Translating the massive increases of data related to biomedical research into improved health care will require improved methods of data management and software tool development, according to two National Institutes of Health reports — the The Biomedical Information Science and Technology Initiative, prepared by the Working Group on Biomedical Computing Advisory Committee to the NIH Director, and the NIH Roadmap for Accelerating Medical Discovery to Improve Health: Bioinformatics and Computational Biology. Both documents recommend employing advanced data management technologies for developing interoperable biomedical databases and software engineering principles for delivering robust and reliable tools for biomedical research.

Data management and bioinformatics software development challenges are also discussed in the U.S. Department of Energy's (DOE) Genomes to Life (GTL) program report User Facilities for 21st Century Systems Biology: Providing Critical Technologies for the Research Community. GTL envisions different types of facilities generating data that would be organized in a variety of databases, including expression, proteomic, protein-function, chemistry, and pathway databases. Data will be collected, archived, and passed through a number of processing stages, including data annotation and integration, whereby a "seamless and effectively centralized capability to deal with data" in the form of data centers collecting and integrating effectively large scale biological data is seen as key to GTL's success.

To help meet these needs, the Biological Data Management and Technology Center (BDMTC) was established in January 2004 in the Computational Research Division (CRD) at DOE's Lawrence Berkeley National Laboratory (LBNL). BDMTC will serve as a source of expertise in and provide support for data management and bioinformatics tool development projects at the Joint Genome Institute (JGI), Life Sciences and Physical Biosciences Divisions at LBNL, Biomedical Centers at UCSF, and other similar organizations in the Bay Area. BDMTC will enable collaborating organizations to share experience, expertise, technology, and results across projects. BDMTC will employ industry practices in developing data management systems and bioinformatics tools, while maintaining academic high standards for the underlying data generation, interpretation, and analysis methods and algorithms.

BDMTC will provide support in addressing key data management challenges, including:

• the massive increase in the amount and range of biological data,
• the difficulty of quantifying the quality of data generated using inherently imprecise tools and techniques, and
• the high complexity of integrating data residing in diverse and sometimes poorly correlated repositories.

BDMTC's strategy involves using existing technology and methods, adapted as needed to a specific application, in order to address immediate data management and bioinformatics requirements. Cost effectiveness and the ability to take advantage of rapid technological advances without loss of quality, time or cost will be built into solutions that are inherently evolving. Critical data management problems that cannot be resolved using existing technology will be pursued as part of longer term R&D activities.

BDMTC is led by Victor M. Markowitz, who until recently was CIO and Senior VP, Data Management Systems at Gene Logic, where he was responsible for the development and deployment of the data management and analysis platform for the company's gene expression data. Prior to joining Gene Logic in 1997, he was a staff scientist at LBNL, where he led the development of data management tools applied to biological databases.

BDMTC is currently involved in data management projects at JGI and in the UC Berkeley proposal for an NIH National Center for Biomedical Computing, where it provides the infrastructure, data management, and software development cores. BDMTC aims to become a QB3 affiliated center.