Functional and Architectural Requirements for Metadata: Supporting Discovery and Management of Scientific Data

Jian Qin, Alex Ball, Jane Greenberg


The tremendous growth in digital data has led to an increase in
metadata initiatives specific to different types of scientific data, as evident by
Ball's survey (2010). Although various communities have specific needs, there are shared
goals that need to be recognized if systems are to effectively support data sharing
within and across all domain. This paper considers this need, and defines systems
requirements that are essential for metadata supporting the discovery and management of
scientific data. The paper begins with an introduction, following by a review of
selected research specific to metadata modeling in the sciences. Next, the paper’s goals
are stated, following by the presentation of systems requirements are stated. The
results include a base-model with three chief principles: principle of least effort,
infrastructure service, and portability. The principles are intended to support "data
user" tasks. Results also include a set of defined user tasks and functions, and
applications scenarios.

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