The Biomedical Resource Ontology (BRO) to enable resource discovery in clinical and translational research

Abstract

The biomedical research community relies on a diverse set of resources, both within their own institutions and at other research centers. In addition, an increasing number of shared electronic resources have been developed. Without effective means to locate and query these resources, it is challenging, if not impossible, for investigators to be aware of the myriad resources available, or to effectively perform resource discovery when the need arises. In this paper, we describe the development and use of the Biomedical Resource Ontology (BRO) to enable semantic annotation and discovery of biomedical resources. We also describe the Resource Discovery System (RDS) which is a federated, inter-institutional pilot project that uses the BRO to facilitate resource discovery on the Internet. Through the RDS framework and its associated Biositemaps infrastructure, the BRO facilitates semantic search and discovery of biomedical resources, breaking down barriers and streamlining scientific research that will improve human health.

A configurable translation-based cross-lingual ontology mapping system to adjust mapping outcomes

“…In finance, ontologies are used to model knowledge in the stock market domain [33] and portfolio management [34]. In medicine, ontologies are used to improve knowledge sharing and reuse, such as work presented by Fang et al [35] that focuses on the creation of a traditional Chinese medicine ontology, and work presented by Tenenbaum et al [36] that focuses on the development of the Biomedical Resource Ontology in biomedicine.…”

“…case and space insensitive). 36 An example of translation collision may be: for entities and in O 1 , the best available candidate AOLT result derived for is meeting, and the best available candidate AOLT result for is also meeting. This causes a translation collision since these entities are distinctive of each other and should not have the same translation in O 1 ′ .…”

Lens: A Faceted Browser for Research Networking Platforms

“…It defines the type of a resource and all relationship edges have a domain and range constrained to one or more type of resources. The VIVO Ontology [3], which includes classes and properties from external ontologies, such as BIBO [21], SKOS [22], FOAF [8], Event [18], GeoPolitical [1], and Eagle-I [23], is further customized to suit the incoming data from a variety of resources. For instance, we have expanded our own experimental data based on the VIVO ontology with additional data from a variety of sources, including NSF/NIH feeds and web scraping from our own institution.…”

Resource Disambiguator for the Web: Extracting Biomedical Resources and Their Citations from the Scientific Literature

“…As described in our previous paper ([3]), each entry in the Registry includes a resource identifier, name, description, URL and resource type, which represents a set of metadata common across several major cataloging efforts in biomedicine including Biomedical Resource Ontology (BRO) [11] (RRID:nlx_143813), BioSiteMaps, and Eagle-i (RRID:nlx_144312) (See Fig 1). Indeed there are eight major types of resources: Data, Software, Training, Service, Material, Funding, People and Jobs.…”