Functional Requirements for Research Data Repositories

Research data must be testable. Science is all about verification and testing. To make data testable, tools used to produce, collect, and examine data during the research must be available. Quite often, however, these data become inaccessible once the work is over and the results being published. Hence, information and the related context must be provided on how research data are preserved and how they can be reproduced. Open Science is the international movement for making scientific research data properly accessible for research community. One of its major goals is building data repositories to foster wide dissemination of open data. The objectives of this research are to examine the features of research data, common repository platforms, and community requests for the purpose of designing functional requirements for research data repositories. To analyze the features of the research data, we use data curation profiles available from the Data Curation Center of the Purdue University, USA. For common repository platforms we examine Fedora Commons, iRODS, DataONE, Dataverse, Open Science Data Cloud (OSDC), and Figshare. We also analyze the requests from research community. To design a technical solution that would meet public needs for data accessibility and sharing, we take the requirements of RDA Repository Interest Group and the requests for the DataNest Community Platform developed by the Korea Institute of Science and Technology Information (KISTI). As a result, we particularize 75 requirement items grouped into 13 categories (metadata; identifiers; authentication and permission management; data access, policy support; publication; submission/ingest/management, data configuration, location; integration, preservation and sustainability, user interface; data and product quality). We hope that functional requirements set down in this study will be of help to organizations that consider deploying or designing data repositories.