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

Abstract

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.