHR) data to be transferred and structurally mapped into a receiving repository, but also for the clinical content of the EHR to be interpreted in conformity with the original meanings intended by its authors. Accurate and complete clinical documentation, faithful to the patient’s situation, and interoperability between systems, require widespread and dependable access to published and maintained collections of coherent and quality-assured semantic resources, including models (...)
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  4.  59
    Semantic Interoperability in Healthcare. State of the Art in the US. A Position Paper with Background Materials.Werner Ceusters & Barry Smith - 2010 - In European Union ARGOS Project: Transatlantic Observatory for Meeting Global Health Policy Challenges through ICT-Enabled Solution.
    Semantic interoperability can be defined as the ability of two or more computer systems to exchange information in such a way that the meaning of that information can be automatically interpreted by the receiving system accurately enough to produce useful results to the end users of both systems. Several activities are currently being performed by a variety of stakeholders to achieve semantic interoperability in healthcare. Many of these activities are not beneficial, because they place too great a focus (...)
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  5.  50
    Biomedical Terminologies and Ontologies: Enabling Biomedical Semantic Interoperability and Standards in Europe.Bernard de Bono, Mathias Brochhausen, Sybo Dijkstra, Dipak Kalra, Stephan Keifer & Barry Smith - 2009 - In European Large-Scale Action on Electronic Health.
    In the management of biomedical data, vocabularies such as ontologies and terminologies (O/Ts) are used for (i) domain knowledge representation and (ii) interoperability. The knowledge representation role supports the automated reasoning on, and analysis of, data annotated with O/Ts. At an interoperability level, the use of a communal vocabulary standard for a particular domain is essential for large data repositories and information management systems to communicate consistently with one other. Consequently, the interoperability benefit of selecting a particular (...)
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  6.  50
    Towards Interoperability of Biomedical Ontologies.Musen Mark, A. Schroeder, Michael Smith & Barry - 2008 - Schloss Dagstuhl: Leibniz-Zentrum für Informatik.
    Report on Dagstuhl Seminar 07132, Schloss Dagstuhl, March 27-30 , 2007.
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  7. Interoperability of Disparate Engineering Domain Ontologies Using Basic Formal Ontology.Thomas J. Hagedorn, Barry Smith, Sundar Krishnamurty & Ian R. Grosse - 2019 - Journal of Engineering Design 31.
    As engineering applications require management of ever larger volumes of data, ontologies offer the potential to capture, manage, and augment data with the capability for automated reasoning and semantic querying. Unfortunately, considerable barriers hinder wider deployment of ontologies in engineering. Key among these is lack of a shared top-level ontology to unify and organise disparate aspects of the field and coordinate co-development of orthogonal ontologies. As a result, many engineering ontologies are limited to their scope, and functionally difficult to extend (...)
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  8.  79
    Using Philosophy to Improve the Coherence and Interoperability of Applications Ontologies: A Field Report on the Collaboration of IFOMIS and L&C.Jonathan Simon, James Matthew Fielding & Barry Smith - 2004 - In Proceedings of the First Workshop on Philosophy and Informatics. Deutsches Forschungs­zentrum für künstliche Intelligenz, Cologne: 2004 (CEUR Workshop Proceedings 112). pp. 65-72.
    The collaboration of Language and Computing nv (L&C) and the Institute for Formal Ontology and Medical Information Science (IFOMIS) is guided by the hypothesis that quality constraints on ontologies for software ap-plication purposes closely parallel the constraints salient to the design of sound philosophical theories. The extent of this parallel has been poorly appreciated in the informatics community, and it turns out that importing the benefits of phi-losophical insight and methodology into application domains yields a variety of improvements. L&C’s LinKBase® (...)
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  9.  38
    Towards Interoperability of Biomedical Ontologies - Report Number 07132.Mark Musen, Michael Schroeder & Barry Smith - 2008 - In Towards Interoperability of Biomedical Ontologies. Schloss Dagstuhl-Leibniz-Zentrum Fuer Informatik.
    The meeting focused on uses of ontologies, with a special focus on spatial ontologies, in addressing the ever increasing needs faced by biology and medicine to cope with ever expanding quantities of data. To provide effective solutions computers need to integrate data deriving from myriad heterogeneous sources by bringing the data together within a single framework. The meeting brought together leaders in the field of what are called "top-level ontologies" to address this issue, and to establish strategies among leaders in (...)
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  10. The Evaluation of Ontologies: Toward Improved Semantic Interoperability.Leo Obrst, Werner Ceusters, Inderjeet Mani, Steve Ray & Barry Smith - 2006 - In Chris Baker & Kei H. Cheung (eds.), Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences. Springer. pp. 139-158.
    Recent years have seen rapid progress in the development of ontologies as semantic models intended to capture and represent aspects of the real world. There is, however, great variation in the quality of ontologies. If ontologies are to become progressively better in the future, more rigorously developed, and more appropriately compared, then a systematic discipline of ontology evaluation must be created to ensure quality of content and methodology. Systematic methods for ontology evaluation will take into account representation of individual ontologies, (...)
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  11. An Ontological Approach to Representing the Product Life Cycle.J. Neil Otte, Dimitris Kiritsi, Munira Mohd Ali, Ruoyu Yang, Binbin Zhang, Ron Rudnicki, Rahul Rai & Barry Smith - 2019 - Applied Ontology 14 (2):1-19.
    The ability to access and share data is key to optimizing and streamlining any industrial production process. Unfortunately, the manufacturing industry is stymied by a lack of interoperability among the systems by which data are produced and managed, and this is true both within and across organizations. In this paper, we describe our work to address this problem through the creation of a suite of modular ontologies representing the product life cycle and its successive phases, from design to end (...)
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  12. Biomedical Imaging Ontologies: A Survey and Proposal for Future Work.Barry Smith, Sivaram Arabandi, Mathias Brochhausen, Michael Calhoun, Paolo Ciccarese, Scott Doyle, Bernard Gibaud, Ilya Goldberg, Charles E. Kahn Jr, James Overton, John Tomaszewski & Metin Gurcan - 2015 - Journal of Pathology Informatics 6 (37):37.
    Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical defi nitions thereby also supporting reasoning over the tagged data. Aim: (...)
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  13. Putting Biomedical Ontologies to Work.Barry Smith & Mathias Brochhausen - 2010 - Methods of Information in Medicine 49 (2):135-40.
    Biomedical ontologies exist to serve integration of clinical and experimental data, and it is critical to their success that they be put to widespread use in the annotation of data. How, then, can ontologies achieve the sort of user-friendliness, reliability, cost-effectiveness, and breadth of coverage that is necessary to ensure extensive usage? Methods: Our focus here is on two different sets of answers to these questions that have been proposed, on the one hand in medicine, by the SNOMED CT community, (...)
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  14. Infectious Disease Ontology.Lindsay Grey Cowell & Barry Smith - 2009 - In Infectious Disease Informatics. New York: Springer New York. pp. 373-395.
    Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and (...)
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  15. ImmPort, Toward Repurposing of Open Access Immunological Assay Data for Translational and Clinical Research.Sanchita Bhattacharya, Patrick Dunn, Cristel Thomas, Barry Smith, Henry Schaefer, Jieming Chen, Zicheng Hu, Kelly Zalocusky, Ravi Shankar & Shai Shen-Orr - 2018 - Scientific Data 5:180015.
    Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four components–Private Data, Shared Data, Data (...)
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  16. The Role of Ontologies for Sustainable, Semantically Interoperable and Trustworthy EHR Solutions.Bernd Blobel, Dipak Kalra, Marc Koehn, Ken Lunn, Peter Pharow, Pekka Ruotsalainen, Stefan Schulz & Barry Smith - 2009 - Studies in Health Technology and Informatics 150:953-957.
    As health systems around the world turn towards highly distributed, specialized and cooperative structures to increase quality and safety of care as well as efficiency and efficacy of delivery processes, there is a growing need for supporting communication and collaboration of all parties involved with advanced ICT solutions. The Electronic Health Record (EHR) provides the information platform which is maturing towards the eHealth core application. To meet the requirements for sustainable, semantically interoperable, and trustworthy EHR solutions, different standards and different (...)
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  17.  50
    Ontology as the Core Discipline of Biomedical Informatics: Legacies of the Past and Recommendations for the Future Direction of Research.Barry Smith & Werner Ceusters - 2007 - In Gordana Dodig Crnkovic & Susan Stuart (eds.), Computation, Information, Cognition: The Nexus and the Liminal. Cambridge Scholars Publishing. pp. 104-122.
    The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In the (...)
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  18.  85
    Universal Core Semantic Layer.Barry Smith, Lowell Vizenor & James Schoening - 2009 - In Ontology for the Intelligence Community: Proceedings of the Third OIC Conference. CEUR, vol. 555. pp. 1-5.
    The Universal Core (UCore) is a central element of the National Information Sharing Strategy that is supported by multiple U.S. Federal Government Departments, by the intelligence community, and by a number of other national and international institutions. The goal of the UCore initiative is to foster information sharing by means of an XML schema providing consensus representations for four groups of universally understood terms under the headings who, what, when, and where. We here describe a project to create an ontology-based (...)
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  19.  70
    Coordinating Coronavirus Research: The COVID-19 Infectious Disease Ontology.John Beverley, Shane Babcock, Gustavo Carvalho, Lindsay Cowell, Sebastian Duesing, Regina Hurley & Barry Smith - 2020 - Open Science Foundation Preprints.
    Rapidly, accurately and easily interpreting generated data is of fundamental concern. Ontologies – structured controlled vocabularies – support interoperability and prevent the development of data silos which undermine interoperability. The Open Biological and Biomedical Ontologies (OBO) Foundry serves to ensure ontologies remain interoperable through adherence by its members to core ontology design principles. For example, the Infectious Disease Ontology (IDO) Core includes terminological content common to investigations of all infectious diseases. Ontologies covering more specific infectious diseases in turn (...)
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  20. A Product Life Cycle Ontology for Additive Manufacturing.Munira Mohd Ali, Rahul Rai, J. Neil Otte & Barry Smith - 2019 - Computers in Industry 105:191-203.
    The manufacturing industry is evolving rapidly, becoming more complex, more interconnected, and more geographically distributed. Competitive pressure and diversity of consumer demand are driving manufacturing companies to rely more and more on improved knowledge management practices. As a result, multiple software systems are being created to support the integration of data across the product life cycle. Unfortunately, these systems manifest a low degree of interoperability, and this creates problems, for instance when different enterprises or different branches of an enterprise (...)
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  21.  76
    Relations in Biomedical Ontologies.Barry Smith, Werner Ceusters, Bert Klagges, Jacob Köhler, Anand Kuma, Jane Lomax, Chris Mungall, , Fabian Neuhaus, Alan Rector & Cornelius Rosse - 2005 - Genome Biology 6 (5):R46.
    To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.
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  22. The Ontology for Biomedical Investigations.Anita Bandrowski, Ryan Brinkman, Mathias Brochhausen, Matthew H. Brush, Bill Bug, Marcus C. Chibucos, Kevin Clancy, Mélanie Courtot, Dirk Derom, Michel Dumontier, Liju Fan, Jennifer Fostel, Gilberto Fragoso, Frank Gibson, Alejandra Gonzalez-Beltran, Melissa A. Haendel, Yongqun He, Mervi Heiskanen, Tina Hernandez-Boussard, Mark Jensen, Yu Lin, Allyson L. Lister, Phillip Lord, James Malone, Elisabetta Manduchi, Monnie McGee, Norman Morrison, James A. Overton, Helen Parkinson, Bjoern Peters, Philippe Rocca-Serra, Alan Ruttenberg, Susanna-Assunta Sansone, Richard H. Scheuermann, Daniel Schober, Barry Smith, Larisa N. Soldatova, Christian J. Stoeckert, Chris F. Taylor, Carlo Torniai, Jessica A. Turner, Randi Vita, Patricia L. Whetzel & Jie Zheng - 2016 - PLoS ONE 11 (4):e0154556.
    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to (...)
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  23. Towards an Ontological Modelling of Preference Relations.Daniele Porello & Giancarlo Guizzardi - 2018 - In C. Ghidini, B. Magnini, A. Passerini & P. Traverso (eds.), AI*IA 2018 - Advances in Artificial Intelligence - XVIIth International Conference of the Italian Association for Artificial Intelligence, Trento, Italy, November 20-23, 2018, Proceedings. pp. 152--165.
    Preference relations are intensively studied in Economics, but they are also approached in AI, Knowledge Representation, and Conceptual Modelling, as they provide a key concept in a variety of domains of application. In this paper, we propose an ontological foundation of preference relations to formalise their essential aspects across domains. Firstly, we shall discuss what is the ontological status of the relata of a preference relation. Secondly, we investigate the place of preference relations within a rich taxonomy of relations (e.g. (...)
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  24. Wüsteria.Barry Smith, Werner Ceusters & Rita Temmerman - 2005 - Studies in Health Technology and Informatics 116:647-652.
    The last two decades have seen considerable efforts directed towards making Electronic Health Records interoperable through improvements in medical ontologies, terminologies and coding systems. Unfortunately, these efforts have been hampered by a number of influential ideas inherited from the work of Eugen Wüster, the father of terminology standardization and the founder of ISO TC 37. We here survey Wüster’s ideas – which see terminology work as being focused on the classification of concepts in people’s minds – and we argue that (...)
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  25. HL7 RIM: An Incoherent Standard.Barry Smith & Werner Ceusters - 2006 - Studies in Health Technology and Informatics 124 (Proceedings of MIE 2006):133–138.
    The Health Level 7 Reference Information Model (HL7 RIM) is lauded by its authors as ‘the foundation of healthcare interoperability’. Yet even after some 10 years of development work, the RIM is still subject to a variety of logical and ontological flaws which have placed severe obstacles in the way of those who are called upon to develop implementations. We offer evidence that these obstacles are insurmountable and that the time has come to abandon an unworkable paradigm.
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  26.  75
    The Trilemma of Sustainable Industrial Growth: Evidence From a Piloting OECD’s Green City.Quan-Hoang Vuong, Ho Manh Tung, Nguyen To Hong Kong & Nguyen Minh Hoang - 2019 - Palgrave Communications 5:156.
    Can green growth policies help protect the environment while keeping the industry growing and infrastructure expanding? The City of Kitakyushu, Japan has actively implemented eco-friendly policies since 1967 and recently inspired the pursuit of sustainable development around the world, especially in the Global South region. However, empirical studies on the effects of green growth policies are still lacking. This study explores the relationship between road infrastructure development and average industrial firm size with air pollution in the city through the Environmental (...)
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  27. The Ontology of Command and Control.Barry Smith, Mietinnin Kristo & Mandrick William - 2009 - In Proceedings of the 14th International Command and Control Research and Technology Symposium (ICCRTS).
    The goal of the Department of Defense Net-Centric Data Strategy is to improve data sharing throughout the DoD. Data sharing is a critical element of interoperability in the emerging system-of-systems. Achieving interoperability requires the elimination of two types of data heterogeneity: differences of syntax and differences of semantics. This paper builds a path toward semantic uniformity through application of a disciplined approach to ontology. An ontology is a consensus framework representing the types of entities within a given domain (...)
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  28. Towards a Conceptualization of Sociomaterial Entanglement.Daniele Porello & Roberta Ferrario - 2015 - In Henning Christiansen, Isidora Stojanovic & George A. Papadopoulos (eds.), Modeling and Using Context. 9th International and Interdisciplinary Conference, Context 2015. Springer. pp. 32--46.
    In knowledge representation, socio-technical systems can be modeled as multiagent systems in which the local knowledge of each individual agent can be seen as a context. In this paper we propose formal ontologies as a means to describe the assumptions driving the construction of contexts as local theories and to enable interoperability among them. In particular, we present two alternative conceptualizations of the notion of sociomateriality (and entanglement), which is central in the recent debates on socio-technical systems in the (...)
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  29.  85
    An Improved Ontological Representation of Dendritic Cells as a Paradigm for All Cell Types.Masci Anna Maria, N. Arighi Cecilia, D. Diehl Alexander, E. Lieberman Anne, Mungall Chris, H. Scheuermann Richard, Barry Smith & G. Cowell Lindsay - 2009 - BMC Bioinformatics 10 (1):70.
    The Cell Ontology (CL) is designed to provide a standardized representation of cell types for data annotation. Currently, the CL employs multiple is_a relations, defining cell types in terms of histological, functional, and lineage properties, and the majority of definitions are written with sufficient generality to hold across multiple species. This approach limits the CL’s utility for cross-species data integration. To address this problem, we developed a method for the ontological representation of cells and applied this method to develop a (...)
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  30. An Improved Ontological Representation of Dendritic Cells as a Paradigm for All Cell Types.Anna Maria Masci, Cecilia N. Arighi, Alexander D. Diehl, Anne E. Liebermann, Chris Mungall, Richard H. Scheuermann, Barry Smith & Lindsay Cowell - 2009 - BMC Bioinformatics 10 (1):70.
    Recent increases in the volume and diversity of life science data and information and an increasing emphasis on data sharing and interoperability have resulted in the creation of a large number of biological ontologies, including the Cell Ontology (CL), designed to provide a standardized representation of cell types for data annotation. Ontologies have been shown to have significant benefits for computational analyses of large data sets and for automated reasoning applications, leading to organized attempts to improve the structure and (...)
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  31.  84
    Tracking Referents in Electronic Health Records.Werner Ceusters & Barry Smith - 2005 - Studies in Health Technology and Informatics 116:71–76.
    Electronic Health Records (EHRs) are organized around two kinds of statements: those reporting observations made, and those reporting acts performed. In neither case does the record involve any direct reference to what such statements are actually about. They record not: what is happening on the side of the patient, but rather: what is said about what is happening. While the need for a unique patient identifier is generally recognized, we argue that we should now move to an EHR regime in (...)
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  32. A Conceptual Investigation of the Ontological Commensurability of Spatial Data Infrastructures Among Different Cultures.D. J. Saab - 2009 - Earth Science Informatics 2 (4):283-297.
    Humans think and communicate in very flexible and schematic ways, and a Spatial Data Infrastructure (SDI) for the Amazon and associated information system ontologies should reflect this flexibility and the adaptive nature of human cognition in order to achieve semantic interoperability. In this paper I offer a conceptual investigation of SDI and explore the nature of cultural schemas as expressions of indigenous ontologies and the challenges of semantic interoperability across cultures. Cultural schemas are, in essence, our ontologies, but (...)
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  33. Adapting Clinical Ontologies in Real-World Environments.Holger Stenzhorn, Stefan Schulz, Martin Boeker & Barry Smith - 2008 - Journal of Universal Computer Science 14 (22):3767-3780.
    The desideratum of semantic interoperability has been intensively discussed in medical informatics circles in recent years. Originally, experts assumed that this issue could be sufficiently addressed by insisting simply on the application of shared clinical terminologies or clinical information models. However, the use of the term ‘ontology’ has been steadily increasing more recently. We discuss criteria for distinguishing clinical ontologies from clinical terminologies and information models. Then, we briefly present the role clinical ontologies play in two multicentric research projects. (...)
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  34. Clinical Ontologies Interfacing the Real World.Stefan Schulz, Holger Stenzhorn, Martin Boeker, Rüdiger Klar & Barry Smith - 2007 - In Third International Conference on Semantic Technologies (i-semantics 2007), Graz, Austria. Graz: pp. 356-363..
    The desideratum of semantic interoperability has been intensively discussed in medical informatics circles in recent years. Originally, experts assumed that this issue could be sufficiently addressed by insisting simply on the application of shared clinical terminologies or clinical information models. However, the use of the term ‘ontology’ has been steadily increasing more recently. We discuss criteria for distinguishing clinical ontologies from clinical terminologies and information models. Then, we briefly present the role clinical ontologies play in two multicentric research projects. (...)
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  35. Strengths and Limitations of Formal Ontologies in the Biomedical Domain.Barry Smith - 2009 - Electronic Journal of Communication, Information and Innovation in Health 3 (1):31-45.
    We propose a typology of representational artifacts for health care and life sciences domains and associate this typology with different kinds of formal ontology and logic, drawing conclusions as to the strengths and limitations for ontology in a description logics framework. The four types of domain representation we consider are: (i) lexico-semantic representation, (ii) representation of types of entities, (iii) representations of background knowledge, and (iv) representation of individuals. We advocate a clear distinction of the four kinds of representation in (...)
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  36. OntONeo: The Obstetric and Neonatal Ontology.Fernanda Farinelli, Mauricio Almeida, Peter Elkin & Barry Smith - 2016 - In Dealing with elements of medical encounters: An approach based on ontological realism. Aachen: CEUR, vol. 1747.
    This paper presents the Obstetric and Neonatal Ontology (OntONeo). This ontology has been created to provide a consensus representation of salient electronic health record (EHR) data and to serve interoperability of the associated data and information systems. More generally, it will serve interoperability of clinical and translational data, for example deriving from genomics disciplines and from clinical trials. Interoperability of EHR data is important to ensuring continuity of care during the prenatal and postnatal periods for both mother (...)
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  37. Developing the Quantitative Histopathology Image Ontology : A Case Study Using the Hot Spot Detection Problem.Metin Gurcan, Tomaszewski N., Overton John, A. James, Scott Doyle, Alan Ruttenberg & Barry Smith - 2017 - Journal of Biomedical Informatics 66:129-135.
    Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to breast cancer hot-spot detection (...)
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  38. CARO: The Common Anatomy Reference Ontology.Melissa Haendel, Fabian Neuhaus, David Osumi-Sutherland, Paula M. Mabee, José L. V. Mejino Jr, Chris J. Mungall & Barry Smith - 2008 - In Anatomy Ontologies for Bioinformatics: Principles and Practice. Springer. pp. 327-349.
    The Common Anatomy Reference Ontology (CARO) is being developed to facilitate interoperability between existing anatomy ontologies for different species, and will provide a template for building new anatomy ontologies. CARO has a structural axis of classification based on the top-level nodes of the Foundational Model of Anatomy. CARO will complement the developmental process sub-ontology of the GO Biological Process ontology, using it to ensure the coherent treatment of developmental stages, and to provide a common framework for the model organism (...)
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  39. Ontology, Natural Language, and Information Systems: Implications of Cross-Linguistic Studies of Geographic Terms.David M. Mark, Werner Kuhn, Barry Smith & A. G. Turk - 2003 - In 6th Annual Conference of the Association of Geographic Information Laboratories for Europe (AGILE). pp. 45-50.
    Ontology has been proposed as a solution to the 'Tower of Babel' problem that threatens the semantic interoperability of information systems constructed independently for the same domain. In information systems research and applications, ontologies are often implemented by formalizing the meanings of words from natural languages. However, words in different natural languages sometimes subdivide the same domain of reality in terms of different conceptual categories. If the words and their associated concepts in two natural languages, or even in two (...)
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  40. Ontological Complexity and Human Culture.D. J. Saab & F. Fonseca - forthcoming - In R. Hagengruber (ed.), Proceedings of Philosophy's Relevance in Information Science.
    Ontologies are being used by information scientists in order to facilitate the sharing of meaningful information. However, computational ontologies are problematic in that they often decontextualize information. The semantic content of information is dependent upon the context in which it exists and the experience through which it emerges. For true semantic interoperability to occur among diverse information systems, within or across domains, information must remain contextualized. In order to bring more context to computational ontologies, we introduce culture as an (...)
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  41. The 2006 Upper Ontology Summit Joint Communiqué.Leo Obrst, Patrick Cassidy, Steve Ray, Barry Smith, Dagobert Soergel, Matthew West & Peter Yim - 2006 - Applied Ontology 1 (2):203-211.
    On March 14-15, 2006, at the US National Institute of Standards and Technology (NIST) in Gaithersburg, MD there took place the first Upper Ontology Summit (UOS). This was a convening of custodians of several prominent upper ontologies, key technology participants, and interested other parties, with the purpose of finding a means to relate the different ontologies to each other. The result is reflected in a joint communiqué, directed to the larger ontology community and the general public, and expressing a joint (...)
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  42. Basic Semantic Integration.Christopher Menzel - 2004 - Semantic Interoperability and Integration, Proceedings of Dagstuhl Seminar 04391.
    The use of highly abstract mathematical frameworks is essential for building the sort of theoretical foundation for semantic integration needed to bring it to the level of a genuine engineering discipline. At the same time, much of the work that has been done by means of these frameworks assumes a certain amount of background knowledge in mathematics that a lot of people working in ontology, even at a fairly high theoretical level, lack. The major purpose of this short paper is (...)
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  43. Culture as Mediator for What is Ready-to-Hand: A Phenomenological Exploration of Semantic Networks.D. J. Saab - manuscript
    Upon what philosophical foundation are semantic network graphs based? Does this foundation allow for the legitimization of other semantic networks and ontological diversity? How can we design our computational and informational systems to accommodate this ontological diversity and the variety of semantic networks? Are semantic networks segmentations of larger semantic landscapes? This paper explores semantic networks from a Heideggerian existentialist and phenomenological perspective. The analysis presented uses cultural schema theory to bridge the syntactic and lexical elements to the semantic and (...)
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  44.  65
    Engineering Ontologies: Foundations and Theories From Philosophy and Logical Theory.Nicola Guarino & Barry Smith - 2006 - In SemanticMining: Semantic Interoperability and Data Mining in Biomedicine (NoE 507505). 1 Deliverable D.21.2. pp. 1-13.
    Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. ‘Ontology’ is often used by philosophers as a synonym for ‘metaphysics’ (literally: ‘what comes after the Physics’), a term which was used by early students of Aristotle to refer to what Aristotle himself called ‘first philosophy’. The term ‘ontology’ (or ontologia) was itself coined in 1613, independently, by two philosophers, Rudolf Göckel (...)
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  45.  63
    Dealing with Elements of Medical Encounters: An Approach Based on Ontological Realism.Farinelli Fernanda, Almeida Mauricio, Elkin Peter & Barry Smith - 2016 - Proceedings of the Joint International Conference on Biological Ontology and Biocreative 1747.
    Electronic health records (EHRs) serve as repositories of documented data collected in a health care encounter. An EHR records information about who receives, who provides the health care and about the place where the encounter happens. We also observe additional elements relating to social relations in which the healthcare consumer is involved. To provide a consensus representation of common data and to enhance interoperability between different EHR repositories we have created a solution grounded in formal ontology. Here, we present (...)
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  46.  32
    An Ontology-Based Methodology for the Migration of Biomedical Terminologies to Electronic Health Records.Barry Smith & Werner Ceusters - 2005 - In Proceedings of AMIA Symposium 2005, Washington DC,. Washington, DC: AMIA. pp. 704-708.
    Biomedical terminologies are focused on what is general, Electronic Health Records (EHRs) on what is particular, and it is commonly assumed that the step from the one to the other is unproblematic. We argue that this is not so, and that, if the EHR of the future is to fulfill its promise, then the foundations of both EHR architectures and biomedical terminologies need to be reconceived. We accordingly describe a new framework for the treatment of both generals and particulars in (...)
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  47. An Ontological Architecture for Orbital Debris Data.Robert J. Rovetto - 2015 - Earth Science Informatics 9 (1):67-82.
    The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris and broader SSA domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to (I) represent general orbital debris and SSA domain (...)
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  48. The Orbital Space Environment and Space Situational Awareness Domain Ontology – Towards an International Information System for Space Data.Robert J. Rovetto - 2016 Sept - In Proceedings of The Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference.
    The orbital space environment is home to natural and artificial satellites, debris, and space weather phenomena. As the population of orbital objects grows so do the potential hazards to astronauts, space infrastructure and spaceflight capability. Orbital debris, in particular, is a universal concern. This and other hazards can be minimized by improving global space situational awareness (SSA). By sharing more data and increasing observational coverage of the space environment we stand to achieve that goal, thereby making spaceflight safer and expanding (...)
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