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Your Environment. Your Health.

NIH BD2K Workshop on Community-Based Data & Metadata Standards

February 25 – 26, 2015
John Edward Porter Neurosciences Research Center GE620/630, Bethesda, MD

Agenda

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Event Video / Webcast

Background

The ability to harvest the wealth of information contained in biomedical Big Data will advance our understanding of human health and disease; however, lack of appropriate tools, poor data accessibility, and insufficient training, are major impediments to rapid translational impact. To meet this challenge, NIH launched the BD2K trans-NIH initiative to enable biomedical research as a digital research enterprise, to facilitate discovery and support new knowledge, and to maximize community engagement. An important aspect of meeting this challenge is to make biomedical research data and resources maximally shareable and reusable. For this reason, BD2K is formulating approaches to encourage development and facilitate the use of data-related (including metadata) standards more broadly across the biomedical research community and is, therefore, interested in the issues involved in developing Community-Based Standards (CBS).

Goals

  1. Effective approaches, processes, and activities that could advance the community-based standards landscape (e.g., creating a collaborative workspace or an advising structure toward standards development, extension, or adoption).
  2. Gaps in community-based data standards of relevance to biomedical research, including real use-cases (e.g., emerging fields and technologies, or research domains with multiple existing data standards that could benefit from additional work, integration and/or reconciliation).
  3. Lessons learned from existing CBS efforts, particularly examples with field-tested processes and infrastructure or known examples of failures by CBS efforts.
  4. Common challenges in CBS development (e.g., methods for community engagement or building interoperability with other related standards). Considerations for evaluating progress and milestones to assess data standards development and utility.
  5. Effective approaches for addressing the need to sustain useful standards, and to update existing standards as a field develops.

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