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    Linked Data in Healthcare and Life Sciences Linked Data in Healthcare and Life Sciences Presentation Transcript

    • Linked Data in Healthcare and Life Sciences James G. Boram Kim foaf:mbox jgkim@jayg.org foaf:homepage http://jayg.org/ owl:sameAs http://jayg.me/ dcterms:modified 2013-03-05+09:00
    • SEMANTIC WEB HEALTH CARE AND LIFE SCIENCES (HCLS) INTEREST GROUPHOMEIntroductionThe mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, andsupport the use of Semantic Web technologies across health care, life sciences, clinical research and translational medicine.These domains stand to gain tremendous benefit from intra- and inter-domain application of Semantic Web technologies asthey depend on the interoperability of information from many disciplines. Please see the accompanying Use Cases and LINKSRationale document. Interest Group links: Group CharterThe group will: Public Wiki page Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. Instructions on joining the IG Implement proof-of-concept demonstrations and industry-ready code. Participants: Document guidelines to accelerate the adoption of the technology. organizations Disseminate information about the groups work at government, industry, academic events and by participating in persons (member only link) community initiatives. Mailing list archivesParticipationCommunications of the HCLS IG are public. This includes public meeting records and access to the archives of the public-semweb-lifesci@w3.org mailing list. DOCUMENTS Emerging practices for mapping andThe HCLS IG welcomes active participation from representatives of W3C Member organizations. If you are part of a W3C linking life sciences data using RDF —Member organization, please verify or create your W3C web account, then ask your Advisory Committe representative A case series(member-only) to join the HCLS IG and nominate you to participate. More detailed instructions are available. Ontology of Rhetorical Blocks (ORB)
    • SEMANTIC WEB HEALTH CARE AND LIFE SCIENCES (HCLS) INTEREST GROUP 2005-2007 2008-2011 2011-2014HOME This charter is now expired; please see the next HCLS IG charter. Scope Motivations Scope Deliverables Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) Charter Motivations Dependencies Deliverables Dependencies Semantic Web Health Care and Life Sciences Interest Group Participation Communication Contents Semantic Web Health Care and Life Sciences Interest Group Participation Communication Charter Decision Policy Patent Disclosures 1. Mission Statement Charter Decision Policy The mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, and support About this Charter 2. Scope Patent Disclosures the use of Semantic Web technologies across health care, life sciences, clinical research and translational medicine. These domains The mission of the Semantic Web Health Care and Life Sciences Interest Group, part of the Semantic Web Activity, is to develop, About this Charter stand to gain tremendous benefit from intra- and inter-domain application of Semantic Web technologies as they depend on the 3. Duration interoperability of information from many disciplines. Please see the accompanying Use Cases and Rationale document. advocate for, and support the use of Semantic Web technologies for health care and life science, with focus on biological science andIntroduction 4. Deliverables translational medicine. These domains stand to gain tremendous benefit by adoption of Semantic Web technologies, as they depend on the interoperability of information from many domains and processes for efficient decision support. The group will: 5. Relationship with Other Activities The group will: Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. 6. Interest Group Participation Implement proof-of-concept demonstrations and industry-ready code. Document use cases to aid individuals in understanding the business and technical benefits of using Semantic Web technologies. Document guidelines to accelerate the adoption of the technology. 7. Meetings Disseminate information about the groups work at government, industry, academic events and by participating in community initiatives. Document guidelines to accelerate the adoption of the technology.The mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, and 8. Group Communications Implement a selection of the use cases as proof-of-concept demonstrations. Explore the possibility of developing high level vocabularies. Join the Semantic Web Health Care and Life Sciences Interest Group. 9. Patent Disclosures Disseminate information about the groups work at government, industry, and academic events. End date 31 Aug 2014 Join the Semantic Web Health Care and Life Sciences Interest Group.support the use of Semantic Web technologies across health care, life sciences, clinical research and translational medicine. Mission Statement Confidentiality Proceedings are Public End date 31 May 2011 Michel Dumontier (Carleton University) - life sciences The Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) is chartered to develop and support the use of Semantic Web Charles Mead (NCI CBIIT) - health care technologies to improve collaboration, research and development, and innovation adoption in the of Health Care and Life Science domains. Success in Confidentiality Proceedings are Public Chairs Vijay Bulusu (Pfizer) - pharmaceuticalsThese domains stand to gain tremendous benefit from intra- and inter-domain application of Semantic Web technologies as these domains depends on a foundation of semantically rich system, process and information interoperability. To these ends, the HCLSIG will focus on Chair assignments will be reviewed every 18 months. Initial Chairs Susie Stephens, Chimezi Ogbuji, M. Scott Marshall the development of use cases that illustrate the business value of Semantic Web technology adoption, core vocabularies, guidelines and best practices regarding unique identifiers, and provide a forum for supporting communication, education, collaboration and implementation. The HCLSIG will also Initial Team Contacts Initial Team Contacts LINKS Eric Prudhommeaux Eric Prudhommeaux work with the other Semantic Web related groups to gather suggestions for further HCLSIG development work. Further, the HCLSIG will provide a (FTE %: 60) (FTE %: 50)they depend on the interoperability of information from many disciplines. Please see the accompanying Use Cases and forum to support and encourage the use of Semantic Web technologies and foster the growth of interoperable, policy-aware data and databases in the Teleconferences: Weekly Teleconferences: Weekly Usual Meeting Schedule Life Sciences and Health Care industries. Usual Meeting Schedule Face-to-face: at most once per year Face-to-face: at least one per year This work falls within the Technology and Society Domain and is part of W3Cs Semantic Web Activity. 1. ScopeRationale document. 1. Scope Scope The HCLS IG will continue to provide a forum for supporting, developing and applying Semantic Web technologies across healthcare, life sciences, clinical Interest Group links: The HCLSIG will provide a forum for supporting, guiding and collecting application and implementation experience. It will develop and support Semantic Web The HCLSIG is focused on the use of Semantic Web technologies to better enable interoperability and improve collaboration, research and development, research and the continuum of translational medicine. Within these contexts, the HCLS IG will focus on the use of Semantic Web technologies to realize technologies in the three focus areas: life science, translational medicine, and health care. Within these areas, it will address use cases that have clear innovation adoption, and data reusability in the health Care and life science domains. Sample areas of work designed to facilitate this goal include: specific use cases which themselves have a specific clinical, research of business values. As use cases are developed, HCLS IG will solicit advice on technical scientific, business, and/or technical value. HCLSIG will solicit advice on technical matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will extensively liason with external organizations that are central to the areas to which matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will also focus Core vocabularies: In order to stimulate cross-community data integration, collaborative efforts are required to define core vocabularies that can on developing ongoing and mutually productive liaisons with relevant external organizations in healthcare, life sciences, and clinical research, including we wish to contribute. In some cases, work started in HCLSIG may be proposed to spin out into a separately chartered group. It is specifically in scope to: Group Charter bridge data and ontologies developed by individual communities of practice in HCLS. It is expected these vocabularies will be expressed in RDF Schema organizations that are actively working on relevant standards and/or implementations to which the HCLS’s work might contribute. In some cases, work started and / or OWL to maximize reuse among the community. Example vocabularies include but are not limited to:The group will: Discuss the relevance and maturity of tools. in HCLS IG may be proposed to spin out into a separately chartered group. It is specifically within the scope of the HCLS IG to: Create vocabulary guidelines. provenance and context: identifying data (e.g. gene banks, protein databases, disease knowledge bases such as SNOMED CT, drug information Build demonstrations and test suites. Create Linked Data and guidelines to help others create Linked Data. knowledge bases, templates for collecting clinical trial data, collections of rules bases comprising clinical decision support logic, etc.) sources, Create vocabularies and vocabulary bridges. Public Wiki page Create collateral within the scope of this interest group. authors, publications names, and collection conditions in HCLS. Build demonstrations and test suites. Assist other groups to create data and tools within the scope of this interest group. citation: vocabularies for supporting cross-references in publication and other reporting of experimental results in HCLS. 1.1 Success Criteria Advise industry on the relevance and maturity of tools. versioning: vocabularies for expressing change and relationships among changed resources (e.g. experimental data sets, clinical trials data sets, Increased consensus around vocabulary choice and use of terminology spanning patient records and clinical research. Instructions on joining the IG ontologies, etc.) in HCLS. 1.1 Success Criteria Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. Development of consensus around core taxonomies and methodologies for representing knowledge in Life Science, Translational Medicine and Health Care. cross-mapping: bridging and/or merging of ontologies that could have either overlapping or orthogonal concepts. Building on the successes of the last edition of the HCLS IG, the group will continue with a refinement of earlier criteria: Adoption of these taxonomies and methodologies by standards organizations that are focused on life science and health care leading to increased understanding and adoption of Semantic Web technologies. Guidelines and Best Practices for Resource Identification: The Interest Group will provide guideline on how best to identify HCLS resources for Participants: Presentation of these taxonomies and methodologies to government, academia and industry organizations that have a keen interest in the application of Development of consensus around core taxonomies and methodologies for representing knowledge in Life Science, Translational Medicine and Health Implement proof-of-concept demonstrations and industry-ready code. use in the Semantic Web. Implementation issues include: Care. information technology to these domains, and support of their efforts to adopt Semantic Web technologies. Increased consensus around vocabulary choice and use of terminology spanning patient records and clinical research. referential integrity Adoption of these taxonomies and methodologies by standards organizations that are focused on life science and health care leading to increased 2. Motivations understanding and adoption of Semantic Web technologies. organizations resource identification for existing and future Semantic Web resources Document guidelines to accelerate the adoption of the technology. Presentation of these taxonomies and methodologies to government, academia and industry organizations that have a keen interest in the application of version control 2.1 Biological Science information technology to these domains, and support of their efforts to adopt Semantic Web technologies. Dissemination of infrastructure and information enabling different groups to contribute usefully to the Semantic Web around health care and life sciences. presence / absence of semantics Development of policy and access control enabling proprietary Linked Data complementing the public Linked Data to be exchanged in limited An understanding of the fundamental underlying principles of biology forms the basis on which all biomedical research relies. Biological research investigates Disseminate information about the groups work at government, industry, academic events and by participating in persons (member only link) partnerships. Scientific and Scholarly Publication: The Interest Group will provide guidelines, suggested best practices, and use of descriptive vocabularies to phenomena at a range of scales: molecules, cells, cell populations, tissues, organs, organisms, populations, and ecosystems and employs an astounding Strategies for defining and reasoning at run-time at service interfaces, enabling "semantically-aware" workflows to sold business problems. better enable the integration and relationships among people, data, observations, software, collections of algorithms, and scholarly publications / clinical variety of experimental techniques, instruments and reagents. This research (e.g. gene expression, phenotypes, chemical screening, ...) generates data and trials. conclusions from which new hypotheses are drawn which subsequently propel new studies at an ever increasing rate. The resulting proliferation of isolated databases hampers efforts to combine results. 2. Motivations community initiatives. Duration The HCLSIG focus area will aid this enterprise and provide ways for researchers in the applied fields to make the best use of the richness of this rapidly The Semantic Web can help us realize the general goal of facilitating research and analytics in the focus areas of biological science and health care, and their accumulating knowledge. HCLSIG activities in the this area will include working with key data repositories towards their semantic integration by advocating for application to translational medicine. The HCLSIG will be chartered for 2 years, beginning in September 2005. and assisting labs, database creators and publishers who would make information accessible using Semantic Web technologies. The group will apply ontologies to the integration of heterogeneous data, show how common analysis tools can use data from and publish to the Semantic Web, and explore other Mailing list archives Deliverables ways that Semantic Web technologies might further facilitate this scientific work. 2.1 Biological Science The HCLSIG will provide a forum for supporting, guiding and collecting application and implementation experience, along with business and use cases An understanding of the fundamental underlying principles of biology forms the basis on which all biomedical research relies. Biological research investigates associated with using Semantic Web technologies to solve life science and health care problems. The discussion or tools, demonstrations, test suites, 2.2 Translational Medicine phenomena at a range of scales: molecules, cells, cell populations, tissues, organs, organisms, populations, and ecosystems and employs an astounding validation tools, and developer resources are all within scope of this interest group. More specifically: variety of experimental techniques, instruments and reagents. This research (e.g. gene expression, phenotypes, chemical screening, ...) generates data and Recent advances in biological understanding are allowing pharmaceutical companies to begin to develop tailored therapeutics, thereby allowing patients to conclusions from which new hypotheses are drawn which subsequently propel new studies at an ever increasing rate. The resulting proliferation of isolatedParticipation Vocabularies that enable broad application of core Semantic Web technologies in Health Care and Life Sciences, for example: context, provenance, receive the right drug, at the right dose, and at the right time. However, in order for such treatments to be developed, companies need to be able to better link databases hampers efforts to combine results. data from the laboratory to the clinic (bench to bedside). This concept is frequently referred to as translational medicine. cross-reference, experimental reporting, versioning, and publication. Guidance for how best to express existing ontologies used by this domain in terms of Semantic Web technologies are also in scope. The HCLS IG focus area will aid this enterprise and provide ways for researchers in the applied fields to make the best use of the richness of this rapidly This HCLSIG activity will provide resources that demonstrate the value of Semantic Web technologies to translational medicine. Activities in this area will focus accumulating knowledge. HCLS IG activities in the this area will include working with key data repositories towards their semantic integration by advocating for Implementations of vocabularies and recommendations for demonstration and use in Health Care and Life Sciences applications such as electronic on connecting pre-clinical and clinical trial data with clinical decision support knowledge in order to assess drug efficacy and safety. Examples of potential and assisting labs, database creators and publishers who would make information accessible using Semantic Web technologies. The group will apply health record, clinical decision support, drug discovery, clinical trials and translation medicine. activities include the integration of health outcome data for identification of safety signals, aggregation of clinical trials data for identification of studies of ontologies to the integration of heterogeneous data, show how common analysis tools can use data from and publish to the Semantic Web, and explore other interest, demonstration of the minimal costs required for the integration of unforeseen data sets into an existing data model to enable answering unanticipated ways that Semantic Web technologies might further facilitate this scientific work. The IG will also adapt ontologies to meet the needs for evolving biological and Use cases, experience reports, guidelines, and best practices for deploying Semantic Web technologies within the Health Care and Life Sciences.Communications of the HCLS IG are public. This includes public meeting records and access to the archives of the public- scientific questions, and the creation of dashboards that show how heterogeneous and disparate data can be integrated to aid decision making. evidence models imposed by new techniques and instruments such as next-gen sequencing. The convening of workshops and interop events to support the exchange of business cases, lessons learned, and applications / toolkits to further demonstrate potential uses of Semantic Web technologies and capabilities to a broad audience of software developers and IT managers in the 2.3 Health Care 2.2 Health Care DOCUMENTS Health Care and Life Science industries.semweb-lifesci@w3.org mailing list. Within the larger domain of health care there has been a dramatic increase in the demand for information systems that capture expressive clinical data, host Pharmaceutical companies and individual patients, exploiting advances in translational medicine and informational infrastructure, are joining clinical interests in rich clinical knowledge, and are able to deliver robust decision support on behalf of healthcare quality improvement and clinical research. This HCLSIG activity Meeting reports, documents and Interest Group minutes will be available from the public HCLSIG home page. recording detailed patient records. As governments and patient advocacy groups demand improved performance from electronic patient records, such as will focus on applying the strengths of Semantic Web technologies directly relevant to meeting this demand. A primary goal will be to aid in efforts to unify the research or clinical decision support, clinicians, pharmaceutical companies and individuals with versatile semantic infrastructure will benefit from health care In order to meet the goal of delivering vocabularies and implementations within the time frame of this charter, the following draft milestones are collection of data for the purpose of both primary care (electronic medical records) and clinical research (patient recruitment, study management, outcomes- data which is easy to integrate with genomics, bio-informatics, chem-informatics and environmental data. This HCLS IG activity will focus on applying the based longitudinal analysis, etc.). defined. A more detailed set of milestones and specific events will be available on the HCLSIG home page. strengths of Semantic Web technologies directly relevant to meeting this demand. A primary goal will be to aid in efforts to unify the collection of data for the purpose of both primary care (electronic medical records) and clinical research (patient recruitment, study management, outcomes-based longitudinal analysis, This interest group will work towards promoting this goal in several ways. First, it will attempt to work with ongoing efforts to standardize and harmonize the January 2006 - Interest Group F2F ; identification of specific tasks to focus on, corresponding task force leaders and expected deliverables. etc.). Enabling semantic interoperability across organizational and jurisdictional boundaries through sharing and linking of such data is an important part of this acquisition and exchange of medical data led by standard bodies such as the CDISC, Health Level Seven (HL7) and BRIDG, enabling the use of these Suggested focus is on 4 month deliverables. Emerging practices for mapping and goal. standards with Semantic Web technologies. Second, it will collaborate with efforts focused on building formal ontologies for clinical medicine and investigationsThe HCLS IG welcomes active participation from representatives of W3C Member organizations. If you are part of a W3C February 2006 - Publication of initial report on vocabularies and detailed working plan expressed in Semantic Web languages such as OWL and RDFS. Finally, it will explore enabling interoperability through the documentation of mappings This interest group will work towards promoting this goal in several ways. First, it will attempt to work with ongoing efforts to standardize and harmonize the between terminologies. acquisition and exchange of medical data led by standard bodies such as the CDISC, Health Level Seven (HL7) and BRIDG, enabling the use of these April 2006 - Initial round of task force deliverables published. linking life sciences data using RDF — standards with Semantic Web technologies. Second, it will collaborate with efforts focused on building formal ontologies for clinical medicine and investigations Another topic of interest is building innovative clinical decision support capabilities into patient record systems. Our task in this area is to identify best practices May 2006 - Interest Group F2F ; Evaluate the status of existing task forces and target new ones accordingly. expressed in Semantic Web languages such as OWL and RDFS. Finally, it will explore enabling interoperability through the documentation of mappingsMember organization, please verify or create your W3C web account, then ask your Advisory Committe representative for clinical guideline representation in such a way that standards-based reasoning systems and knowledge sources can be leveraged in these patient record between terminologies. July 2006 - new round of task force deliverables published. systems. August 2006 - Public Semantic Web / Health Care and Life Sciences Interoperability Workshop 3. Deliverables A case series Another topic of interest is building innovative clinical decision support capabilities into patient record systems. Our task in this area is to identify best practices for clinical guideline representation in such a way that standards-based reasoning systems and knowledge sources can be leveraged in these patient record(member-only) to join the HCLS IG and nominate you to participate. More detailed instructions are available. October 2006 - Interest Group F2F ; Evaluate the status of existing task forces and target new ones accordingly. systems. Implementation and demonstrations of one or two use cases in each of the three focus areas. Ontology of Rhetorical Blocks (ORB) Dec 2006 - new round of task force deliverables published. Technical collateral including tutorials, experience reports, and guidelines. 2.1 Translational Medicine Business level communications and literature for use in liaison activities, to be updated biannually. Relationship with Other Activities Organization of at least one international workshop each year, to exchange knowledge on deployed systems, interesting use cases, lessons learned, and As research exposes more associations between genetics and medication outcomes, translational models are needed to allow health workers and researchers demos built. to access this information. Recent advances in biological understanding are allowing pharmaceutical companies to begin to develop tailored therapeutics, The HCLSIG will utilize W3C Semantic Web technologies where appropriate, and provide input back to such groups on use cases, experiences and Presentations, by members, of aspects of the groups activities at three to five relevant conferences or workshops each year. thereby allowing patients to receive the right drug, at the right dose, and at the right time. However, in order for such treatments to be developed, companies
    • SEMANTIC WEB HEALTH CARE AND LIFE SCIENCES (HCLS) INTEREST GROUPHOME “The Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) is chartered to develop and support the use of Semantic Web technologiesIntroductionThe mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, andsupportimprove collaboration, research andclinical research and translational medicine. to domains stand to gainWeb technologies across healthand inter-domain application of Semantic Web technologies as the use of Semantic care, life sciences, development, and innovation adoption inThese tremendous benefit from intra-they depend on the interoperability of information from many disciplines.and Life Science domains.” the Health Care Please see the accompanying Use Cases and LINKSRationale document. Interest Group links: Group CharterThe group will: Public Wiki page Instructions on joining the IG 2005-2007 2008-2011 Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. Implement proof-of-concept demonstrations and industry-ready code. 2011-2014 Participants: Document guidelines to accelerate the adoption of the technology. organizations This charter is now expired; please see the next HCLS IG charter. Scope Disseminate information about the groups work at government, industry, academic events and by participating in persons (member only link) Motivations Scope Deliverables Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) Charter Motivations Dependencies Deliverables Semantic Web Health Care and Life Sciences Interest Group Participation community initiatives. Dependencies Communication Contents Semantic Web Health Care and Life Sciences Interest Group Participation Communication Charter Decision Policy Patent Disclosures 1. Mission Statement Charter Mailing list archives Decision Policy The mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, and support About this Charter 2. Scope Patent Disclosures the use of Semantic Web technologies across health care, life sciences, clinical research and translational medicine. These domains The mission of the Semantic Web Health Care and Life Sciences Interest Group, part of the Semantic Web Activity, is to develop, About this Charter stand to gain tremendous benefit from intra- and inter-domain application of Semantic Web technologies as they depend on the 3. Duration interoperability of information from many disciplines. Please see the accompanying Use Cases and Rationale document. advocate for, and support the use of Semantic Web technologies for health care and life science, with focus on biological science and 4. Deliverables translational medicine. These domains stand to gain tremendous benefit by adoption of Semantic Web technologies, as they depend on the interoperability of information from many domains and processes for efficient decision support. The group will:Participation 5. Relationship with Other Activities The group will: Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. 6. Interest Group Participation Implement proof-of-concept demonstrations and industry-ready code. Document use cases to aid individuals in understanding the business and technical benefits of using Semantic Web technologies. Document guidelines to accelerate the adoption of the technology. 7. Meetings Disseminate information about the groups work at government, industry, academic events and by participating in community initiatives. Document guidelines to accelerate the adoption of the technology. 8. Group Communications Implement a selection of the use cases as proof-of-concept demonstrations. Explore the possibility of developing high level vocabularies. Join the Semantic Web Health Care and Life Sciences Interest Group. 9. Patent DisclosuresCommunications of the HCLS IG are public. This includes public meeting records and access to the archives of the public- Disseminate information about the groups work at government, industry, and academic events. End date 31 Aug 2014 Join the Semantic Web Health Care and Life Sciences Interest Group. Mission Statement Confidentiality Proceedings are Publicsemweb-lifesci@w3.org mailing list. The Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) is chartered to develop and support the use of Semantic Web technologies to improve collaboration, research and development, and innovation adoption in the of Health Care and Life Science domains. Success in these domains depends on a foundation of semantically rich system, process and information interoperability. To these ends, the HCLSIG will focus on End date Confidentiality 31 May 2011 Proceedings are Public Chairs DOCUMENTS Michel Dumontier (Carleton University) - life sciences Charles Mead (NCI CBIIT) Vijay Bulusu (Pfizer) - health care - pharmaceuticals Chair assignments will be reviewed every 18 months. Initial Chairs Susie Stephens, Chimezi Ogbuji, M. Scott Marshall the development of use cases that illustrate the business value of Semantic Web technology adoption, core vocabularies, guidelines and best practices regarding unique identifiers, and provide a forum for supporting communication, education, collaboration and implementation. The HCLSIG will also Initial Team Contacts Initial Team Contacts Eric Prudhommeaux Eric Prudhommeaux work with the other Semantic Web related groups to gather suggestions for further HCLSIG development work. Further, the HCLSIG will provide a (FTE %: 60) (FTE %: 50) forum to support and encourage the use of Semantic Web technologies and foster the growth of interoperable, policy-aware data and databases in the Emerging practices for mapping and Teleconferences: Weekly Teleconferences: Weekly Life Sciences and Health Care industries. Usual Meeting Schedule Usual Meeting ScheduleThe HCLS IG welcomes active participation from representatives of W3C Member organizations. If you are part of a W3C Face-to-face: at least one per year Face-to-face: at most once per year This work falls within the Technology and Society Domain and is part of W3Cs Semantic Web Activity. linking life sciences data using RDF — 1. Scope 1. Scope ScopeMember organization, please verify or create your W3C web account, then ask your Advisory Committe representative The HCLSIG will provide a forum for supporting, guiding and collecting application and implementation experience. It will develop and support Semantic Web The HCLS IG will continue to provide a forum for supporting, developing and applying Semantic Web technologies across healthcare, life sciences, clinical The HCLSIG is focused on the use of Semantic Web technologies to better enable interoperability and improve collaboration, research and development, A case series technologies in the three focus areas: life science, translational medicine, and health care. Within these areas, it will address use cases that have clear research and the continuum of translational medicine. Within these contexts, the HCLS IG will focus on the use of Semantic Web technologies to realize innovation adoption, and data reusability in the health Care and life science domains. Sample areas of work designed to facilitate this goal include: specific use cases which themselves have a specific clinical, research of business values. As use cases are developed, HCLS IG will solicit advice on technical scientific, business, and/or technical value. HCLSIG will solicit advice on technical matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will extensively liason with external organizations that are central to the areas to which matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will also focus(member-only) to join the HCLS IG and nominate you to participate. More detailed instructions are available. Core vocabularies: In order to stimulate cross-community data integration, collaborative efforts are required to define core vocabularies that can on developing ongoing and mutually productive liaisons with relevant external organizations in healthcare, life sciences, and clinical research, including we wish to contribute. In some cases, work started in HCLSIG may be proposed to spin out into a separately chartered group. It is specifically in scope to: bridge data and ontologies developed by individual communities of practice in HCLS. It is expected these vocabularies will be expressed in RDF Schema organizations that are actively working on relevant standards and/or implementations to which the HCLS’s work might contribute. In some cases, work started Ontology of Rhetorical Blocks (ORB) and / or OWL to maximize reuse among the community. Example vocabularies include but are not limited to: Discuss the relevance and maturity of tools. in HCLS IG may be proposed to spin out into a separately chartered group. It is specifically within the scope of the HCLS IG to: Create vocabulary guidelines. provenance and context: identifying data (e.g. gene banks, protein databases, disease knowledge bases such as SNOMED CT, drug information Build demonstrations and test suites. Create Linked Data and guidelines to help others create Linked Data. knowledge bases, templates for collecting clinical trial data, collections of rules bases comprising clinical decision support logic, etc.) sources, Create collateral within the scope of this interest group. Create vocabularies and vocabulary bridges. authors, publications names, and collection conditions in HCLS. Build demonstrations and test suites.
    • SEMANTIC WEB HEALTH CARE AND LIFE SCIENCES (HCLS) INTEREST GROUPHOME “The mission of the Semantic Web for Health Care and Life Sciences Interest Group, part of the Semantic Web Activity, is to develop, advocate for, and supportIntroductionThe mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, andsupport the use of Semantic Web technologiesWeb technologies for and translational medicine. and life science, the usestand toSemantic across healthand inter-domain application of Semantic Web technologies as of gain tremendous benefit from intra- care, life sciences, clinical research health careThese domainsthey depend with focus on biological sciencethe accompanying Use Cases and on the interoperability of information from many disciplines. Please see and translational medicine.” LINKSRationale document. Interest Group links: Group CharterThe group will: Public Wiki page Instructions on joining the IG 2005-2007 2008-2011 Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. Implement proof-of-concept demonstrations and industry-ready code. 2011-2014 Participants: Document guidelines to accelerate the adoption of the technology. organizations This charter is now expired; please see the next HCLS IG charter. Scope Disseminate information about the groups work at government, industry, academic events and by participating in persons (member only link) Motivations Scope Deliverables Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) Charter Motivations Dependencies Deliverables Semantic Web Health Care and Life Sciences Interest Group Participation community initiatives. Dependencies Communication Contents Semantic Web Health Care and Life Sciences Interest Group Participation Communication Charter Decision Policy Patent Disclosures 1. Mission Statement Charter Mailing list archives Decision Policy The mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, and support About this Charter 2. Scope Patent Disclosures the use of Semantic Web technologies across health care, life sciences, clinical research and translational medicine. These domains The mission of the Semantic Web Health Care and Life Sciences Interest Group, part of the Semantic Web Activity, is to develop, About this Charter stand to gain tremendous benefit from intra- and inter-domain application of Semantic Web technologies as they depend on the 3. Duration interoperability of information from many disciplines. Please see the accompanying Use Cases and Rationale document. advocate for, and support the use of Semantic Web technologies for health care and life science, with focus on biological science and 4. Deliverables translational medicine. These domains stand to gain tremendous benefit by adoption of Semantic Web technologies, as they depend on the interoperability of information from many domains and processes for efficient decision support. The group will:Participation 5. Relationship with Other Activities The group will: Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. 6. Interest Group Participation Implement proof-of-concept demonstrations and industry-ready code. Document use cases to aid individuals in understanding the business and technical benefits of using Semantic Web technologies. Document guidelines to accelerate the adoption of the technology. 7. Meetings Disseminate information about the groups work at government, industry, academic events and by participating in community initiatives. Document guidelines to accelerate the adoption of the technology. 8. Group Communications Implement a selection of the use cases as proof-of-concept demonstrations. Explore the possibility of developing high level vocabularies. Join the Semantic Web Health Care and Life Sciences Interest Group. 9. Patent DisclosuresCommunications of the HCLS IG are public. This includes public meeting records and access to the archives of the public- Disseminate information about the groups work at government, industry, and academic events. End date 31 Aug 2014 Join the Semantic Web Health Care and Life Sciences Interest Group. Mission Statement Confidentiality Proceedings are Publicsemweb-lifesci@w3.org mailing list. The Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) is chartered to develop and support the use of Semantic Web technologies to improve collaboration, research and development, and innovation adoption in the of Health Care and Life Science domains. Success in these domains depends on a foundation of semantically rich system, process and information interoperability. To these ends, the HCLSIG will focus on End date Confidentiality 31 May 2011 Proceedings are Public Chairs DOCUMENTS Michel Dumontier (Carleton University) - life sciences Charles Mead (NCI CBIIT) Vijay Bulusu (Pfizer) - health care - pharmaceuticals Chair assignments will be reviewed every 18 months. Initial Chairs Susie Stephens, Chimezi Ogbuji, M. Scott Marshall the development of use cases that illustrate the business value of Semantic Web technology adoption, core vocabularies, guidelines and best practices regarding unique identifiers, and provide a forum for supporting communication, education, collaboration and implementation. The HCLSIG will also Initial Team Contacts Initial Team Contacts Eric Prudhommeaux Eric Prudhommeaux work with the other Semantic Web related groups to gather suggestions for further HCLSIG development work. Further, the HCLSIG will provide a (FTE %: 60) (FTE %: 50) forum to support and encourage the use of Semantic Web technologies and foster the growth of interoperable, policy-aware data and databases in the Emerging practices for mapping and Teleconferences: Weekly Teleconferences: Weekly Life Sciences and Health Care industries. Usual Meeting Schedule Usual Meeting ScheduleThe HCLS IG welcomes active participation from representatives of W3C Member organizations. If you are part of a W3C Face-to-face: at least one per year Face-to-face: at most once per year This work falls within the Technology and Society Domain and is part of W3Cs Semantic Web Activity. linking life sciences data using RDF — 1. Scope 1. Scope ScopeMember organization, please verify or create your W3C web account, then ask your Advisory Committe representative The HCLSIG will provide a forum for supporting, guiding and collecting application and implementation experience. It will develop and support Semantic Web The HCLS IG will continue to provide a forum for supporting, developing and applying Semantic Web technologies across healthcare, life sciences, clinical The HCLSIG is focused on the use of Semantic Web technologies to better enable interoperability and improve collaboration, research and development, A case series technologies in the three focus areas: life science, translational medicine, and health care. Within these areas, it will address use cases that have clear research and the continuum of translational medicine. Within these contexts, the HCLS IG will focus on the use of Semantic Web technologies to realize innovation adoption, and data reusability in the health Care and life science domains. Sample areas of work designed to facilitate this goal include: specific use cases which themselves have a specific clinical, research of business values. As use cases are developed, HCLS IG will solicit advice on technical scientific, business, and/or technical value. HCLSIG will solicit advice on technical matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will extensively liason with external organizations that are central to the areas to which matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will also focus(member-only) to join the HCLS IG and nominate you to participate. More detailed instructions are available. Core vocabularies: In order to stimulate cross-community data integration, collaborative efforts are required to define core vocabularies that can on developing ongoing and mutually productive liaisons with relevant external organizations in healthcare, life sciences, and clinical research, including we wish to contribute. In some cases, work started in HCLSIG may be proposed to spin out into a separately chartered group. It is specifically in scope to: bridge data and ontologies developed by individual communities of practice in HCLS. It is expected these vocabularies will be expressed in RDF Schema organizations that are actively working on relevant standards and/or implementations to which the HCLS’s work might contribute. In some cases, work started Ontology of Rhetorical Blocks (ORB) and / or OWL to maximize reuse among the community. Example vocabularies include but are not limited to: Discuss the relevance and maturity of tools. in HCLS IG may be proposed to spin out into a separately chartered group. It is specifically within the scope of the HCLS IG to: Create vocabulary guidelines. provenance and context: identifying data (e.g. gene banks, protein databases, disease knowledge bases such as SNOMED CT, drug information Build demonstrations and test suites. Create Linked Data and guidelines to help others create Linked Data. knowledge bases, templates for collecting clinical trial data, collections of rules bases comprising clinical decision support logic, etc.) sources, Create collateral within the scope of this interest group. Create vocabularies and vocabulary bridges. authors, publications names, and collection conditions in HCLS. Build demonstrations and test suites.
    • SEMANTIC WEB HEALTH CARE AND LIFE SCIENCES (HCLS) INTEREST GROUPHOME “The mission of the Semantic Web Health Care and Life Sciences Interest GroupIntroduction IG) is to develop, advocate for, and support the use of Semantic Web (HCLSThe mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, andsupport the use of Semantic Web technologies across health care, care, life sciences, clinical research and technologies across from intra- and inter-domain application of Semantictranslational medicine. health life sciences, clinical research and Web technologies asThese domains stand to gain tremendous benefitthey depend on the interoperability of information from translational medicine.” many disciplines. Please see the accompanying Use Cases and LINKSRationale document. Interest Group links: Group CharterThe group will: Public Wiki page Instructions on joining the IG 2005-2007 2008-2011 Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. Implement proof-of-concept demonstrations and industry-ready code. 2011-2014 Participants: Document guidelines to accelerate the adoption of the technology. organizations This charter is now expired; please see the next HCLS IG charter. Scope Disseminate information about the groups work at government, industry, academic events and by participating in persons (member only link) Motivations Scope Deliverables Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) Charter Motivations Dependencies Deliverables Semantic Web Health Care and Life Sciences Interest Group Participation community initiatives. Dependencies Communication Contents Semantic Web Health Care and Life Sciences Interest Group Participation Communication Charter Decision Policy Patent Disclosures 1. Mission Statement Charter Mailing list archives Decision Policy The mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, and support About this Charter 2. Scope Patent Disclosures the use of Semantic Web technologies across health care, life sciences, clinical research and translational medicine. These domains The mission of the Semantic Web Health Care and Life Sciences Interest Group, part of the Semantic Web Activity, is to develop, About this Charter stand to gain tremendous benefit from intra- and inter-domain application of Semantic Web technologies as they depend on the 3. Duration interoperability of information from many disciplines. Please see the accompanying Use Cases and Rationale document. advocate for, and support the use of Semantic Web technologies for health care and life science, with focus on biological science and 4. Deliverables translational medicine. These domains stand to gain tremendous benefit by adoption of Semantic Web technologies, as they depend on the interoperability of information from many domains and processes for efficient decision support. The group will:Participation 5. Relationship with Other Activities The group will: Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies. 6. Interest Group Participation Implement proof-of-concept demonstrations and industry-ready code. Document use cases to aid individuals in understanding the business and technical benefits of using Semantic Web technologies. Document guidelines to accelerate the adoption of the technology. 7. Meetings Disseminate information about the groups work at government, industry, academic events and by participating in community initiatives. Document guidelines to accelerate the adoption of the technology. 8. Group Communications Implement a selection of the use cases as proof-of-concept demonstrations. Explore the possibility of developing high level vocabularies. Join the Semantic Web Health Care and Life Sciences Interest Group. 9. Patent DisclosuresCommunications of the HCLS IG are public. This includes public meeting records and access to the archives of the public- Disseminate information about the groups work at government, industry, and academic events. End date 31 Aug 2014 Join the Semantic Web Health Care and Life Sciences Interest Group. Mission Statement Confidentiality Proceedings are Publicsemweb-lifesci@w3.org mailing list. The Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) is chartered to develop and support the use of Semantic Web technologies to improve collaboration, research and development, and innovation adoption in the of Health Care and Life Science domains. Success in these domains depends on a foundation of semantically rich system, process and information interoperability. To these ends, the HCLSIG will focus on End date Confidentiality 31 May 2011 Proceedings are Public Chairs DOCUMENTS Michel Dumontier (Carleton University) - life sciences Charles Mead (NCI CBIIT) Vijay Bulusu (Pfizer) - health care - pharmaceuticals Chair assignments will be reviewed every 18 months. Initial Chairs Susie Stephens, Chimezi Ogbuji, M. Scott Marshall the development of use cases that illustrate the business value of Semantic Web technology adoption, core vocabularies, guidelines and best practices regarding unique identifiers, and provide a forum for supporting communication, education, collaboration and implementation. The HCLSIG will also Initial Team Contacts Initial Team Contacts Eric Prudhommeaux Eric Prudhommeaux work with the other Semantic Web related groups to gather suggestions for further HCLSIG development work. Further, the HCLSIG will provide a (FTE %: 60) (FTE %: 50) forum to support and encourage the use of Semantic Web technologies and foster the growth of interoperable, policy-aware data and databases in the Emerging practices for mapping and Teleconferences: Weekly Teleconferences: Weekly Life Sciences and Health Care industries. Usual Meeting Schedule Usual Meeting ScheduleThe HCLS IG welcomes active participation from representatives of W3C Member organizations. If you are part of a W3C Face-to-face: at least one per year Face-to-face: at most once per year This work falls within the Technology and Society Domain and is part of W3Cs Semantic Web Activity. linking life sciences data using RDF — 1. Scope 1. Scope ScopeMember organization, please verify or create your W3C web account, then ask your Advisory Committe representative The HCLSIG will provide a forum for supporting, guiding and collecting application and implementation experience. It will develop and support Semantic Web The HCLS IG will continue to provide a forum for supporting, developing and applying Semantic Web technologies across healthcare, life sciences, clinical The HCLSIG is focused on the use of Semantic Web technologies to better enable interoperability and improve collaboration, research and development, A case series technologies in the three focus areas: life science, translational medicine, and health care. Within these areas, it will address use cases that have clear research and the continuum of translational medicine. Within these contexts, the HCLS IG will focus on the use of Semantic Web technologies to realize innovation adoption, and data reusability in the health Care and life science domains. Sample areas of work designed to facilitate this goal include: specific use cases which themselves have a specific clinical, research of business values. As use cases are developed, HCLS IG will solicit advice on technical scientific, business, and/or technical value. HCLSIG will solicit advice on technical matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will extensively liason with external organizations that are central to the areas to which matters from other Semantic Web related groups within W3C and give feedback on the use of technologies based on the work they do. The IG will also focus(member-only) to join the HCLS IG and nominate you to participate. More detailed instructions are available. Core vocabularies: In order to stimulate cross-community data integration, collaborative efforts are required to define core vocabularies that can on developing ongoing and mutually productive liaisons with relevant external organizations in healthcare, life sciences, and clinical research, including we wish to contribute. In some cases, work started in HCLSIG may be proposed to spin out into a separately chartered group. It is specifically in scope to: bridge data and ontologies developed by individual communities of practice in HCLS. It is expected these vocabularies will be expressed in RDF Schema organizations that are actively working on relevant standards and/or implementations to which the HCLS’s work might contribute. In some cases, work started Ontology of Rhetorical Blocks (ORB) and / or OWL to maximize reuse among the community. Example vocabularies include but are not limited to: Discuss the relevance and maturity of tools. in HCLS IG may be proposed to spin out into a separately chartered group. It is specifically within the scope of the HCLS IG to: Create vocabulary guidelines. provenance and context: identifying data (e.g. gene banks, protein databases, disease knowledge bases such as SNOMED CT, drug information Build demonstrations and test suites. Create Linked Data and guidelines to help others create Linked Data. knowledge bases, templates for collecting clinical trial data, collections of rules bases comprising clinical decision support logic, etc.) sources, Create collateral within the scope of this interest group. Create vocabularies and vocabulary bridges. authors, publications names, and collection conditions in HCLS. Build demonstrations and test suites.
    • Linked LOV User Slideshare tags2con Audio Feedback 2RDF delicious Moseley Scrobbler Bricklink Sussex Folk (DBTune) Reading St. GTAA Magna- Lists Andrews Klapp- tune stuhl- Resource NTU DB club Lists Resource Tropes Lotico Semantic yovisto John Music Man- Lists Music Tweet chester Hellenic Peel Brainz NDL (DBTune) (Data Brainz Reading subjects FBD (zitgist) Lists Open EUTC Incubator) Linked Hellenic Library Open t4gm Produc- Crunch- PD Surge RDF info tions Discogs base Library Radio Ontos Source Code Crime ohloh Plymouth (Talis) (Data News LEM Ecosystem Reading RAMEAU Reports business Incubator) Crime data.gov. Portal Linked Data Lists SH UK Music Jamendo (En- uk Brainz (DBtune) LinkedL Ox AKTing) FanHubz gnoss ntnusc (DBTune) SSW CCN Points Thesau- Last.FM Poké- Thesaur Popula- artists pédia Didactal us rus W LIBRIS tion (En- (DBTune) Last.FM ia theses. LCSH Rådata reegle research patents MARC AKTing) (rdfize) my fr nå! data.gov. data.go Codes Ren. NHS uk v.uk Good- Experi- Classical List Energy (En- win flickr ment (DB Pokedex Norwe- Genera- AKTing) Mortality BBC Family wrappr Sudoc PSH Tune) gian (En- tors Program MeSH AKTing) semantic mes BBC IdRef GND CO2 educatio OpenEI web.org SW Energy Sudoc ndlna Emission n.data.g Music Dog VIAF EEA (En- Chronic- Linked (En- ov.uk Portu- Food UB AKTing) ling Event MDB AKTing) guese Mann- Europeana BBC America Media DBpedia Calames heim Ord- Recht- Wildlife Deutsche Open Revyu DDC Openly spraak. Finder Bio- lobid Election nance legislation Local nl RDF graphie Resources NSZL Swedish Data Survey Tele- data Ulm EU New Book Project data.gov.uk graphis bnf.fr Catalog Open Insti- York Open Mashup Cultural tutions Times URI Greek P20 UK Post- Burner Calais Heritage codes DBpedia ECS Wiki statistics lobid GovWILD data.gov. Taxon iServe South- Organi- LOIUS BNBBrazilian uk Concept ECS ampton sations Geo World OS BibBase STW GESIS Poli- ESD South- ECS Names Fact- (RKB ticians stan- reference ampton data.gov.uk book Freebase Explorer) Budapest dards data.gov. NASA EPrints uk intervals Project OAI Lichfield transport (Data DBpedia data Guten- Pisa Spen- data.gov. Incu- dcs RESEX Scholaro- ISTAT ding bator) Fishes berg DBLP DBLP uk Geo meter Immi- Scotland of Texas (FU (L3S) Pupils & Uberblic DBLP gration Species Berlin) IRIT Exams Euro- dbpedia data- (RKB London TCM ACM stat lite open- Explorer) NVD Gazette (FUB) Gene IBM Traffic Geo ac-uk Scotland TWC LOGD Eurostat Daily DIT Linked UN/ Data UMBEL Med ERA Data LOCODE DEPLOY Gov.ie CORDIS YAGO New- lingvoj Disea- (RKB some SIDER RAE2001 castle LOCAH CORDIS Explorer) Linked Eurécom Eurostat Drug CiteSeer Roma (FUB) Sensor Data GovTrack (Ontology (Kno.e.sis) Open Bank Pfam Course- Central) riese Enipedia Cyc Lexvo LinkedCT ware Linked PDB UniProt VIVO EURES EDGAR dotAC US SEC Indiana ePrints IEEE (Ontology totl.net (rdfabout) Central) WordNet RISKS (VUA) Taxono UniProt US Census EUNIS Twarql HGNC Semantic Cornetto (Bio2RDF) (rdfabout) my VIVO FTS XBRL PRO- ProDom STITCH Cornell LAAS SITE KISTI NSF Scotland Geo- GeoWord LODE graphy Net WordNet WordNet JISC (W3C) (RKB Climbing Linked Affy- KEGG SMC Explorer) SISVU Pub VIVO UF Piedmont GeoData metrix Drug ECCO- Finnish Journals PubMed Gene SGD Chem Munici- Accomo- El AGROV Ontology TCP Media dations Alpine bible palities Viajero OC Ski ontology Tourism KEGG Ocean Austria Enzyme PBAC Geographic Metoffice GEMET ChEMBL Italian Drilling OMIM KEGG Weather Open public Codices AEMET Linked MGI Pathway schools Forecasts Data Open InterPro GeneID Publications EARTh Thesau- KEGG Turismo rus Colors Reaction de Zaragoza Product Smart KEGG User-generated content Weather DB Link Medi Glycan Janus Stations Product Care KEGG AMP UniParc UniRef UniSTS Government Types Italian Homolo Com- Yahoo! Airports Museums pound Ontology Google Gene Geo Art Planet National wrapper Chem2 Cross-domain Radio- Bio2RDF activity UniPath JP Sears Open Linked OGOLOD way Life sciences Corpo- Amster- Reactome dam medu- Open rates Numbers Museum cator As of September 2011 Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/
    • Linked LOV User Slideshare tags2con Audio Feedback 2RDF delicious Moseley Scrobbler Bricklink Sussex Folk (DBTune) Reading St. GTAA Magna- Lists Andrews Klapp- tune stuhl- Resource NTU DB club Lists Resource Tropes Lotico Semantic yovisto John Music Man- Lists Music Tweet chester Hellenic Peel Brainz NDL (DBTune) (Data Brainz Reading subjects FBD (zitgist) Lists Open EUTC Incubator) Linked Hellenic Library Open t4gm Produc- Crunch- PD Surge RDF info tions Discogs base Library Radio Ontos Source Code Crime ohloh Plymouth (Talis) (Data News LEM Ecosystem Reading RAMEAU Reports business Incubator) Crime data.gov. Portal Linked Data Lists SH UK Music Jamendo (En- uk Brainz (DBtune) LinkedL Ox AKTing) FanHubz gnoss ntnusc (DBTune) SSW CCN Points Thesau- Last.FM Poké- Thesaur Popula- artists pédia Didactal us rus W LIBRIS tion (En- (DBTune) Last.FM ia theses. LCSH Rådata reegle research patents MARC AKTing) (rdfize) my fr nå! data.gov. data.go Codes Ren. NHS uk v.uk Good- Experi- Classical List Energy (En- win flickr ment (DB Pokedex Norwe- Genera- AKTing) Mortality BBC Family wrappr Sudoc PSH Tune) gian (En- tors Program MeSH AKTing) semantic mes BBC IdRef GND CO2 educatio OpenEI web.org SW Energy Sudoc ndlna Emission n.data.g Music Dog VIAF EEA (En- Chronic- Linked (En- ov.uk Portu- Food UB AKTing) ling Event MDB AKTing) guese Mann- Europeana BBC America Media DBpedia Calames heim Ord- Recht- Wildlife Deutsche Open Revyu DDC Openly spraak. Finder Bio- lobid Election nance legislation Local nl RDF graphie Resources NSZL Swedish Data Survey Tele- data Ulm EU New Book Project data.gov.uk graphis bnf.fr Catalog Open Insti- York Open Mashup Cultural tutions Times URI Greek P20 UK Post- Burner Calais Heritage codes DBpedia ECS Wiki statistics lobid GovWILD data.gov. Taxon iServe South- Organi- LOIUS BNBBrazilian uk Concept ECS ampton sations Geo World OS BibBase STW GESIS Poli- ESD South- ECS Names Fact- (RKB ticians stan- reference ampton data.gov.uk book Freebase Explorer) Budapest dards data.gov. NASA EPrints uk intervals Project OAI Lichfield transport (Data DBpedia data Guten- Pisa Spen- data.gov. Incu- dcs RESEX Scholaro- ISTAT ding bator) Fishes berg DBLP DBLP uk Geo meter Immi- Scotland of Texas (FU (L3S) Pupils & Uberblic DBLP gration Species Berlin) IRIT Exams Euro- dbpedia data- (RKB London TCM ACM stat lite open- Explorer) NVD Gazette (FUB) Gene IBM Traffic Geo ac-uk Scotland TWC LOGD Eurostat Daily DIT Linked UN/ Data UMBEL Med ERA Data LOCODE DEPLOY Gov.ie CORDIS YAGO New- lingvoj Disea- (RKB some SIDER RAE2001 castle LOCAH CORDIS Explorer) Linked Eurécom Eurostat Drug CiteSeer Roma (FUB) Sensor Data GovTrack (Ontology (Kno.e.sis) Open Bank Pfam Course- Central) riese Enipedia Cyc Lexvo LinkedCT ware Linked PDB UniProt VIVO EURES EDGAR dotAC US SEC Indiana ePrints IEEE (Ontology totl.net (rdfabout) Central) WordNet RISKS (VUA) Taxono UniProt US Census EUNIS Twarql HGNC Semantic Cornetto (Bio2RDF) (rdfabout) my VIVO FTS XBRL PRO- ProDom STITCH Cornell LAAS SITE KISTI NSF Scotland Geo- GeoWord LODE graphy Net WordNet WordNet JISC (W3C) (RKB Climbing Linked Affy- KEGG SMC Explorer) SISVU Pub VIVO UF Piedmont GeoData metrix Drug ECCO- Finnish Journals PubMed Gene SGD Chem Munici- Accomo- El AGROV Ontology TCP Media dations Alpine bible palities Viajero OC Ski ontology Tourism KEGG Ocean Austria Enzyme PBAC Geographic Metoffice GEMET ChEMBL Italian Drilling OMIM KEGG Weather Open public Codices AEMET Linked MGI Pathway Forecasts Data InterPro GeneID Publications schools EARTh Thesau- Open KEGG Turismo rus Colors Reaction de Zaragoza Product Smart User-generated content KEGG Weather DB Link Medi Glycan Janus Stations Product Care AMP UniParc UniRef UniSTS Government Types Italian Homolo Com- Yahoo! Airports Museums pound Ontology Google Gene Geo Art Planet National wrapper Chem2 Cross-domain Radio- Bio2RDF activity UniPath JP Sears Open Linked OGOLOD way Life sciences Corpo- Amster- Reactome dam medu- Open rates Numbers Museum cator As of September 2011 Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/
    • Image Courtesy of Umberto Salvagnin and Quote from W3C HCLS IG Charter
    • “An understanding of the fundamental underlying principles of biology forms the basis on which all biomedical research relies.Biological research investigates phenomena at a range of scales: molecules, cells, cell populations, tissues, organs, organisms, populations, and ecosystems and employs an astounding variety of experimental techniques, instruments and reagents.” Image Courtesy of Umberto Salvagnin and Quote from W3C HCLS IG Charter
    • “Discovery increasingly done in silico on results obtainedfrom experiments using computational analysis and data repositories.” mining analysis integration prediction hypothesis integration experiment mining analysis results Adopted from the Slides of Carole Goble, ISWC 2005
    • According to the 2013 Nucleic Acids Research (NAR)online Molecular Biology Database Collection, 1512 public databases exist.
    • ★ make your stuff available on the Web (whatever format) under an open license ★★ make it available as structured data (e.g., Excel instead of image scan of a table) ★★★ use non-proprietary formats (e.g., CSV instead of Excel) ★★★★ use URIs to denote things, so that people can point at your stuff★★★★★ link your data to other data to provide context Adopted from Tim Berners-Lee’s Note on Linked Data. http://www.w3.org/DesignIssues/LinkedData.html
    • a framework to create and provide linked data for the life sciences Adopted from the Slides of Michel Dumontier
    • Virtuoso RDFization Triple StoreDownload URI Normalization Services Adopted from the Slides of Michel Dumontier
    • Image Courtesy of Allan Baxter
    • The Banff Manifesto Rules of Thumb1 URIs are normalized and dereferenceable.2 Authoritative public namespaces are used.3 Mandatory predicates are used.4 Blank nodes are forbidden.5 RDFizer programs are open source.6 Dereferenceable ontologies. Image Courtesy of Allan Baxter
    • 1 URIs are normalized and dereferenceable. When available, use the provider’s identifier in the naming the resource. http://bio2rdf.org/namespace:identifierFor example, the Bio2RDF URL for the DrugBank record with the identifier DB00650 would be: http://bio2rdf.org/drugbank:DB00650 Types and predicates that are generated to support the semantic annotation are in the vocabulary namespace. (type) http://bio2rdf.org/drugbank_vocabulary:Drug (predicate) http://bio2rdf.org/drugbank_vocabulary:target Adopted from the Slides of Michel Dumontier
    • 1 URIs are normalized and dereferenceable. Adopted from the Slides of Michel Dumontier
    • 2 Authoritative public namespaces are used. An initial registry of ~600 datasets is accessible through an API provided. It includes: dataset title, preferred namespace prefix, alternative namespace prefixes Adopted from the Slides of Michel Dumontier
    • 2 Authoritative public namespaces are used. In the last summer, Bio2RDF team consolidated and curated nearly 2,100 entries in a Google spreadsheet, which includes a mostly complete coverage of datasets/collections listed in Bio2RDF, MIRIAM, BioPortal, UniProt, NCBI, and NAR Database Issue. Working with Identifiers.org team (Nick Juty, Camille Laibe, Nicolas Le Novere) to have a single dataset registry that we can use for both Bio2RDF and identifiers.org enable automatic cross-links between Bio2RDF and identifiers.org Adopted from the Slides of Michel Dumontier
    • 3 Mandatory predicates are used. Banff Manifesto RDF documents must contain at least the following predicates: http://bio2rdf.org/drugbank:DB00650 rdf:type | the class of object described by the document http://bio2rdf.org/drugbank_vocabulary:Drug Adopted from Bio2RDF RDFization Guide v1.1
    • 3 Mandatory predicates are used. Banff Manifesto RDF documents must contain at least the following predicates: http://bio2rdf.org/drugbank:DB00650 dc:identifier | a string that contains the identifier using the following pattern <namespace>:<identifier> “drugbank:DB00650” Adopted from Bio2RDF RDFization Guide v1.1
    • 3 Mandatory predicates are used. Banff Manifesto RDF documents must contain at least the following predicates: http://bio2rdf.org/drugbank:DB00650 dc:title | a human readable title as it appears in the source data “Leucovorin” Adopted from Bio2RDF RDFization Guide v1.1
    • 3 Mandatory predicates are used. Banff Manifesto RDF documents must contain at least the following predicates: http://bio2rdf.org/drugbank:DB00650 rdfs:label | a Bio2RDF generated label containing a title followed by the identifier “title [namespace:identifier]” “Leucovorin [drugbank:DB00650]” Adopted from Bio2RDF RDFization Guide v1.1
    • 4 Blank nodes are forbidden. If in the process of converting a dataset to RDF you create new identifiers that did not previously exist in the dataset being converted, then use a namespace_resource namespace. http://bio2rdf.org/drugbank:DB00650 drugbank_vocabulary:ddi-interactor-in http://bio2rdf.org/drugbank_resource:DB00440_DB00650 rdf:type drugbank_vocabulary:Drug-Drug-Interaction Adopted from the Slides of Michel Dumontier
    • 4 Blank nodes are forbidden. If in the process of converting a dataset to RDF you create new identifiers that did not previously exist in the dataset being converted, then use a namespace_resource namespace. http://bio2rdf.org/drugbank:DB00650 drugbank_vocabulary:ddi-interactor-in http://bio2rdf.org/drugbank_resource:DB00440_DB00650 rdfs:label “DDI between Trimethoprim and Leucovorin [drugbank_resource:DB00440_DB00650]” Adopted from Bio2RDF RDFization Guide v1.1
    • 5 RDFizer programs are open source.
    • 6 Dereferenceable ontologies. “Researchers and practitioners in the Semantic Web normally deal with two types of data: (1) ontologies, vocabularies or TBoxes; and (2) instance data or simply data. It is important to clarify that BioPortal’s content is almost exclusively ontologies and related artifacts. By contrast, most other datasets of the Linked Data Cloud focus on instance data and ontologies and vocabularies play only a small role there.” Quote from Manuel Salvadores et al.
    • 6 Dereferenceable ontologies. UMLS MySQL Release UMLS2RDF RRF/UMLS (RRF) Protege-backend Protege-API Metadata Triple Store (Metadata) (4store) BioPortal File Download Service OWL-API OWL and OBO SPARQL (OWL and OBO) (Import Closure) Import Materialized OWL and OBO Imports Web Adopted from the Paper of Manuel Salvadores et al.
    • 6 Dereferenceable ontologies.“In addition to SPARQL access, BioPortal provides de-referenceable terms and ontology URIs. Individual terms can be resolved in RDF by dereferencing a specific term URI. Term URIs are normally in the name space that ontology authors have defined, which is outside of BioPortal’s domain. To provide linked data for these URIs, our Web front-end provides permanent URLs for each ontology term using a PURL server.” http://purl.bioontology.org/ontology/{ACR}:{SHORT_ID} “The PURL server will redirect this URL to get information about the term with the ID SHORT_ID in the ontology identified by a unique acronym ACR.” Adopted from Manuel Salvadores et al.
    • 6 Dereferenceable ontologies.
    • drugbank_vocabulary:Drug rdf:type rdfs:labeldrugbank:DB00650 “Leucovorin [drugbank:DB00650]” pharmgkb_vocabulary:xrefpharmgkb:PA450198 “leucovorin [pharmgkb:PA450198]” rdfs:label rdf:typepharmgkb_vocabulary:Drug Adopted from the Slides of Michel Dumontier
    • What links to DrugBank’s Leucovorin? http://bio2rdf.org/linksns/drugbank/drugbank:DB00650
    • SPARQL 1.1 Federated QuerySELECT ?chem, ?prot, ?procFROM <http://bio2rdf.org/ctd>WHERE { ?chemical a sio:chemical-entity. ?chemical rdfs:label ?chem. ?chemical sio:is-participant-in ?process. ?process rdfs:label ?proc. FILTER regex (?process, "http://bio2rdf.org/go:") SERVICE <http://sgd.bio2rdf.org/sparql> { ?protein a sio:protein . ?protein sio:is-participant-in ?process. ?protein rdfs:label ?prot . }} Adopted from the Slides of Michel Dumontier
    • Semantic Data Integration through RDF Warehousing
    • Six Linked Data Integration Patterns Image Courtesy of Ontotext
    • Applying Text Mining Technologies to Link the Text with Entities Semantic Annotations umls:C0035204 Respiration Disorders Chronic Obstructive Airway Diseases Bronchial Diseases umls:C0006261 COPD Asthma umls:C000496Clinical and experimental pharmacology … pmid:17714090 Ian A Yang #29 Adopted from the Slidesof Ontotext Image Courtesy of Vassil Momtchev
    • SourcesRepository overviewRepositoryID: LLD 1.1Description: Linked Life Data is a semantic data integration platform for the biomedical domain.Number of statements: 8,740,201,002Number of expl. statements: 5,918,290,955Number of entities: 2,068,072,570Data source Named graph Load date Statements Instances typeBioGRID http://linkedlifedata.com/resource/biogrid 2012.07.20 14,327,672 biopax-2:entityReference LicenseCellMap http://linkedlifedata.com/resource/cellmap 2012.07.20 154,863 biopax-Reference License 2:biochemicalReactionChEBI http://linkedlifedata.com/resource/chebi 2012.07.20 323,220 skos:ConceptReference LicenseDailyMed http://linkedlifedata.com/resource/dailymed 2012.07.20 162,972 dailymed:drugsReference LicenseDiseaseOntology http://linkedlifedata.com/resource/diseaseontology 2012.07.20 90,652 skos:ConceptReference LicenseDiseasome http://linkedlifedata.com/resource/diseasome 2012.07.20 72,445 diseasome:diseasesReference LicenseDrugBank http://linkedlifedata.com/resource/drugbank 2012.07.20 517,023 drugbank:drugsReference LicenseFreebase http://linkedlifedata.com/resource/freebase 2012.07.20 705,161,223Reference LicenseGeneOntology http://linkedlifedata.com/resource/geneontology 2012.07.20 364,947 skos:ConceptReference License
    • +Image Courtesy og Time
    • “Recent advances in biological understanding are allowing pharmaceutical companies to begin to develop tailored therapeutics, thereby allowing patients to receive the right drug, at the right dose, and at the right time. However, in order for such treatments to be developed, companies need to be able to better link data from the laboratory to the clinic (bench to bedside). This concept is frequently referred to as translational medicine.” Image Courtesy og Time
    • Image Courtesy of Anja Jentzsch et al.
    • LODD: Linked Open Drug Data Image Courtesy of Anja Jentzsch et al.
    • Image Courtesy of Mark Sharp et al.
    • Questions that LODD might Help to Answer:Physicians and Pharmacists • What are alternative drugs for a given indication (disease)? • What are equivalent drugs (generic version of a brand name, or the chemical name of a active ingredient)? • Are there ongoing clinical trials for a drug? Consumers • What background information is available about a drug? • Which alternative drugs are available? • What are the contraindications of a drug? • What are the results of clinical trials for a drug? Pharmaceutical Companies • What are other companies with drugs in similar areas? • Which companies have a similar therapeutic focus? Adopted from the Slides of Chistian Bizer
    • ClinicalTrial.gov
    • LinkedCT.org
    • Source / Target Link Type CountLinkedCT (intervention) owl:sameAs 11,527 ↔ DBpedia (drug)LinkedCT (intervention) rdfs:seeAlso 23,493 ↔ DrugBank (drug)LinkedCT (intervention) rdfs:seeAlso 39,396 ↔ DailyMed (drug) LinkedCT (condition) owl:sameAs 342 ↔ DBpedia (disease) LinkedCT (condition) owl:sameAs 830↔ Diseasome (disease) LinkedCT (trial) foaf:based_near 129,177 ↔ Geonames LinkedCT (reference) owl:sameAs 42,219↔ Bio2RDF’s PubMed LinkedCT (trial) foaf:page 61,920↔ ClinicalTrials.gov Adopted from the Paper of Oktie Hassanzadeh et al.
    • Luciano et al. Journal of Biomedical Semantics 2011, 2(Suppl 2):S1 Page 11 of 21http://www.jbiomedsem.com/content/2/S2/S1 Figure 3 TKMB overview. Overview of the contents of the Translational Medicine Knowledge Base (TMKB). TMKB is composed of the Translational Medicine Ontology with mappings to ontologies and terminologies listed in the NCBO BioPortal. The TMO provides a global schema for Indivo-based electronic health records (EHRs) and can be used with formalized criteria for Alzheimer’s Disease. The TMO maps types from Linking Open Data sources. Image Courtesy of Joanne S. Luciano et al.
    • Image Courtesy of Escape Fire
    • “As governments and patient advocacy groups demand improved performance from electronic patient records, such as research or clinical decision support, clinicians, pharmaceutical companies and individuals with versatile semantic infrastructure will benefit from health care data which is easy to integrate with genomics, bio-informatics, chem-informatics and environmental data.” Image Courtesy of Escape Fire
    • Image Courtesy of Pete Souza and Quote from the White House
    • “My Administration is committed to creating an unprecedented level of openness in government. We will work together to ensure the public trust and establish a system of transparency, public participation, and collaboration.” Image Courtesy of Pete Souza and Quote from the White House
    • Image Courtesy of Forbes and Quote from Discuss Diabetes Blog
    • “The basic idea behind the Health Data Initiative is to open up the vast data that HHS and other federal agencies have and to get it into the hands of innovators who can then use it as fuelto develop products and services that can improve health and healthcare.” Image Courtesy of Forbes and Quote from Discuss Diabetes Blog
    • “HealthData.gov is a one-stop resource where folks can access big data, which includes community data, health and healthcare performance data, provider directories,a health indicators warehouse with 1770 metrics of community health, healthcare determinants, such as smoking rates, access to healthy food, hospitals, and so on. We are constantly adding data sets and APIs.” Quote from Discuss Diabetes Blog
    • Community Health ProviderGovernment Directories Spending & Quality the “liberation” of healthcare data Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Community Health ProviderGovernment Directories Spending & Quality Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Community Health ProviderGovernment Directories Spending & Quality Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Community Health ProviderGovernment Directories Spending & Quality Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Community Health ProviderGovernment Directories Spending & Quality Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Community Health ProviderGovernment Directories Spending & Quality Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Community Health ProviderGovernment Directories Spending & Quality Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Community Health ProviderGovernment Directories Spending & Quality Medical / Scientific “Blue Button”Knowledge Consumer Product Information Adopted from the Slides of Todd Park
    • Clinical Quality Linked Data
    • CQLD Vocabulary
    • http://health.data.gov/doc/hospital/393303 HTTP 303 http://health.data.gov/id/hospital/393303 rdf:typehttp://health.data.gov/def/hospital/Hospital
    • http://health.data.gov/doc/hospital/393303
    • http://healthdata.gov/doc/hospital/393303
    • http://health.data.gov/sparql
    • http://healthdata.gov/sparqled
    • Blue Button Free Text Data----------------------------- DEMOGRAPHICS ----------------------------Source: Self-EnteredFirst Name: ONEMiddle Initial: ALast Name: MHVVETERANSuffix:Alias: MHVVETRelationship to VA: Patient, Veteran, EmployeeGender: Male Blood Type: AB+ Organ Donor: YesDate of Birth: 01 Mar 1948Marital Status: MarriedCurrent Occupation: Truck Driver Adopted from the GitHub Page of Blue Button Parser
    • Blue Button Parsed Data (JSON)"DEMOGRAPHICS": { "Source": "Self-Entered", "First Name": "ONE", "Middle Initial": "A", "Last Name": "MHVVETERAN", "Suffix": null, "Alias": "MHVVET", "Relationship to VA": "Patient, Veteran, Employee", "Gender": "Male", "Blood Type": "AB+", "Organ Donor": "Yes", "Date of Birth": "01 Mar 1948", "Marital Status": "Married", "Current Occupation": "Truck Driver"} Adopted from the GitHub Page of Blue Button Parser
    • SMART Data Model: Problem@prefix dcterms: <http://purl.org/dc/terms/> .@prefix sp: <http://smartplatforms.org/terms#> .@prefix spcode: <http://smartplatforms.org/terms/codes/> .<http://sandbox-api.smartplatforms.org/records/2169591/problems/961237> a sp:Problem; sp:belongsTo <http://sandbox-api.smartplatforms.org/records/2169591>; sp:endDate "2007-08-01"; sp:problemName [ a sp:CodedValue; dcterms:title "Backache (finding)"; sp:code <http://purl.bioontology.org/ontology/SNOMEDCT/161891005> ]; sp:startDate "2007-06-12" .<http://purl.bioontology.org/ontology/SNOMEDCT/161891005> a sp:Code, spcode:SNOMED; dcterms:identifier "161891005"; dcterms:title "Backache (finding)"; sp:system "http://purl.bioontology.org/ontology/SNOMEDCT/" . Adopted from the SMART Data Model Documentation
    • SMART Indivo Architecture SMART&API& Indivo&API& ! !Clinician ! SMART2 ! Clinician Clinician Indivo! Clinician2Facing! Clinician ! ! Indivo! 2Facing! Pa:ent2 2Facing! SMART! Connector! 2Facing! Apps! 2Facing! ! ! Apps! Facing! Apps! Container! App! Apps! Apps! ! ! Apps! ! ! ! ! ! ! ! ! Local!EHR! Image Courtesy of Chldrens Hospital Informaitcs Program
    • Original HTML<h1>New guidelines for metformin and diabetes mellitus</h1><p> Dr. John Smith<br> Medical University<br> 2012-03-24</p><p> <b>Abstract:</b> We review clinical evidence related to the use of metformin for treatment of type-2 diabetes mellitus and provide new clinical guideline recommendations.</p><p><b>MeSH subject headings:</b> Metformin; Diabetes Mellitus, Type 2</p>...<h3>Guidelines</h3>Recommendation: we recommend monotherapy with metformin as an initialpharmacologic therapy to treat most patients with type 2 diabetes(Grade: strong recommendation; high-quality evidence). Adopted from the schema.org Documentation
    • HTML with Microdata<div itemscope itemtype="http://schema.org/MedicalScholarlyArticle"> <link itemprop="audience" href="http://schema.org/Clinician"/> <meta itemprop="publicationType" content="Meta-Analysis"/> <h1><span itemprop="name">New guidelines for metformin and diabetes mellitus</span></h1> <p> <span itemprop="author" itemscope itemtype="http://schema.org/Person"> <span itemprop="name">Dr. John Smith</span> <br><span itemprop="affiliation">Medical University</span> </span> <br><span itemprop="datePublished">2012-03-24</span> <p><b>Abstract:</b> We review clinical evidence related to the use of metformin for treatment of type-2 diabetes mellitus and provide new clinical guideline recommendations.</p> ... Adopted from the schema.org Documentation
    • Thanks