A Semantic Web Management Model for Integrative Biomedical Informatics

Abstract

BackgroundData, data everywhere. The diversity and magnitude of the data generated in the Life Sciences defies automated articulation among complementary efforts. The additional need in this field for managing property and access permissions compounds the difficulty very significantly. This is particularly the case when the integration involves multiple domains and disciplines, even more so when it includes clinical and high throughput molecular data.Methodology/Principal FindingsThe emergence of Semantic Web technologies brings the promise of meaningful interoperation between data and analysis resources. In this report we identify a core model for biomedical Knowledge Engineering applications and demonstrate how this new technology can be used to weave a management model where multiple intertwined data structures can be hosted and managed by multiple authorities in a distributed management infrastructure. Specifically, the demonstration is performed by linking data sources associated with the Lung Cancer SPORE awarded to The University of Texas MDAnderson Cancer Center at Houston and the Southwestern Medical Center at Dallas. A software prototype, available with open source at www.s3db.org, was developed and its proposed design has been made publicly available as an open source instrument for shared, distributed data management.Conclusions/SignificanceThe Semantic Web technologies have the potential to addresses the need for distributed and evolvable representations that are critical for systems Biology and translational biomedical research. As this technology is incorporated into application development we can expect that both general purpose productivity software and domain specific software installed on our personal computers will become increasingly integrated with the relevant remote resources. In this scenario, the acquisition of a new dataset should automatically trigger the delegation of its analysis.

Exposing the cancer genome atlas as a SPARQL endpoint

“…These are: Deployment, an entity representing an instance of an S3DB engine; User, an authenticated entity of any S3DB Deployment; Project, an entity that represents a specific domain by aggregating its entities and attributes; Collection, any entity associated with a domain that may be instantiated; Rule, the association between two Collections or between a Collection and a literal attribute; Item, an instance of a Collection; Statement, the relationship between two Items or between an Item and a literal value (see Fig. 4 in [28]). By design, each instance of an S3DB entity is automatically associated with a URI that consists of a URL (identifying the S3DB deployment in which the data are kept) concatenated with an alphanumeric identifier composed of the first character of the entity name (D, U, P, C, I, R or S) and a numeric component unique for each deployment of S3DB.…”

“…TCGA experimental datasets were broken into their fundamental data elements and assigned to entities of the Simple Sloppy Semantic Database (S3DB) management model [28]. S3DB defines entities and relationships using an RDF schema (RDFS) core model that enables encapsulation of RDF triples as part of a domain description, also represented as RDF triples [29].…”

Semantic Information Modeling for Emerging Applications in Smart Grid

“…Semantic modeling is an active research area that has been studied in many domains including Smart Oilfield [29], eHealthCare [16], [24], biology [17], [23] and transportation [20], [21]. Different from existing Smart Grid standards, the semantic Smart Grid information model allows us to describe data semantics as well as represent domain knowledge using a description language and automate data and knowledge transforms based on reasoning.…”

Construction of coffee transcriptome networks based on gene annotation semantics

“…Multiple data sets are derived deBio2RDF, but also some that were built independently. Approaches based on Semantic Web for biomedical data integration have been proposed in some instances in recent years [12,13,14,15]. In the biomedical field, a resource copy has been represented by Bio2RDF [16], a system for integrated access to a large number of biomedical databases through Semantic Web technologies RDF, ie, for data representation and SPARQL (SPARQL Protocol and RDF Query Language) [17] for queries.…”