EVS has enjoyed wide use and many collaborations within caBIG® and other organizations in the cancer research and biomedical community. The following are included in this profile:
- Topical Groupings
- LexEVS Adopter Community
- Common Biorepository Model (CBM)
- Human Studies Database (HSDB) Consortium
- Imaging Standards
- Georgetown University
- Mayo Clinic
- Ohio State University Medical Center
- Open Biomedical Ontologies (OBO)
- Stanford/National Center for Biomedical Ontology (NCBO)
- Stanford Tissue Microarray Database (TMAD)
- University of Pittsburgh
- Washington University
LexEVS Adopter Community
MD Anderson is using a local LexEVS server as part of their enterprise infrastructure. Special resources were dedicated to resolving initial software compatibility and other issues, ensuring a successful deployment. NCI EVS terminology browsers have also been deployed, as have NCIt and other EVS terminology resources. This is an example of leveraging a wide range of EVS resources and services in support of the research and clinical enterprise infrastructure of a leading cancer center.
Emory University is using LexEVS to develop and host local ontologies. Uses include terminology support for an analytic data warehouse, which incorporates custom patient classes defined using ICD-9 codes. This is an example of an academic medical center deploying and extending EVS components.
GE is developing a platform called Qualibria, which includes LexEVS as a terminology server. VKC has been working with GE since 2008. As part of the collaboration, GE created an extension to the LexEVS 5.1 API based on the Common Terminology Services specification. GE provided the code for that extension, which is now available to the community via the VKC web site. This is an example of NCI open source technology being bundled into a commercial healthcare product.
McGill University Health Center, Canada
McGill is connected to the TRANSFoRm project for European health care reform. LexEVS was chosen as the terminology server for the project, but a new loader is required in support of the ATC terminology. The VKC is currently working with them on the development of the ATC loader, which includes requirements gathering, coding, testing, and documentation. This represents an example where a project-specific use case provided by a customer is used as the basis for collaborative development of an open source contribution.
Seoul National University, Korea
The Biomedical Knowledge Engineering (BiKE) lab adopted the 2005 version of the LexGrid model and over the last several years created an entire terminology-based application suite on that model. The VKC is currently working with BiKE to finalize an agreement under which they would provide to us the source code for a terminology mapping UI that was developed as part of their project. This would be a potentially significant contribution, as it would add a new tool in an area with a known gap in the current functionality of LexEVS.
Nanotechnology, and more specifically nanomedicine, has become important in the development of reagents for cancer detection and treatment. NCI established Cancer Centers of Nanotechnology Excellence (CCNE) to support translational nanomedical research. EVS provides assistance in curating concept definitions with the community, making them available in NCIt; a glossary of these terms also is provided within the caNanoLab application (see below).
Nanotechnology Working Group
caBIG® has established a Nanotechnology Working Group as part of its Integrative Cancer Research Workspace (ICR Nano WG) with a mission to federate nanotechnology databases. The Nanotechnology Working Group includes about 60 people representing approximately 40 agencies, universities and institutes, a few from Europe. One requirement of this group has been to develop data and vocabulary standards to facilitate federation and increase data accessibility. EVS is contributing to this effort as an active participant in the working group. Part of the working group effort is the continuing development of the Nanoparticle Ontology (NPO) from Washington University in St. Louis. EVS has supported this effort in several areas: giving feedback on ontology structure and terminology best practices, supporting NPO curation using the NCI Protégé platform, loading and hosting NPO on LexEVS, preparing NPO for integration into the NCI Metathesaurus (NCIm), and planning for future editing of NPO in the BiomedGT Wiki collaborative editing environment.
The NCI CCNE office partnered with CBIIT in 2006 to develop a data sharing platform called caNanoLab. caNanoLab has a goal of semantic interoperability across centers performing nanoparticle characterization studies. caNanoLab is based on an information model representing nanoparticles and their physical and in vitro characterization. NCI Thesaurus (NCIt) has been supporting concept curation for development of caNanoLab since its inception. NCIt editors have worked with the developers and users of caNanoLab from the CCNEs and other academic institutions to define concepts for data curation and to expand the object model to include data submission for both characterizations of experimental nanomaterials and translational research studies. Funding for additional development was recently lost, but caNanoLab continues to be heavily used. It currently contains 886 samples, 72 sample sources, 3,329 characterizations, and 41 protocols, and identifies 1,073 publications. The caNanoLab homepage shows 141,668 visitors since June 3, 2010.
Developed by CBIIT, Oregon State University, PNNL, Washington University St. Louis, Stanford, Jackson Labs, Pennsylvania BioNano Systems, NIOSH, NCI Frederick NCL, Emory/Georgia Tech. This tool is used by all members of the ICR Nano Working Group. Despite recent loss of caNanoLab funding, NanoTAB continues to be used heavily.
NanoParticle Ontology (NPO)
This terminology is loaded in NCI Metathesaurus, on LexEVS, and on the NCI Term Browser. NPO curators use the NCI Protégé curation tool and they use NCI Thesaurus as a cross-reference and a source for some of their definitions.
This database, which predates caBIG®, provides curated information for animal models of human cancers. caMOD annotates information with NCIt terminology, and uses the LexEVS API directly to generate anatomy and diagnosis tree hierarchies. 400 concepts were added or updated for caMOD in the past six months.
Common Biorepository Model (CBM)
EVS has provided about 1,300 concepts for this model through support for caDSR. CBM is used in many domains including clinical trials management, ICR, in vivo imaging, and tissue banks and pathology tools.
Human Studies Database (HSDB) Consortium
HSDB is using LexEVS as a core component of its collaborative, distributed, clinical research systems. The OCRe Terminology is served through an NCBO site, which uses LexEVS. This is an example of a consortium of institutions leveraging LexEVS terminology services at the core of a new workflow for the collection of human studies data.
Imaging standards development requires the support of multiple products made available through EVS, including publication of RadLex terminology, developed through a collaboration of the Radiological Society of North America (RSNA), which convened experts in imaging informatics and radiological subspecialties to create this resource, now made freely available. RadLex has developed into a rich, structured radiology-specific ontology, which currently includes more than 30,000 terms and to which EVS provides content as well as publication support. EVS incorporates RadLex into the NCI Metathesaurus, and also supports imaging terminology in the NCI Thesaurus as needed by the imaging community.
Georgetown uses LexEVS and other EVS resources for its cancer Bench-to-Bedside (caB2B) project and other activities. Both a local LexEVS installation and NCI's production LexEVS servers provide terminology support for this project. This is an example of how terminology services are being incorporated into other tools as primary components in support of translational medicine.
Mayo Clinic has partnered with, supported and used EVS resources in a variety of ways over many years. Mayo both develops and uses LexEVS (see above).
Pharmacogenomics Research Network (PGRN) Ontology Network Resource (PHONT)
Mayo Clinic is the primary site for PHONT, a leading user of EVS resources supporting clear annotation and representation of phenotype (disease, adverse event, or clinical and physiological outcomes) to support data integration and cross-database analyses, collaborating with Case Western Reserve University, Harvard Medical School, MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, University of Erlangen, and Washington University.
Strategic Health IT Advanced Research Projects: Research Focus Area 4 - Secondary Use of EHR Data
Ohio State University Medical Center
Ohio State is using LexEVS, NCIt, and NCIm, notably for openMDR. Ohio State University launched openMDR (open metadata repository) in 2009, using local instances of LexEVS, BioPortal, and caDSR. This is an example of an academic research group adopting several open source components of NCI's EVS and semantic infrastructure, and integrating them to create a novel tool for metadata management.
Open Biomedical Ontologies (OBO)
EVS has worked with the OBO Foundry group since around 2005 to develop shared principles for open ontologies. NCI Thesaurus is designated as an Application ontology, since it uses and references domain ontologies within the OBO Foundry group. EVS makes several of the OBO Foundry ontologies available through LexEVS for caBIG® use. (For more information, visit the OBO Foundry website.)
Stanford/National Center for Biomedical Ontology (NCBO)
NCBO bases its BioPortal terminology services on LexEVS. NCIt is generally at or near the top of the NCBO ontology use chart (see section 3 above). NCBO and EVS maintain ongoing coordination and harmonization efforts through both caBIG® and other channels. For example, NCBO participates in the VCDE working group on Representing Terminology Metadata, which is adapting work begun by NCBO in this area for use by NCI and NCRI. NCBO also makes its terminologies available through caGrid.
NCBO built its NCBO BioPortal ontology services on top of LexEVS, supporting a very wide collection of ontologies that are actively used in biomedicine. This is an example of how two federally-funded groups are working together on the development of resources that will benefit the biomedical terminology community.
Stanford Tissue Microarray Database (TMAD)
TMAD [http://tma.stanford.edu] is an important public resource for raw and processed data (with stained tissue images) from tissue microarray experiments. TMAD uses NCI Thesaurus to index, browse and search tissues, and provides methods for data retrieval, grouping of data, analysis and visualization as well as export to standard formats.
University of Pittsburgh
Pittsburgh uses the NCI Thesaurus cancer, anatomy, and pathology findings terminologies for their research and informatics projects. The ODIE project is used by the University of Pittsburgh, University of California, San Diego, and Children's Hospital, Boston. This collaboration has resulted in the publication of two papers in peer-reviewed journals so far:
- Tobias J, Chilukuri R, Komatsoulis GA, Mohanty S, Sioutos N, Warzel DB, Wright LW, Crowley RS. The CAP Cancer Protocols – A Case Study of caCORE Based Data Standards Implementation to Integrate with the Cancer Biomedical Informatics Grid. BMC Medical Informatics Decision Making, 20; 6:25, 2006.
- Liu K, Chapman WW, Savova G, Chute CG, Sioutos N, Crowley RS. Effectiveness of Lexico-syntactic Pattern Matching for Ontology Enrichment with Clinical Documents. Methods Inf Med. 2010: 8;49(6).
Washington University uses LexEVS and EVS terminology content in its clinical data warehouse project (CIDER). Washington University deployed LexEVS in 2008 as the terminology server for CIDER. The terminologies are used to code data and for information retrieval. This is an example of an academic medical center adopting NCI EVS technology to support research and clinical enterprise infrastructure.