ReVeaLD: a user-driven domain-specific interactive search platform for biomedical research.

Bioinformatics research relies heavily on the ability to discover and correlate data from various sources. The specialization of life sciences over the past decade, coupled with an increasing number of biomedical datasets available through standardized interfaces, has created opportunities towards new methods in biomedical discovery. Despite the popularity of semantic web technologies in tackling the integrative bioinformatics challenge, there are many obstacles towards its usage by non-technical research audiences. In particular, the ability to fully exploit integrated information needs using improved interactive methods intuitive to the biomedical experts. In this report we present ReVeaLD (a Real-time Visual Explorer and Aggregator of Linked Data), a user-centered visual analytics platform devised to increase intuitive interaction with data from distributed sources. ReVeaLD facilitates query formulation using a domain-specific language (DSL) identified by biomedical experts and mapped to a self-updated catalogue of elements from external sources. ReVeaLD was implemented in a cancer research setting; queries included retrieving data from in silico experiments, protein modeling and gene expression. ReVeaLD was developed using Scalable Vector Graphics and JavaScript and a demo with explanatory video is available at http://www.srvgal78.deri.ie:8080/explorer. A set of user-defined graphic rules controls the display of information through media-rich user interfaces. Evaluation of ReVeaLD was carried out as a game: biomedical researchers were asked to assemble a set of 5 challenge questions and time and interactions with the platform were recorded. Preliminary results indicate that complex queries could be formulated under less than two minutes by unskilled researchers. The results also indicate that supporting the identification of the elements of a DSL significantly increased intuitiveness of the platform and usability of semantic web technologies by domain users.

A family-based framework for supporting quality assurance of biomedical ontologies in BioPortal.

BioPortal contains over 300 ontologies, for which quality assurance (QA) is critical. Abstraction networks (ANs), compact summarizations of ontology structure and content, have been used in such QA efforts, typically in a "one-off" manner for a single ontology. Ontologies can be characterized-independently of knowledge-content focus-from a structural standpoint leading to the formulation of ontology families. A family is defined as a set of ontologies satisfying some overarching condition regarding their structural features. Seven such families, comprising 186 ontologies, are identified. To increase efficiency, a new family-based QA framework is introduced in which an automated, uniform AN derivation technique and accompanying semi-automated, uniform QA regimen are applicable to the ontologies of a given family. Specifically, across an entire family, the QA efforts exploit family-wide AN features in the characterization of sets of classes that are more likely to harbor errors. The approach is demonstrated on the Cancer Chemoprevention BioPortal ontology.