Generic tools and technologies for creating and maintaining data cooperatives- confederations whose purpose is distributed data sharing-will be developed to overcome the difficultiess encountered in the sharing of information in life sciences, specifically in bioinformatics.
The vision of large-scale data sharing has been a long-time goal of the bioinformatics field, much of it proceeding through data integration efforts. However, conventional approaches to data integration do not have the necessary flexibility and adaptability to make the existing and future plethora of data accessible and usable to typical biologists, while keeping it rapidly extensible to new concepts, domains, and types of queries, and thus fostering new research developments. The main reasons are that (1) different biologists work with different types of data and at differing levels of abstraction; (2) schemas in the bioinformatics world are typically large and complex; (3) queries and mappings may "break" without warning because of asynchronous updates; (4) it is logistically, economically and politically difficult to operate centralized data integration facilities. In response to these difficulties data cooperatives emphasize: decentralization for both scalability and flexibility, incremental development of resources such as schemas, mappings, and queries, rapid discovery mechanisms for finding the resources relevant to a topic, and tolerance for intermittent participation of members and for approximate consistency of mappings. More specifically, the technical goals of the proposal include: (1)collaboratively developed yellow pages of biological topics; (2) schema templates, capturing the part of the structure of data pertaining to a specific interest and functioning also as visual templates from which a query form created; (3) incremental specification of mappings; (4) reasoning about uncertainty in mappings by measuring with statistical tools their degree of reliability and using it in query answering; (5) multi-path answering for queries with caching and replication in a large-scale data cooperative where the participation of individual members may not always be assured.
Data cooperatives will have broader impact through applications in a variety of scientific and industrial fields, but it is in the field of bioinformatics that they are likely to have an immediate and significant impact. Therefore, a specific data cooperative as a biological testbed for evaluating the proposed technologies. This testbed is based on a small set of databases which are already collaborating and exchanging data related to Plasmodium falciparum. Broader impact will be also be achieved through the proposed educational initiatives, specifically through a "compu-tational orchestra" bioinformatics course which will expose students to data integration issues through project work, and a workshop for the Greater Philadelphia Bioinformatics Alliance (GPBA). Minority involvement will also be encouraged through a GPBA internship program.
