Results for 'data interoperability'

999 found
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  1. 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 (...)
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  2.  76
    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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  3. 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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  4. 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 (...)
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  5.  46
    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 (...)
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  6. Wanting What We Don't Want to Want: Representing Addiction in Interoperable Bio-Ontologies.Janna Hastings, Nicolas Le Novère, Werner Ceusters, Kevin Mulligan & Barry Smith - 2012 - In Ronald Cornet & Robert Stevens (eds.), Proceeedings of the Third International Conference on Biomedical Ontology. CEUR. pp. 56-60.
    Ontologies are being developed throughout the biomedical sciences to address standardization, integration, classification and reasoning needs against the background of an increasingly data-driven research paradigm. In particular, ontologies facilitate the translation of basic research into benefits for the patient by making research results more discoverable and by facilitating knowledge transfer across disciplinary boundaries. Addressing and adequately treating mental illness is one of our most pressing public health challenges. Primary research across multiple disciplines such as psychology, psychiatry, biology, neuroscience and (...)
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  7. 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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  8. 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 (...)
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  9.  66
    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 (...)
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  10.  91
    PROMES: An Ontology‐Based Messaging Service for Semantically Interoperable Information Exchange During Disaster Response.Linda Elmhadhbi, Mohamed‐Hedi Karray, Bernard Archimède, J. Neil Otte & Barry Smith - 2020 - Journal of Contingencies and Crisis Management 28 (3):324-338.
    Disaster response requires the cooperation of multiple emergency responder organizations (EROs). However, after‐action reports relating to large‐scale disasters identity communication difficulties among EROs as a major hindrance to collaboration. On the one hand, the use of two‐radio communication, based on multiple orthogonal frequencies and uneven coverage, has been shown to degrade inter‐organization communication. On the other hand, because they reflect different areas of expertise, EROs use differing terminologies, which are difficult to reconcile. These issues lead to ambiguities, misunderstandings, and inefficient (...)
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  11.  59
    Ontology of Common Sense Geographic Phenomena: Foundations for Interoperable Multilingual Geospatial Databases.David M. Mark, Barry Smith & Berit Brogaard - 2000 - In 3rd AGILE Conference on Geographic Information Science. pp. 32-34.
    Information may be defined as the conceptual or communicable part of the content of mental acts. The content of mental acts includes sensory data as well as concepts, particular as well as general information. An information system is an external (non-mental) system designed to store such content. Information systems afford indirect transmission of content between people, some of whom may put information into the system and others who are among those who use the system. In order for communication to (...)
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  12.  23
    Methodology for Semantic Enhancement of Intelligence Data.Barry Smith, Tatiana Malyuta & William Mandrick - 2013 - CUBRC Report.
    What follows is a contribution to the horizontal integration of warfighter intelligence data as defined in Chairman of the Joint Chiefs of Staff Instruction J2 CJCSI 3340.02AL: -/- Horizontally integrating warfighter intelligence data improves the consumers’ production, analysis and dissemination capabilities. HI requires access (including discovery, search, retrieval, and display) to intelligence data among the warfighters and other producers and consumers via standardized services and architectures. These consumers include, but are not limited to, the combatant commands, Services, (...)
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  13. 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 (...)
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  14. 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 (...), Shared Data, Data Analysis, and Resources—for data archiving, dissemination, analyses, and reuse. To date, more than 300 studies have been made freely available through the ImmPort Shared Data portal , which allows research data to be repurposed to accelerate the translation of new insights into discoveries. (shrink)
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  15. 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 (...)
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  16. Exploring Environmental Kuznets Curves of Kitakyushu: 50-Year Time-Series Data of the OECD SDGs Pilot City.Quan-Hoang Vuong, Ho Manh Tung, Nguyen To Hong Kong & Nguyen Minh Hoang - manuscript
    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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  17. 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, (...)
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  18.  68
    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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  19. 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 (...)
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  20. 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 (...)
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  21. 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 (...). Aim: This paper provides a survey of the biomedical imaging ontologies that have been developed thus far. It outlines the challenges, particularly faced by ontologies in the fields of histopathological imaging and image analysis, and suggests a strategy for addressing these challenges in the example domain of quantitative histopathology imaging. The ultimate goal is to support the multiscale understanding of disease that comes from using interoperable ontologies to integrate imaging data with clinical and genomics data. (shrink)
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  22. 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 (...)
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  23. 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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  24. 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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  25. 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 (...)
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  26. 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 (...)
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  27.  77
    A Unified Framework for Biomedical Terminologies and Ontologies.Werner Ceusters & Barry Smith - 2010 - Studies in Health Technology and Informatics 160:1050-1054.
    The goal of the OBO (Open Biomedical Ontologies) Foundry initiative is to create and maintain an evolving collection of non-overlapping interoperable ontologies that will offer unambiguous representations of the types of entities in biological and biomedical reality. These ontologies are designed to serve non-redundant annotation of data and scientific text. To achieve these ends, the Foundry imposes strict requirements upon the ontologies eligible for inclusion. While these requirements are not met by most existing biomedical terminologies, the latter may nonetheless (...)
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  28. 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 (...)
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  29. 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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  30. 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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  31. 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 (...)
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  32. 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 (...)
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  33. 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 (...)
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  34.  36
    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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  35. The Infectious Disease Ontology in the Age of COVID-19.Shane Babcock, Lindsay G. Cowell, John Beverley & Barry Smith - 2021 - Journal of Biomedical Semantics 12 (13).
    The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In this paper we (...)
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  36. 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 (...)
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  37.  41
    CIDO: The Community-Based Coronavirus Infectious Disease Ontology.Yongqun He, Hong Yu, Edison Ong, Yang Wang, Yingtong Liu, Anthony Huffman, Hsin-hui Huang, Beverley John, Asiyah Yu Lin, Duncan William D., Sivaram Arabandi, Jiangan Xie, Junguk Hur, Xiaolin Yang, Luonan Chen, Gilbert S. Omenn, Brian Athey & Barry Smith - 2021 - Proceedings of the 11th International Conference on Biomedical Ontologies (ICBO) and 10th Workshop on Ontologies and Data in Life Sciences (ODLS).
    Current COVID-19 pandemic and previous SARS/MERS outbreaks have caused a series of major crises to global public health. We must integrate the large and exponentially growing amount of heterogeneous coronavirus data to better understand coronaviruses and associated disease mechanisms, in the interest of developing effective and safe vaccines and drugs. Ontologies have emerged to play an important role in standard knowledge and data representation, integration, sharing, and analysis. We have initiated the development of the community-based Coronavirus Infectious Disease (...)
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  38. Protein Ontology: A Controlled Structured Network of Protein Entities.A. Natale Darren, N. Arighi Cecilia, A. Blake Judith, J. Bult Carol, R. Christie Karen, Cowart Julie, D’Eustachio Peter, D. Diehl Alexander, J. Drabkin Harold, Helfer Olivia, Barry Smith & Others - 2013 - Nucleic Acids Research 42 (1):D415-21..
    The Protein Ontology (PRO; http://proconsortium.org) formally defines protein entities and explicitly represents their major forms and interrelations. Protein entities represented in PRO corresponding to single amino acid chains are categorized by level of specificity into family, gene, sequence and modification metaclasses, and there is a separate metaclass for protein complexes. All metaclasses also have organism-specific derivatives. PRO complements established sequence databases such as UniProtKB, and interoperates with other biomedical and biological ontologies such as the Gene Ontology (GO). PRO relates to (...)
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  39.  75
    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, (...)
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  40. Big Data and Their Epistemological Challenge.Luciano Floridi - 2012 - Philosophy and Technology 25 (4):435-437.
    Between 2006 and 2011, humanity accumulated 1,600 EB of data. As a result of this growth, there is now more data produced than available storage. This article explores the problem of “Big Data,” arguing for an epistemological approach as a possible solution to this ever-increasing challenge.
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  41. Data, Privacy, and the Individual.Carissa Véliz - 2020 - Center for the Governance of Change.
    The first few years of the 21st century were characterised by a progressive loss of privacy. Two phenomena converged to give rise to the data economy: the realisation that data trails from users interacting with technology could be used to develop personalised advertising, and a concern for security that led authorities to use such personal data for the purposes of intelligence and policing. In contrast to the early days of the data economy and internet surveillance, the (...)
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  42.  61
    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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  43. Open Data, Open Review and Open Dialogue in Making Social Sciences Plausible.Quan-Hoang Vuong - 2017 - Nature: Scientific Data Updates 2017.
    Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to work (...)
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  44. Open Data, Open Review and Open Dialogue in Making Social Sciences Plausible.Quan-Hoang Vuong - 2017 - Scientific Data 4.
    A growing awareness of the lack of reproducibility has undermined society’s trust and esteem in social sciences. In some cases, well-known results have been fabricated or the underlying data have turned out to have weak technical foundations.
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  45. Updating Data Semantics.Anthony S. Gillies - 2020 - Mind 129 (513):1-41.
    This paper has three main goals. First, to motivate a puzzle about how ignorance-expressing terms like maybe and if interact: they iterate, and when they do they exhibit scopelessness. Second, to argue that there is an ambiguity in our theoretical toolbox, and that exposing that opens the door to a solution to the puzzle. And third, to explore the reach of that solution. Along the way, the paper highlights a number of pleasing properties of two elegant semantic theories, explores some (...)
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  46.  23
    Enabling Posthumous Medical Data Donation: An Appeal for the Ethical Utilisation of Personal Health Data.Jenny Krutzinna, Mariarosaria Taddeo & Luciano Floridi - 2019 - Science and Engineering Ethics 25 (5):1357-1387.
    This article argues that personal medical data should be made available for scientific research, by enabling and encouraging individuals to donate their medical records once deceased, similar to the way in which they can already donate organs or bodies. This research is part of a project on posthumous medical data donation developed by the Digital Ethics Lab at the Oxford Internet Institute at the University of Oxford. Ten arguments are provided to support the need to foster posthumous medical (...)
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  47. Big Data, Epistemology and Causality: Knowledge in and Knowledge Out in EXPOsOMICS.Stefano Canali - 2016 - Big Data and Society 3 (2).
    Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal (...)
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  48. Sense-Data and the Philosophy of Mind: Russell, James, and Mach.Gary Hatfield - 2002 - Principia 6 (2):203-230.
    The theory of knowledge in early twentieth-century Anglo American philosophy was oriented toward phenomenally described cognition. There was a healthy respect for the mind-body problem, which meant that phenomena in both the mental and physical domains were taken seriously. Bertrand Russell's developing position on sense-data and momentary particulars drew upon, and ultimately became like, the neutral monism of Ernst Mach and William James. Due to a more recent behaviorist and physicalist inspired "fear of the mental", this development has been (...)
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  49.  91
    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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  50. Using Models to Correct Data: Paleodiversity and the Fossil Record.Alisa Bokulich - forthcoming - Synthese.
    Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: First, the 'purity' of a data model is not a (...)
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