Linked Data in Healthcare and Life Sciences

Linked Datain Healthcare

James G. Boram [email protected]

http://jayg.me/http://jayg.org/

foaf:mbox

foaf:homepage

owl:sameAs

dcterms:modi!ed 2013-03-05+09:00

and Life Sciences

IntroductionThe 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 andRationale document.

The group will:

Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies.Implement proof-of-concept demonstrations and industry-ready code.Document guidelines to accelerate the adoption of the technology.Disseminate information about the group's work at government, industry, academic events and by participating incommunity initiatives.

ParticipationCommunications of the HCLS IG are public. This includes public meeting records and access to the archives of the [email protected] mailing list.

The HCLS IG welcomes active participation from representatives of W3C Member organizations. If you are part of a W3CMember organization, please verify or create your W3C web account, then ask your Advisory Committe representative(member-only) to join the HCLS IG and nominate you to participate. More detailed instructions are available.

LINKSLINKS

Interest Group links:Group CharterPublic Wiki pageInstructions on joining the IGParticipants:

organizationspersons (member only link)

Mailing list archives

DOCUMENTSDOCUMENTS

Emerging practices for mapping andlinking life sciences data using RDF —A case seriesOntology of Rhetorical Blocks (ORB)Semantically enabling

SEMANTIC WEB HEALTH CARE AND LIFE SCIENCES (HCLS) INTEREST GROUPSEMANTIC WEB HEALTH CARE AND LIFE SCIENCES (HCLS) INTEREST GROUP

HOMEHOME


The group will:




LINKSLINKS




DOCUMENTSDOCUMENTS



HOMEHOME2005-2007 2008-2011 2011-2014

Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) Charter

Contents

1. Mission Statement

2. Scope

3. Duration

4. Deliverables

5. Relationship with Other Activities

6. Interest Group Participation

7. Meetings

8. Group Communications

9. Patent Disclosures

Mission Statement

The Semantic Web for Health Care and Life Sciences Interest Group (HCLSIG) is chartered to develop and support the use of Semantic Webtechnologies to improve collaboration, research and development, and innovation adoption in the of Health Care and Life Science domains. Success inthese domains depends on a foundation of semantically rich system, process and information interoperability. To these ends, the HCLSIG will focus onthe development of use cases that illustrate the business value of Semantic Web technology adoption, core vocabularies, guidelines and best practicesregarding unique identifiers, and provide a forum for supporting communication, education, collaboration and implementation. The HCLSIG will alsowork with the other Semantic Web related groups to gather suggestions for further HCLSIG development work. Further, the HCLSIG will provide aforum to support and encourage the use of Semantic Web technologies and foster the growth of interoperable, policy-aware data and databases in theLife Sciences and Health Care industries.

This work falls within the Technology and Society Domain and is part of W3C's Semantic Web Activity.

Scope

The HCLSIG is focused on the use of Semantic Web technologies to better enable interoperability and improve collaboration, research and development,innovation adoption, and data reusability in the health Care and life science domains. Sample areas of work designed to facilitate this goal include:

Core vocabularies: In order to stimulate cross-community data integration, collaborative efforts are required to define core vocabularies that canbridge data and ontologies developed by individual communities of practice in HCLS. It is expected these vocabularies will be expressed in RDF Schemaand / or OWL to maximize reuse among the community. Example vocabularies include but are not limited to:

provenance and context: identifying data (e.g. gene banks, protein databases, disease knowledge bases such as SNOMED CT, drug informationknowledge bases, templates for collecting clinical trial data, collections of rules bases comprising clinical decision support logic, etc.) sources,authors, publications names, and collection conditions in HCLS.

citation: vocabularies for supporting cross-references in publication and other reporting of experimental results in HCLS.

versioning: vocabularies for expressing change and relationships among changed resources (e.g. experimental data sets, clinical trials data sets,ontologies, etc.) in HCLS.

cross-mapping: bridging and/or merging of ontologies that could have either overlapping or orthogonal concepts.

Guidelines and Best Practices for Resource Identification: The Interest Group will provide guideline on how best to identify HCLS resources foruse in the Semantic Web. Implementation issues include:

referential integrity

resource identification for existing and future Semantic Web resources

version control

presence / absence of semantics

Scientific and Scholarly Publication: The Interest Group will provide guidelines, suggested best practices, and use of descriptive vocabularies tobetter enable the integration and relationships among people, data, observations, software, collections of algorithms, and scholarly publications / clinicaltrials.

Duration

The HCLSIG will be chartered for 2 years, beginning in September 2005.

Deliverables

The HCLSIG will provide a forum for supporting, guiding and collecting application and implementation experience, along with business and use casesassociated with using Semantic Web technologies to solve life science and health care problems. The discussion or tools, demonstrations, test suites,validation tools, and developer resources are all within scope of this interest group. More specifically:

Vocabularies that enable broad application of core Semantic Web technologies in Health Care and Life Sciences, for example: context, provenance,cross-reference, experimental reporting, versioning, and publication. Guidance for how best to express existing ontologies used by this domain interms of Semantic Web technologies are also in scope.

Implementations of vocabularies and recommendations for demonstration and use in Health Care and Life Sciences applications such as electronichealth record, clinical decision support, drug discovery, clinical trials and translation medicine.

Use cases, experience reports, guidelines, and best practices for deploying Semantic Web technologies within the Health Care and Life Sciences.

The convening of workshops and interop events to support the exchange of business cases, lessons learned, and applications / toolkits to furtherdemonstrate potential uses of Semantic Web technologies and capabilities to a broad audience of software developers and IT managers in theHealth Care and Life Science industries.

Meeting reports, documents and Interest Group minutes will be available from the public HCLSIG home page.

In order to meet the goal of delivering vocabularies and implementations within the time frame of this charter, the following draft milestones aredefined. A more detailed set of milestones and specific events will be available on the HCLSIG home page.

January 2006 - Interest Group F2F ; identification of specific tasks to focus on, corresponding task force leaders and expected deliverables.Suggested focus is on 4 month deliverables.

February 2006 - Publication of initial report on vocabularies and detailed working plan

April 2006 - Initial round of task force deliverables published.

May 2006 - Interest Group F2F ; Evaluate the status of existing task forces and target new ones accordingly.

July 2006 - new round of task force deliverables published.

August 2006 - Public Semantic Web / Health Care and Life Sciences Interoperability Workshop

October 2006 - Interest Group F2F ; Evaluate the status of existing task forces and target new ones accordingly.

Dec 2006 - new round of task force deliverables published.

Relationship with Other Activities

The HCLSIG will utilize W3C Semantic Web technologies where appropriate, and provide input back to such groups on use cases, experiences andcapabilities for consideration of future standards work (e.g. Rules) in this area. Where the HCLSIG community recognizes the development of broader,general best practices are required, the HCLSIG community will work with the SWBPD Working Group to communicate these requirements.

Cooperation with other groups that are exploring the use of Semantic Web technologies is also expected. These include, but are not limited to, HL7,AMIA, HIMSS, ONCHIT, National Centers for Biomedical Computing (NCBCs), caBIG, American Pathologists (CAP), National Library of Medicine, andother Life Sciences / Pharma industry groups such as those involved in BioPax, SBML, etc.

Interest Group Participation

W3C has created the HCLSIG to be an an open, sustainable forum. To help ensure that the deliverables identified in this charter are produced in atimely fashion and represent the needs of a variety of communities, we therefore seek both dedicated and broad participation. We anticipate thatdedicated individuals will enable the group to make timely progress, and that the diverse communities interested in the goals outlined by this charter --companies, universities, and organizations of various types -- will be represented in the group.

The HCLSIG therefore welcomes participation from representatives of W3C Member organizations. To enable a broad spectrum of input, the HCLSIGalso anticipates the active participation of individuals as W3C Invited Experts from universities and organizations. Participation from W3C Members andnon-Members alike will help ensure the goals of this charter are effectively addressed.

The W3C Team expects to dedicate the services of one staff member to serve 50% of his / her time as staff contact for the HCLSIG to facilitatediscussion as well as in the publication of notes and help with the liaison to related W3C efforts.

Meetings

The HCLSIG is expected to hold weekly conference calls, and two or three face-to-face meetings. In addition, much of the work of this Interest Groupwill be done in task forces, which may hold additional conference calls or face-to-face meetings. An up-to-date schedule is kept on the public HCLSIGInterest Group homepage.

Task forces may additionally be responsible for identifying use cases and requirements for future Working Groups. The relevant Interest Group Notes assuch would be considered as input into such work. These requirements are expected to be communicated to the Semantic Web Coordination Group forconsideration of chartering new Working Groups in this area.

Group Communications

Communications of the HCLSIG will be public. This includes a public home page that records the history of the group and provides access to [email protected] mailing list, ( discussion archives, meeting minutes, updated schedule of deliverables, membership list, and relevant documentsand resources).

For W3C Invited Experts, access to W3C Member-only information will not be required for participation in this Interest Group.

Patent Disclosures

The HCLS Interest Group provides an opportunity to share perspectives on Semantic Web technologies to improve collaboration, research anddevelopment, and innovation adoption in the of Health Care and Life Science domains. W3C reminds Interest Group participants of their obligation tocomply with patent disclosure obligations as set out in Section 6 of the W3C Patent Policy. While the Interest Group does not produce Recommendation-track documents, when Interest Group participants review Recommendation-track specifications from Working Groups, the patent disclosure obligationsdo apply.

Eric Miller <[email protected]>, (W3C) Semantic Web Activity Lead$Id: charter.html,v 1.12 2005/11/29 18:06:02 em Exp $

ScopeMotivationsDeliverablesDependenciesParticipationCommunicationDecision PolicyPatent DisclosuresAbout this Charter

This charter is now expired; please see the next HCLS IG charter.

Semantic Web Health Care and Life Sciences Interest GroupCharterThe mission of the Semantic Web Health Care and Life Sciences Interest Group, part of the Semantic Web Activity, is to develop,advocate for, and support the use of Semantic Web technologies for health care and life science, with focus on biological science andtranslational medicine. These domains stand to gain tremendous benefit by adoption of Semantic Web technologies, as they dependon the interoperability of information from many domains and processes for efficient decision support.

The group will:

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.Implement a selection of the use cases as proof-of-concept demonstrations.Explore the possibility of developing high level vocabularies.Disseminate information about the group's work at government, industry, and academic events.

Join the Semantic Web Health Care and Life Sciences Interest Group.

End date 31 May 2011Confidentiality Proceedings are PublicInitial Chairs Susie Stephens, Chimezi Ogbuji, M. Scott MarshallInitial Team Contacts(FTE %: 60) Eric Prud'hommeaux

Usual Meeting Schedule Teleconferences: Weekly Face-to-face: at least one per year

1. ScopeThe HCLSIG will provide a forum for supporting, guiding and collecting application and implementation experience. It will develop and support Semantic Webtechnologies in the three focus areas: life science, translational medicine, and health care. Within these areas, it will address use cases that have clearscientific, business, and/or technical value. HCLSIG will solicit advice on technical matters from other Semantic Web related groups within W3C and givefeedback 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 whichwe 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:

Discuss the relevance and maturity of tools.Create vocabulary guidelines.Build demonstrations and test suites.Create collateral within the scope of this interest group.

1.1 Success Criteria

Increased consensus around vocabulary choice and use of terminology spanning patient records and clinical research.Development of consensus around core taxonomies and methodologies for representing knowledge in Life Science, Translational Medicine and HealthCare.Adoption of these taxonomies and methodologies by standards organizations that are focused on life science and health care leading to increasedunderstanding and adoption of Semantic Web technologies.Presentation of these taxonomies and methodologies to government, academia and industry organizations that have a keen interest in the application ofinformation technology to these domains, and support of their efforts to adopt Semantic Web technologies.

2. Motivations

2.1 Biological Science

An understanding of the fundamental underlying principles of biology forms the basis on which all biomedical research relies. Biological research investigatesphenomena at a range of scales: molecules, cells, cell populations, tissues, organs, organisms, populations, and ecosystems and employs an astoundingvariety of experimental techniques, instruments and reagents. This research (e.g. gene expression, phenotypes, chemical screening, ...) generates data andconclusions from which new hypotheses are drawn which subsequently propel new studies at an ever increasing rate. The resulting proliferation of isolateddatabases hampers efforts to combine results.

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 rapidlyaccumulating knowledge. HCLSIG activities in the this area will include working with key data repositories towards their semantic integration by advocating forand assisting labs, database creators and publishers who would make information accessible using Semantic Web technologies. The group will applyontologies to the integration of heterogeneous data, show how common analysis tools can use data from and publish to the Semantic Web, and explore otherways that Semantic Web technologies might further facilitate this scientific work.

2.2 Translational Medicine

Recent advances in biological understanding are allowing pharmaceutical companies to begin to develop tailored therapeutics, thereby allowing patients toreceive 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 linkdata from the laboratory to the clinic (bench to bedside). This concept is frequently referred to as translational medicine.

This HCLSIG activity will provide resources that demonstrate the value of Semantic Web technologies to translational medicine. Activities in this area will focuson connecting pre-clinical and clinical trial data with clinical decision support knowledge in order to assess drug efficacy and safety. Examples of potentialactivities include the integration of health outcome data for identification of safety signals, aggregation of clinical trials data for identification of studies ofinterest, demonstration of the minimal costs required for the integration of unforeseen data sets into an existing data model to enable answering unanticipatedscientific questions, and the creation of dashboards that show how heterogeneous and disparate data can be integrated to aid decision making.

2.3 Health Care

Within the larger domain of health care there has been a dramatic increase in the demand for information systems that capture expressive clinical data, hostrich clinical knowledge, and are able to deliver robust decision support on behalf of healthcare quality improvement and clinical research. This HCLSIG activitywill 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 thecollection of data for the purpose of both primary care (electronic medical records) and clinical research (patient recruitment, study management, outcomes-based longitudinal analysis, etc.).

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 theacquisition and exchange of medical data led by standard bodies such as the CDISC, Health Level Seven (HL7) and BRIDG, enabling the use of thesestandards with Semantic Web technologies. Second, it will collaborate with efforts focused on building formal ontologies for clinical medicine and investigationsexpressed in Semantic Web languages such as OWL and RDFS. Finally, it will explore enabling interoperability through the documentation of mappingsbetween terminologies.

Another topic of interest is building innovative clinical decision support capabilities into patient record systems. Our task in this area is to identify best practicesfor clinical guideline representation in such a way that standards-based reasoning systems and knowledge sources can be leveraged in these patient recordsystems.

3. DeliverablesImplementation and demonstrations of one or two use cases in each of the three focus areas.Technical collateral including tutorials, experience reports, and guidelines.Business level communications and literature for use in liaison activities, to be updated biannually.Organization of at least one international workshop each year, to exchange knowledge on deployed systems, interesting use cases, lessons learned, anddemos built.Presentations, by members, of aspects of the group's activities at three to five relevant conferences or workshops each year.

4. Dependencies

4.1 W3C Groups

The OWL Working Groupto share feedback on the use of OWL in the proof of concept work

Rule Interchange Format (RIF) Working Groupto share feedback and solicit technical advice on the use of rules in the proof of concept work

4.2 External Groups

American Medical Information Association (AMIA)which has working groups that serve as a mechanism to exchange information on topical areas of biomedical and health informatics.

Clinical Data Interchange Standards Consortium (CDISC)which has the goal to develop and support global, platform-independent data standards that enable information system interoperability to improve medicala research and related areas of healthcare.

Health Information and Management Systems Society (HIMSS)which is focused on providing leadership for the optimal use of health information technology and management systems for the betterment of healthcare.

Health Level 7 (HL7)which develops standards for electronic interchange of clinical, financial, and administrative information among healthcare oriented computer systems.

International Health Terminology Standards Development Organizationwhich has the goal to develop, maintain, promote and enable the uptake and correct use of its terminology products in health systems, services andproducts around the world.

National Centers for Biomedical Ontology (NCBO)which is a consortium that develops innovative technology and methods that allow scientists to create, disseminate, and manage biomedical informationand knowledge in a machine readable form.

Office of the National Coordinator for Health Information Technology (ONCHIT)which allows comprehensive management of medical information and its secure exchange between health care consumers and providers

Open Biomedical Ontologies Foundrya collaborative effort to design science-based ontologies and principles for ontology development.

Coordination with other W3C groups will be managed through the Semantic Web Coordination Group. Given the importance of interaction with outside groups,the HCLSIG will have designated liasons to manage critical relationships, to be on the lookout for other organizations that we might work with — both within andoutside North America — and to provide advise and support for additional liason opportunities within the group.

The HCLSIG may identify and build support for additional Working Groups. The preparation for these groups, typically in the form of an interest group note, listof requirements, or draft charter, will be communicated to the Semantic Web Coordination Group for consideration.

5. ParticipationParticipation in the Semantic Web Health Care and Life Sciences Interest Group is open to the public. Any person interested in this topic is welcome toparticipate in this Interest Group. Individuals who wish to participate as Invited Experts (i.e., they do not represent a W3C Member) should refer to the policy forapproval of Invited Experts. Invited Experts in this group are not granted access to Member-only information.

There are no minimum requirements for participation in this group. Participants are strongly encouraged to take advantage of frequent opportunities to reviewand comment on deliverables from other groups.

The Chair may call occasional meetings consistent with the W3C Process requirements for meetings.

6. CommunicationThis group primarily conducts its work on the Public mailing list [email protected] (archive). As appropriate, other public mailing lists may becreated for more targeted discussions. Records of the history of the group, meeting minutes, an updated schedule of deliverables, membership list, andrelevant documents and resources will be maintained on the public HCLSIG Wiki.

Information about the group (deliverables, participants, face-to-face meetings, teleconferences, etc.) is available from the Semantic Web Health Care and LifeSciences Interest Group home page.

7. Decision PolicyAs explained in the Process Document (section 3.3), this group will seek to make decisions when there is consensus. When the Chair puts a question andobserves dissent, after due consideration of different opinions, the Chair should record a decision (possibly after a formal vote) and any objections, and moveon.

This charter is written in accordance with Section 3.4, Votes of the W3C Process Document and includes no voting procedures beyond what the ProcessDocument requires.

8. Patent DisclosuresThe Semantic Web Health Care and Life Sciences Interest Group provides an opportunity to share perspectives on the topic addressed by this charter. W3Creminds Interest Group participants of their obligation to comply with patent disclosure obligations as set out in Section 6 of the W3C Patent Policy. While theInterest Group does not produce Recommendation-track documents, when Interest Group participants review Recommendation-track specifications fromWorking Groups, the patent disclosure obligations do apply.

For more information about disclosure obligations for this group, please see the W3C Patent Policy Implementation.

9. About this CharterThis charter for the Semantic Web Health Care and Life Sciences Interest Group has been created according to section 6.2 of the Process Document. In theevent of a conflict between this document or the provisions of any charter and the W3C Process, the W3C Process shall take precedence.

Please also see the previous charter for this group. This charter has been produced from contributions by the current interest group, in particular, TonyaHongsermeier, Eric Neumann, Chimezi Ogbuji, Alan Ruttenberg and Susie Stephens.

Eric Prud'hommeaux

Copyright© 2008 W3C ® (MIT , ERCIM , Keio), All Rights Reserved.

$Date: 2011/09/06 16:37:59 $

- life sciences- health care

- pharmaceuticals


Semantic Web Health Care and Life Sciences Interest GroupCharterThe mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, and supportthe use of Semantic Web technologies across health care, life sciences, clinical research and translational medicine. These domainsstand to gain tremendous benefit from intra- and inter-domain application of Semantic Web technologies as they depend on theinteroperability of information from many disciplines. Please see the accompanying Use Cases and Rationale document.

The group will:

Continue to develop high level (e.g. TMO) and architectural (e.g. SWAN) vocabularies.Implement proof-of-concept demonstrations and industry-ready code.Document guidelines to accelerate the adoption of the technology.Disseminate information about the group's work at government, industry, academic events and by participating in community initiatives.


End date 31 Aug 2014Confidentiality Proceedings are Public

ChairsMichel Dumontier (Carleton University) Charles Mead (NCI CBIIT) Vijay Bulusu (Pfizer) Chair assignments will be reviewed every 18 months.

Initial Team Contacts(FTE %: 50) Eric Prud'hommeaux

Usual Meeting Schedule Teleconferences: WeeklyFace-to-face: at most once per year

1. ScopeThe HCLS IG will continue to provide a forum for supporting, developing and applying Semantic Web technologies across healthcare, life sciences, clinicalresearch and the continuum of translational medicine. Within these contexts, the HCLS IG will focus on the use of Semantic Web technologies to realizespecific use cases which themselves have a specific clinical, research of business values. As use cases are developed, HCLS IG will solicit advice on technicalmatters 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 focuson developing ongoing and mutually productive liaisons with relevant external organizations in healthcare, life sciences, and clinical research, includingorganizations that are actively working on relevant standards and/or implementations to which the HCLS’s work might contribute. In some cases, work startedin 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 Linked Data and guidelines to help others create Linked Data.Create vocabularies and vocabulary bridges.Build demonstrations and test suites.Assist other groups to create data and tools within the scope of this interest group.Advise industry on the relevance and maturity of tools.


Building on the successes of the last edition of the HCLS IG, the group will continue with a refinement of earlier criteria:

Development of consensus around core taxonomies and methodologies for representing knowledge in Life Science, Translational Medicine and HealthCare.Increased consensus around vocabulary choice and use of terminology spanning patient records and clinical research.Adoption of these taxonomies and methodologies by standards organizations that are focused on life science and health care leading to increasedunderstanding and adoption of Semantic Web technologies.Presentation of these taxonomies and methodologies to government, academia and industry organizations that have a keen interest in the application ofinformation 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.Development of policy and access control enabling proprietary Linked Data complementing the public Linked Data to be exchanged in limitedpartnerships.Strategies for defining and reasoning at run-time at service interfaces, enabling "semantically-aware" workflows to sold business problems.

2. MotivationsThe 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 theirapplication to translational medicine.



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 rapidlyaccumulating knowledge. HCLS IG activities in the this area will include working with key data repositories towards their semantic integration by advocating forand assisting labs, database creators and publishers who would make information accessible using Semantic Web technologies. The group will applyontologies to the integration of heterogeneous data, show how common analysis tools can use data from and publish to the Semantic Web, and explore otherways that Semantic Web technologies might further facilitate this scientific work. The IG will also adapt ontologies to meet the needs for evolving biological andevidence models imposed by new techniques and instruments such as next-gen sequencing.

2.2 Health Care

Pharmaceutical companies and individual patients, exploiting advances in translational medicine and informational infrastructure, are joining clinical interests inrecording detailed patient records. As governments and patient advocacy groups demand improved performance from electronic patient records, such asresearch or clinical decision support, clinicians, pharmaceutical companies and individuals with versatile semantic infrastructure will benefit from health caredata which is easy to integrate with genomics, bio-informatics, chem-informatics and environmental data. This HCLS IG activity will focus on applying thestrengths 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 thepurpose of both primary care (electronic medical records) and clinical research (patient recruitment, study management, outcomes-based longitudinal analysis,etc.). Enabling semantic interoperability across organizational and jurisdictional boundaries through sharing and linking of such data is an important part of thisgoal.




As research exposes more associations between genetics and medication outcomes, translational models are needed to allow health workers and researchersto access this information. 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, companiesneed 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.

This HCLS IG activity will provide resources that demonstrate the value of Semantic Web technologies to translational medicine. Activities in this area will focuson connecting pre-clinical and clinical trial data with clinical decision support knowledge in order to assess drug efficacy and safety. Examples of potentialactivities include the integration of health outcome data for identification of safety signals, aggregation of clinical trials data for identification of studies ofinterest, demonstration of the minimal costs required for the integration of unforeseen data sets into an existing data model to enable answering unanticipatedscientific questions, and the creation of dashboards that show how heterogeneous and disparate data can be integrated to aid decision making.

3. DeliverablesImplementation and demonstrations of one or two use cases in each of the three focus areas.Technical collateral including tutorials, experience reports, and guidelines.Business level communications and literature for use in liaison activities.Organization of at least one international workshop each year, to exchange knowledge on deployed systems, interesting use cases, lessons learned, anddemos built.Presentations, by members, of aspects of the group's activities at three to five relevant conferences or workshops each year.

4. Dependencies

4.1 W3C Groups

The SPARQL Working GroupThe HCLS IG will share query and update requirements and implementation experience.

The RDF Working GroupThe HCLS IG will share practical coding heuristics about deployed life sciences or health care data.

The Provenance Working GroupThe HCLS IG will prepare use cases and seek guidance in merging the myriad of provenance taxonomies and conventions already present in lifesciences. Health care use cases will help the provenance WG meet the needs around legitimate use and chain of custody of medical records.

The RDB2RDF Working GroupThe HCLS IG will share database access requirements and implementation experience.

4.2 External Groups


Clinical Data Interchange Standards Consortium (CDISC)which has the goal to develop and support global, platform-independent data standards that enable information system interoperability to improve medicalresearch and related areas of healthcare.


Health Level 7 (HL7)which develops standards for electronic interchange of clinical, financial, and administrative information among health care-oriented computer systems.


National Center for Biomedical Ontology (NCBO)which is a consortium that develops innovative technology and methods that allow scientists to create, disseminate, and manage biomedical informationand knowledge in a machine readable form.



Coordination with other W3C groups will be managed through the Semantic Web Coordination Group. Given the importance of interaction with outside groups,the HCLS IG will have designated liaisons to manage critical relationships, to be on the lookout for other organizations that we might work with — both withinand outside North America — and to provide advise and support for additional liaison opportunities within the group.

The HCLS IG may identify and build support for additional Working Groups. The preparation for these groups, typically in the form of an interest group note, listof requirements, or draft charter, will be communicated to the Semantic Web Coordination Group for consideration.

5. ParticipationParticipation in the Semantic Web Health Care and Life Sciences Interest Group mailing list is open to the public. W3C Members (and Invited Experts) areinvited to participate in HCLS IG projects. Individuals who wish to participate as Invited Experts (i.e., they do not represent a W3C Member) should refer to thepolicy for approval of Invited Experts. Invited Experts in this group are not granted access to Member-only information.



6. CommunicationThis group primarily conducts its work on the Public mailing list [email protected] (archive). As appropriate, other public mailing lists may becreated for more targeted discussions. Records of the history of the group, meeting minutes, an updated schedule of deliverables, membership list, andrelevant documents and resources will be maintained on the public HCLS IG Wiki.






9. About this CharterThis charter for the Semantic Web Health Care and Life Sciences Interest Group, part of the Semantic Web Activity, has been created according to section 6.2of the Process Document. In the event of a conflict between this document or the provisions of any charter and the W3C Process, the W3C Process shall takeprecedence.

Please also see the previous charter for this group.

Eric Prud'hommeaux


$Date: 2011/10/18 02:29:28 $


The group will:




LINKSLINKS




DOCUMENTSDOCUMENTS



HOMEHOME

2005-2007 2008-2011 2011-2014


Contents


2. Scope

3. Duration

4. Deliverables



7. Meetings



Mission Statement



Scope










version control



Duration


Deliverables























Meetings






Patent Disclosures






The group will:









2. Motivations







2.3 Health Care





4. Dependencies

4.1 W3C Groups



4.2 External Groups






















Eric Prud'hommeaux


$Date: 2011/09/06 16:37:59 $


- pharmaceuticals



The group will:
















2.2 Health Care








4. Dependencies

4.1 W3C Groups





4.2 External Groups






















Eric Prud'hommeaux


$Date: 2011/10/18 02:29:28 $

“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 Health Care and Life Science domains.”


The group will:




LINKSLINKS




DOCUMENTSDOCUMENTS



HOMEHOME

2005-2007 2008-2011 2011-2014


Contents


2. Scope

3. Duration

4. Deliverables



7. Meetings



Mission Statement



Scope










version control



Duration


Deliverables























Meetings






Patent Disclosures






The group will:









2. Motivations







2.3 Health Care





4. Dependencies

4.1 W3C Groups



4.2 External Groups






















Eric Prud'hommeaux


$Date: 2011/09/06 16:37:59 $


- pharmaceuticals



The group will:
















2.2 Health Care








4. Dependencies

4.1 W3C Groups





4.2 External Groups






















Eric Prud'hommeaux


$Date: 2011/10/18 02:29:28 $

“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 support the use of Semantic Web technologies for health care and life science,

with focus on biological science and translational medicine.”


The group will:




LINKSLINKS




DOCUMENTSDOCUMENTS



HOMEHOME

2005-2007 2008-2011 2011-2014


Contents


2. Scope

3. Duration

4. Deliverables



7. Meetings



Mission Statement



Scope










version control



Duration


Deliverables























Meetings






Patent Disclosures






The group will:









2. Motivations







2.3 Health Care





4. Dependencies

4.1 W3C Groups



4.2 External Groups






















Eric Prud'hommeaux


$Date: 2011/09/06 16:37:59 $


- pharmaceuticals



The group will:
















2.2 Health Care








4. Dependencies

4.1 W3C Groups





4.2 External Groups






















Eric Prud'hommeaux


$Date: 2011/10/18 02:29:28 $

“The mission of the Semantic Web Health Care and Life Sciences Interest Group (HCLS IG) is to develop, advocate for, and support the use of Semantic Web technologies across health care, life sciences, clinical research and

translational medicine.”

As of September 2011

MusicBrainz

(zitgist)

P20

Turismo de

Zaragoza

yovisto

Yahoo! Geo

Planet

YAGO

World Fact-book

El ViajeroTourism

WordNet (W3C)

WordNet (VUA)

VIVO UF

VIVO Indiana

VIVO Cornell

VIAF

URIBurner

Sussex Reading

Lists

Plymouth Reading

Lists

UniRef

UniProt

UMBEL

UK Post-codes

legislationdata.gov.uk

Uberblic

UB Mann-heim

TWC LOGD

Twarql

transportdata.gov.

uk

Traffic Scotland

theses.fr

Thesau-rus W

totl.net

Tele-graphis

TCMGeneDIT

TaxonConcept

Open Library (Talis)

tags2con delicious

t4gminfo

Swedish Open

Cultural Heritage

Surge Radio

Sudoc

STW

RAMEAU SH

statisticsdata.gov.

uk

St. Andrews Resource

Lists

ECS South-ampton EPrints

SSW Thesaur

us

SmartLink

Slideshare2RDF

semanticweb.org

SemanticTweet

Semantic XBRL

SWDog Food

Source Code Ecosystem Linked Data

US SEC (rdfabout)

Sears

Scotland Geo-

graphy

ScotlandPupils &Exams

Scholaro-meter

WordNet (RKB

Explorer)

Wiki

UN/LOCODE

Ulm

ECS (RKB

Explorer)

Roma

RISKS

RESEX

RAE2001

Pisa

OS

OAI

NSF

New-castle

LAASKISTI

JISC

IRIT

IEEE

IBM

Eurécom

ERA

ePrints dotAC

DEPLOY

DBLP (RKB

Explorer)

Crime Reports

UK

Course-ware

CORDIS (RKB

Explorer)CiteSeer

Budapest

ACM

riese

Revyu

researchdata.gov.

ukRen. Energy Genera-

tors

referencedata.gov.

uk

Recht-spraak.

nl

RDFohloh

Last.FM (rdfize)

RDF Book

Mashup

Rådata nå!

PSH

Product Types

Ontology

ProductDB

PBAC

Poké-pédia

patentsdata.go

v.uk

OxPoints

Ord-nance Survey

Openly Local

Open Library

OpenCyc

Open Corpo-rates

OpenCalais

OpenEI

Open Election

Data Project

OpenData

Thesau-rus

Ontos News Portal

OGOLOD

JanusAMP

Ocean Drilling Codices

New York

Times

NVD

ntnusc

NTU Resource

Lists

Norwe-gian

MeSH

NDL subjects

ndlna

myExperi-ment

Italian Museums

medu-cator

MARC Codes List

Man-chester Reading

Lists

Lotico

Weather Stations

London Gazette

LOIUS

Linked Open Colors

lobidResources

lobidOrgani-sations

LEM

LinkedMDB

LinkedLCCN

LinkedGeoData

LinkedCT

LinkedUser

FeedbackLOV

Linked Open

Numbers

LODE

Eurostat (OntologyCentral)

Linked EDGAR

(OntologyCentral)

Linked Crunch-

base

lingvoj

Lichfield Spen-ding

LIBRIS

Lexvo

LCSH

DBLP (L3S)

Linked Sensor Data (Kno.e.sis)

Klapp-stuhl-club

Good-win

Family

National Radio-activity

JP

Jamendo (DBtune)

Italian public

schools

ISTAT Immi-gration

iServe

IdRef Sudoc

NSZL Catalog

Hellenic PD

Hellenic FBD

PiedmontAccomo-dations

GovTrack

GovWILD

GoogleArt

wrapper

gnoss

GESIS

GeoWordNet

GeoSpecies

GeoNames

GeoLinkedData

GEMET

GTAA

STITCH

SIDER

Project Guten-berg

MediCare

Euro-stat

(FUB)

EURES

DrugBank

Disea-some

DBLP (FU

Berlin)

DailyMed

CORDIS(FUB)

Freebase

flickr wrappr

Fishes of Texas

Finnish Munici-palities

ChEMBL

FanHubz

EventMedia

EUTC Produc-

tions

Eurostat

Europeana

EUNIS

EU Insti-

tutions

ESD stan-dards

EARTh

Enipedia

Popula-tion (En-AKTing)

NHS(En-

AKTing) Mortality(En-

AKTing)

Energy (En-

AKTing)

Crime(En-

AKTing)

CO2 Emission

(En-AKTing)

EEA

SISVU

education.data.g

ov.uk

ECS South-ampton

ECCO-TCP

GND

Didactalia

DDC Deutsche Bio-

graphie

datadcs

MusicBrainz

(DBTune)

Magna-tune

John Peel

(DBTune)

Classical (DB

Tune)

AudioScrobbler (DBTune)

Last.FM artists

(DBTune)

DBTropes

Portu-guese

DBpedia

dbpedia lite

Greek DBpedia

DBpedia

data-open-ac-uk

SMCJournals

Pokedex

Airports

NASA (Data Incu-bator)

MusicBrainz(Data

Incubator)

Moseley Folk

Metoffice Weather Forecasts

Discogs (Data

Incubator)

Climbing

data.gov.uk intervals

Data Gov.ie

databnf.fr

Cornetto

reegle

Chronic-ling

America

Chem2Bio2RDF

Calames

businessdata.gov.

uk

Bricklink

Brazilian Poli-

ticians

BNB

UniSTS

UniPathway

UniParc

Taxonomy

UniProt(Bio2RDF)

SGD

Reactome

PubMedPub

Chem

PRO-SITE

ProDom

Pfam

PDB

OMIMMGI

KEGG Reaction

KEGG Pathway

KEGG Glycan

KEGG Enzyme

KEGG Drug

KEGG Com-pound

InterPro

HomoloGene

HGNC

Gene Ontology

GeneID

Affy-metrix

bible ontology

BibBase

FTS

BBC Wildlife Finder

BBC Program

mes BBC Music

Alpine Ski

Austria

LOCAH

Amster-dam

Museum

AGROVOC

AEMET

US Census (rdfabout)

Media

Geographic

Publications

Government

Cross-domain

Life sciences

User-generated content

Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/

Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/

MusicBrainz

(zitgist)

P20

Turismo de

Zaragoza

yovisto

Yahoo! Geo

Planet

YAGO

World Fact-book

El ViajeroTourism

WordNet (W3C)

WordNet (VUA)

VIVO UF

VIVO Indiana

VIVO Cornell

VIAF

URIBurner

Sussex Reading

Lists

Plymouth Reading

Lists

UniRef

UniProt

UMBEL

UK Post-codes

legislationdata.gov.uk

Uberblic

UB Mann-heim

TWC LOGD

Twarql

transportdata.gov.

uk

Traffic Scotland

theses.fr

Thesau-rus W

totl.net

Tele-graphis

TCMGeneDIT

TaxonConcept

Open Library (Talis)

tags2con delicious

t4gminfo

Swedish Open

Cultural Heritage

Surge Radio

Sudoc

STW

RAMEAU SH

statisticsdata.gov.

uk

St. Andrews Resource

Lists

ECS South-ampton EPrints

SSW Thesaur

us

SmartLink

Slideshare2RDF

semanticweb.org

SemanticTweet

Semantic XBRL

SWDog Food

Source Code Ecosystem Linked Data

US SEC (rdfabout)

Sears

Scotland Geo-

graphy

ScotlandPupils &Exams

Scholaro-meter

WordNet (RKB

Explorer)

Wiki

UN/LOCODE

Ulm

ECS (RKB

Explorer)

Roma

RISKS

RESEX

RAE2001

Pisa

OS

OAI

NSF

New-castle

LAASKISTI

JISC

IRIT

IEEE

IBM

Eurécom

ERA

ePrints dotAC

DEPLOY

DBLP (RKB

Explorer)

Crime Reports

UK

Course-ware

CORDIS (RKB

Explorer)CiteSeer

Budapest

ACM

riese

Revyu

researchdata.gov.

ukRen. Energy Genera-

tors

referencedata.gov.

uk

Recht-spraak.

nl

RDFohloh

Last.FM (rdfize)

RDF Book

Mashup

Rådata nå!

PSH

Product Types

Ontology

ProductDB

PBAC

Poké-pédia

patentsdata.go

v.uk

OxPoints

Ord-nance Survey

Openly Local

Open Library

OpenCyc

Open Corpo-rates

OpenCalais

OpenEI

Open Election

Data Project

OpenData

Thesau-rus

Ontos News Portal

OGOLOD

JanusAMP

Ocean Drilling Codices

New York

Times

NVD

ntnusc

NTU Resource

Lists

Norwe-gian

MeSH

NDL subjects

ndlna

myExperi-ment

Italian Museums

medu-cator

MARC Codes List

Man-chester Reading

Lists

Lotico

Weather Stations

London Gazette

LOIUS

Linked Open Colors

lobidResources

lobidOrgani-sations

LEM

LinkedMDB

LinkedLCCN

LinkedGeoData

LinkedCT

LinkedUser

FeedbackLOV

Linked Open

Numbers

LODE

Eurostat (OntologyCentral)

Linked EDGAR

(OntologyCentral)

Linked Crunch-

base

lingvoj

Lichfield Spen-ding

LIBRIS

Lexvo

LCSH

DBLP (L3S)

Linked Sensor Data (Kno.e.sis)

Klapp-stuhl-club

Good-win

Family

National Radio-activity

JP

Jamendo (DBtune)

Italian public

schools

ISTAT Immi-gration

iServe

IdRef Sudoc

NSZL Catalog

Hellenic PD

Hellenic FBD

PiedmontAccomo-dations

GovTrack

GovWILD

GoogleArt

wrapper

gnoss

GESIS

GeoWordNet

GeoSpecies

GeoNames

GeoLinkedData

GEMET

GTAA

STITCH

SIDER

Project Guten-berg

MediCare

Euro-stat

(FUB)

EURES

DrugBank

Disea-some

DBLP (FU

Berlin)

DailyMed

CORDIS(FUB)

Freebase

flickr wrappr

Fishes of Texas

Finnish Munici-palities

ChEMBL

FanHubz

EventMedia

EUTC Produc-

tions

Eurostat

Europeana

EUNIS

EU Insti-

tutions

ESD stan-dards

EARTh

Enipedia

Popula-tion (En-AKTing)

NHS(En-

AKTing) Mortality(En-

AKTing)

Energy (En-

AKTing)

Crime(En-

AKTing)

CO2 Emission

(En-AKTing)

EEA

SISVU

education.data.g

ov.uk

ECS South-ampton

ECCO-TCP

GND

Didactalia

DDC Deutsche Bio-

graphie

datadcs

MusicBrainz

(DBTune)

Magna-tune

John Peel

(DBTune)

Classical (DB

Tune)

AudioScrobbler (DBTune)

Last.FM artists

(DBTune)

DBTropes

Portu-guese

DBpedia

dbpedia lite

Greek DBpedia

DBpedia

data-open-ac-uk

SMCJournals

Pokedex

Airports

NASA (Data Incu-bator)

MusicBrainz(Data

Incubator)

Moseley Folk

Metoffice Weather Forecasts

Discogs (Data

Incubator)

Climbing

data.gov.uk intervals

Data Gov.ie

databnf.fr

Cornetto

reegle

Chronic-ling

America

Chem2Bio2RDF

Calames

businessdata.gov.

uk

Bricklink

Brazilian Poli-

ticians

BNB

UniSTS

UniPathway

UniParc

Taxonomy

UniProt(Bio2RDF)

SGD

Reactome

PubMedPub

Chem

PRO-SITE

ProDom

Pfam

PDB

OMIMMGI

KEGG Reaction

KEGG Pathway

KEGG Glycan

KEGG Enzyme

KEGG Drug

Com-pound

InterPro

HomoloGene

HGNC

Gene Ontology

GeneID

Affy-metrix

bible ontology

BibBase

FTS

BBC Wildlife Finder

BBC Program

mes BBC Music

Alpine Ski

Austria

LOCAH

Amster-dam

Museum

AGROVOC

AEMET

US Census (rdfabout)

As of September 2011

Media

Geographic

Publications

Government

Cross-domain

Life sciences

User-generated content

Image Courtesy of Umberto Salvagnin and Quote from W3C HCLS IG Charter

“An understanding of the fundamental underlying principles of biologyforms 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

Adopted from the Slides of Carole Goble, ISWC 2005

prediction

results

experiment

analysis

integration

mining

hypothesis

analysismining

integration

“Discovery increasingly done in silico on results obtainedfrom experiments using computational analysis and data repositories.”

According to the 2013 Nucleic Acids Research (NAR)online Molecular Biology Database Collection, 1512 public databases exist.

Adopted from Tim Berners-Lee’s Note on Linked Data. http://www.w3.org/DesignIssues/LinkedData.html

★ 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★★★★★

a framework to create and provide linked data for the life sciences

Adopted from the Slides of Michel Dumontier

Download

RDFization

URI Normalization

VirtuosoTriple Store

Services


Image Courtesy of Allan Baxter

Image Courtesy of Allan Baxter

The Banff Manifesto Rules of Thumb

URI's are normalized and dereferenceable.1

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.



When available, use the provider’s identifier in the naming the resource.

http://bio2rdf.org/namespace:identi!er

http://bio2rdf.org/drugbank:DB00650For example, the Bio2RDF URL for the DrugBank record with the identifier DB00650 would be:

Types and predicates that are generated to supportthe semantic annotation are in the vocabulary namespace.

http://bio2rdf.org/drugbank_vocabulary:Drug(type)

(predicate) http://bio2rdf.org/drugbank_vocabulary:target

Authoritative public namespaces are used.2


An initial registry of ~600 datasets is accessible through an API provided. It includes:

dataset title, preferred namespace pre!x, alternative namespace pre!xes

Authoritative public namespaces are used.2


In the last summer, Bio2RDF team consolidated and curated nearly 2,100 entriesin 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 havea single dataset registry that we can use for both Bio2RDF and identifiers.org

enable automatic cross-links between Bio2RDF and identi!ers.org

Mandatory predicates are used.3

Adopted from Bio2RDF RDFization Guide v1.1

Banff Manifesto RDF documents must contain at least the following predicates:

http://bio2rdf.org/drugbank:DB00650

http://bio2rdf.org/drugbank_vocabulary:Drug

rdf:type| the class of object described by the document





“drugbank:DB00650”

dc:identifier| a string that contains the identi!er using the following pattern <namespace>:<identi!er>





“Leucovorin”

dc:title| a human readable title as it appears in the source data





“Leucovorin [drugbank:DB00650]”

rdfs:label| a Bio2RDF generated label containing a title followed by the identi!er “title [namespace:identi!er]”

Blank nodes are forbidden.4


If in the process of converting a dataset to RDF you create new identifiersthat did not previously exist in the dataset being converted,

then use a namespace_resource namespace.


http://bio2rdf.org/drugbank_resource:DB00440_DB00650

drugbank_vocabulary:ddi-interactor-in

drugbank_vocabulary:Drug-Drug-Interaction

rdf:type

Blank nodes are forbidden.4


If in the process of converting a dataset to RDF you create new identifiersthat did not previously exist in the dataset being converted,

then use a namespace_resource namespace.


http://bio2rdf.org/drugbank_resource:DB00440_DB00650

drugbank_vocabulary:ddi-interactor-in

“DDI between Trimethoprim and Leucovorin [drugbank_resource:DB00440_DB00650]”

rdfs:label

RDFizer programs are open source.5

Dereferenceable ontologies.6

“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 ontologiesand 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.


Adopted from the Paper of Manuel Salvadores et al.

UMLS MySQL Release(RRF)

Protege-backend(Metadata)

BioPortal File Download Service(OWL and OBO)

UMLS2RDF

Protege-API

OWL-API(Import Closure)

Web

OWL and OBOImports

Triple Store(4store)

SPARQLOWL and OBOImport Materialized

Metadata

RRF/UMLS


Adopted from Manuel Salvadores et al.

“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 termwith the ID SHORT_ID in the ontology identified by a unique acronym ACR.”

drugbank:DB00650

drugbank_vocabulary:Drug

rdf:type

“Leucovorin [drugbank:DB00650]”rdfs:label

pharmgkb:PA450198


“leucovorin [pharmgkb:PA450198]”

pharmgkb_vocabulary:Drug

pharmgkb_vocabulary:xref

rdfs:label

rdf:type

What links to DrugBank’s Leucovorin?

http://bio2rdf.org/linksns/drugbank/drugbank:DB00650

SPARQL 1.1 Federated Query

SELECT ?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 . }}


Semantic Data Integration through RDF Warehousing

Image Courtesy of Ontotext

Six Linked Data Integration Patterns

Image Courtesy of Ontotext

Applying Text Mining Technologiesto Link the Text with EntitiesSemantic Annotations

pmid:17714090

umls:C0035204

COPD

Bronchial Diseases

Respiration Disorders

umls:C0006261

Chronic Obstructive Airway Diseases

Asthma umls:C000496

Ian A Yang

Clinical and experimental pharmacology …

#29

Adopted from the Slides of Vassil Momtchev

SourcesRepository overview

Repository

ID: LLD 1.1

Description: Linked Life Data is a semantic data integration platform for the biomedical domain.

Number of statements: 8,740,201,002

Number of expl. statements: 5,918,290,955

Number of entities: 2,068,072,570

Data source Named graph Load date Statements Instances type

BioGRIDReference License

http://linkedlifedata.com/resource/biogrid 2012.07.20 14,327,672 biopax-2:entity

CellMapReference License

http://linkedlifedata.com/resource/cellmap 2012.07.20 154,863 biopax-2:biochemicalReaction

ChEBIReference License

http://linkedlifedata.com/resource/chebi 2012.07.20 323,220 skos:Concept

DailyMedReference License

http://linkedlifedata.com/resource/dailymed 2012.07.20 162,972 dailymed:drugs

DiseaseOntologyReference License

http://linkedlifedata.com/resource/diseaseontology 2012.07.20 90,652 skos:Concept

DiseasomeReference License

http://linkedlifedata.com/resource/diseasome 2012.07.20 72,445 diseasome:diseases

DrugBankReference License

http://linkedlifedata.com/resource/drugbank 2012.07.20 517,023 drugbank:drugs

FreebaseReference License

http://linkedlifedata.com/resource/freebase 2012.07.20 705,161,223

GeneOntologyReference License

http://linkedlifedata.com/resource/geneontology 2012.07.20 364,947 skos:Concept

HapMapReference License

http://linkedlifedata.com/resource/hapmap 2012.07.20 22,462,178 -

HPRDReference License

http://linkedlifedata.com/resource/hprd 2012.07.20 1,972,499 biopax-2:entity

HumanCYCReference License

http://linkedlifedata.com/resource/humancyc 2012.07.20 332,828 biopax-2:entity

HumanPhenotypeOntologyReference License

http://linkedlifedata.com/resource/phenotype 2012.07.20 62,240 skos:Concept

IMIDReference License

http://linkedlifedata.com/resource/imid 2012.07.20 117,675 biopax-2:entity

IntActReference License

http://linkedlifedata.com/resource/intact 2012.07.20 2,845,521 biopax-2:entity

LHGDNReference License

http://linkedlifedata.com/resource/lhgdn 2012.07.20 316,021 -

LinkedCTReference License

http://linkedlifedata.com/resource/linkedct 2012.07.20 9,804,652 linkedct:condition

MINTReference License

http://linkedlifedata.com/resource/mint 2012.07.20 17,249,403 biopax-2:entity

NCBI GeneReference License

http://linkedlifedata.com/resource/entrezgene 2012.07.20 186,904,730 entrezgene:Gene

NCI NatureReference License

http://linkedlifedata.com/resource/nci-nature 2012.07.20 914,442 biopax-2:entity

PubMedReference License

http://linkedlifedata.com/resource/pubmed 2012.07.20 1,454,405,726 pubmed:Citation

ReactomeReference License

http://linkedlifedata.com/resource/reactome 2012.07.20 1,082,499 biopax-2:entity

SIDERReference License

http://linkedlifedata.com/resource/sider 2012.07.20 101,542 sider:drugs

SymptomOntologyReference License

http://linkedlifedata.com/resource/symptom 2012.07.20 5,210 skos:Concept

UMLSReference License

http://linkedlifedata.com/resource/umls 2012.07.20 129,803,921 skos:Concept

UniProtReference License

http://linkedlifedata.com/resource/uniprot 2012.07.20 3,177,871,239 uniprot:Protein

Instance mappings

Source dataset Destination dataset Linked Data Mapping Rule Number of connections Semantic relationship

BioPax proteins NCBI-Gene genes Reference node 907 skos:closeMatch

BioPax proteins UniProt proteins Reference Node 1,220 skos:relatedMatch

Diseasome genes NCBI-Gene genes Reference Node 1,776 skos:relatedMatch

DrugBank targets UniProt proteins Namespace Mapping 4,660 skos:exactMatch

DrugBank targets NCBI-Gene genes Namespace Mapping 1,617 skos:relatedMatch

HGNC genes NCBI-Gene genes Namespace mapping 27,558 skos:exactMatch

HUGO citations PubMed citations Namespace Mapping 15,039 skos:relatedMatch

HUGO Genes UniProt proteins Namespace Mapping 18,996 skos:relatedMatch

LHGDN association UMLS concepts Namespace Mapping 63,148 lhgdn:umls_code

NCBI-Gene organisms UMLS organisms Mismatched Identifiers 6,720 skos:exactMatch

PubMed Mesh terms UMLS Mesh terms Value Dereference 25,969 skos:exactMatch

SIDER drugs UMLS drug records Namespace Mapping 1,684 skos:exactMatch

UniProt organisms UMLS organism records Value Dereference 634,181 skos:exactMatch

UniProt proteins UMLS protein records Reference Node 19,261 skos:exactMatch

Predicate mappings

Source dataset Destination dataset Linked Data Mapping Rule Number of connections Semantic relationship

Disclaimer: Part of the information in the Linked Life Data knowledge base is from copyrighted data sources.Linked Life Data is a prototype demonstration service and its users are solely responsible for compliance with any copyright restrictions. Report a copyright violation.

Linked Life Data is partly funded by the EU IST project LarKC (FP7-215535).© 2009-2012 Ontotext AD. All rights reserved.

Build Timestamp: 2012-09-11 16:19:42Build Revision: 2226

Home SPARQL RelFinder Co-occurrence Sources Conventions Download About Questions? Admin

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.

Image Courtesy of Anja Jentzsch et al.

LODD: Linked Open Drug Data

Image Courtesy of Mark Sharp et al.

Questions that LODD might Help to Answer:

Adopted from the Slides of Chistian Bizer

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?

ClinicalTrial.gov

LinkedCT.org

Adopted from the Paper of Oktie Hassanzadeh et al.

Source / Target Link Type Count

LinkedCT (intervention)↔ DBpedia (drug) owl:sameAs 11,527

LinkedCT (intervention)↔ DrugBank (drug) rdfs:seeAlso 23,493

LinkedCT (intervention)↔ DailyMed (drug) rdfs:seeAlso 39,396

LinkedCT (condition)↔ DBpedia (disease) owl:sameAs 342

LinkedCT (condition)↔ Diseasome (disease) owl:sameAs 830

LinkedCT (trial)↔ Geonames foaf:based_near 129,177

LinkedCT (reference)↔ Bio2RDF’s PubMed owl:sameAs 42,219

LinkedCT (trial)↔ ClinicalTrials.gov foaf:page 61,920

and all of their details remain in one profile. If the patient chooses to receive care ata hospital outside this network, as described above, only relevant details pertainingto their care are transferred. A new, abridged EHR is then re-created at each newinstitution, in much less detail, and is largely similar to the simulated patientsdesigned for TMO.Our records were, to a large extent, built upon the XML-based Indivo specification

for personally-controlled health care records. The Indivo initiative [35] offers simpleuser interfaces to store records and to grant others controlled access to them. Archiv-ing systems like i2b2’s database records and Indivo’s XML records can genericallyrecord data, such as test results, in tuples that include a coding system, a code, a tested

Table 4 Data sources used in this studyLODD Prefix Dataset Description

x linkedct Clinicaltrials.gov Registry of clinical trials

dubois AD diagnostic AD diagnostic criteria

x dailymed DailyMed Marketed & FDA approved drugs

x diseasome Diseasome The genetic basis of disease

x drugbank DrugBank Detailed drug data & drug target

x medicare Medicare Medicare D approved drugs

pchr Patient synthetic patient data

pharmgkb PharmGKB Drug response to genetic variation

x sider SIDER Side effects of marketed drugs

LODD – ‘x’ indicates a Linking Open Drug Data dataset

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 andterminologies listed in the NCBO BioPortal. The TMO provides a global schema for Indivo-based electronichealth records (EHRs) and can be used with formalized criteria for Alzheimer’s Disease. The TMO mapstypes from Linking Open Data sources.

Luciano et al. Journal of Biomedical Semantics 2011, 2(Suppl 2):S1http://www.jbiomedsem.com/content/2/S2/S1

Page 11 of 21

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 integratewith genomics, bio-informatics, chem-informatics and environmental data.”

Image Courtesy of Escape Fire

Image Courtesy of Pete Souza and Quote from the White House

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 Forbes and Quote from Discuss Diabetes Blog

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 fuel to develop products and services that can improve health and healthcare.”

“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

“Blue Button”

Consumer Product

Information

Medical / Scientific

Knowledge

Government Spending

the “liberation” of healthcare data

Provider Directories & Quality

Adopted from the Slides of Todd Park

Community Health

“Blue Button”

Consumer Product

Information

Medical / Scientific

Knowledge

Government Spending

Provider Directories & Quality

Adopted from the Slides of Todd Park

Clinical Quality Linked Data

CQLD Vocabulary

http://health.data.gov/id/hospital/393303

http://health.data.gov/def/hospital/Hospital

rdf:type

http://health.data.gov/doc/hospital/393303

HTTP 303

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-Entered

First Name: ONEMiddle Initial: ALast Name: MHVVETERANSuffix: Alias: MHVVETRelationship to VA: Patient, Veteran, Employee

Gender: Male Blood Type: AB+ Organ Donor: Yes

Date 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&API&!!!!!!!!!

SMART!Container!

Indivo&API&!!!!!!!!!

Indivo!SMART2Indivo!

Connector!App!

Clinician2Facing!Apps!





Pa:ent2Facing!Apps!

Local!EHR!

SMART Indivo Architecture

Image Courtesy of Chldren's 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

Linked Data in Healthcare and Life Sciences

Health & Medicine

Transcript of Linked Data in Healthcare and Life Sciences