MetaStore: A metadata framework for scientific data repositories

Abstract

In this paper, we present MetaStore, a metadata management framework for scientific data repositories. Scientific experiments are generating a deluge of data and metadata. Metadata is critical for scientific research, as it enables discovering, analysing, reusing, and sharing of scientific data. Moreover, metadata produced by scientific experiments is heterogeneous and subject to frequent changes, demanding a flexible data model. Currently, there does not exist an adaptive and a generic solution that is capable of handling heterogeneous metadata models. To address this challenge, we present MetaStore, an adaptive metadata management framework based on a NoSQL database. To handle heterogeneous metadata models and standards, the MetaStore automatically generates the necessary software code (services) and extends the functionality of the framework. To leverage the functionality of NoSQL databases, the MetaStore framework allows full-text search over metadata through automated creation of indexes. Finally, a dedicated REST service is provided for efficient harvesting (sharing) of metadata using the METS metadata standard over the OAI-PMH protocol.