A major barrier to the conduct of biomedical research is how difficult it is to share biomedical research data, both within and between institutions. Data located in different data repositories are almost always organized, categorized, and represented in different ways. This problem has been referred to as “the Chasm of Semantic Despair.” In an attempt to address this problem, the Cancer Informatics group at the NCI, in collaboration with their colleagues at the FDA, ISO, HL7, and CDISC, developed a new international standard data model for biomedical research called the Biomedical Research Integrated Doman Group (BRIDG) model. The purpose of the BRIDG model is to “bridge” the large number of Chasms of Semantic despair that exist both within and between academic medical centers, pharmaceutical companies, and government regulators. The Sidney Kimmel Cancer Center at Thomas Jefferson University in Philadelphia, has successfully designed and implemented a cancer research information system based on the NCI-BRIDG model. In this talk. Dr. Klumpp will describe how the BRIDG model has been implemented in the cancer research information system at Thomas Jefferson and the benefits of such an integrated system.
FDA, CDC, NIH (NCATS) are developing a FHIR based infrastructure that facilitates interactions with the four most prevalent Common Data Models (CDMs) - Sentinel , OMOP, i2b2/ACT and PCORNet - from a single portal. The infrastructure allows investigators the ability to create a universal query that can be run against all four CDMs, a secure transport and aggregation of the cross CDM query results, and the ability to submit the results directly to the FDA as a CDISC STDM file.
Building a web-based API (Application Programming Interface) has been rapidly adopted in the bioinformatics field as a new way of disseminating the underlying biomedical knowledge. While researchers benefit from the simplicity and the high accessibility (A) of available APIs, the findability (F), interoperability (I) and reusability (R) across APIs are largely not well-handled by the community. BioThings API project (http://biothings.io) is tasked to build a FAIR API ecosystem to better serve the underlying inter-connected biomedical knowledge. BioThings API provides three components in its API development ecosystem. First, it provides a family of high-performance APIs for accessing up-to-date annotations for genes, genetic variants, chemicals and drugs. Second, BioThings API packages its API-development best practice into a reusable SDK (Software Development Kit) to help other bioinformaticians to build the same high-quality API to distribute their own specific knowledge. Third, BioThings API provides a platform to foster the findability and interoperability across the community-developed biomedical APIs. Through the SmartAPI application (http://smart-api.info), it provides tools for authoring API metadata following the community supported OpenAPI standard and hosts standardized interactive API documentation. It also defines a set of OpenAPI extensions to provide biomedical-specific semantic annotations, such as what specific biomedical identifiers an API parameter accepts and what specific biomedical entity types an API response contains. Powered by these semantic annotations, a new web application called BioThings Explorer was developed to allow researchers to navigate the scope of the distributed biomedical API landscape and build the desired knowledge extraction workflows by identifying and combining required APIs.
In this talk, Dr. Smith will describe the work he and his lab are doing to progress the state of Informatics for Computational Mass Spectrometry to further proteomic research.