Research data is defined as recorded factual material commonly retained by and accepted in the scientific community as necessary to validate research findings. Research data is precious to the global community and its correct management is crucial. In the context of research and scholarship, RDM refers to the storage, access and preservation of data produced from a given investigation. Data management practices cover the entire lifecycle of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to long term preservation of data deliverables after the research investigation has concluded. To ensure a correct and effective RDM, 4Science proposes an integration of DSpace(-CRIS/GLAM) with CKAN, http://ckan.org/, a fully-featured, mature, open-source data management solution. CKAN provides a streamlined way to make your data discoverable and presentable.
The DSpace-CKAN Integration Module allows users to directly preview the dataset content deposited in a CKAN instance from DSpace via a “curation task”. The new DSpace-CKAN Integration Module offers the users the possibility to access the services provided by the CKAN data management system without leaving their DSpace installation, making their life easier and their activities more efficient. The module allows to connect the publications with the datasets and better describe the context of realization of the dataset by creating detailed records on the equipment used, the related services, the projects concerned, etc.
One of the main advantages of the Module is that it allows the management of dataset access via DSpace, without the need of getting into a CKAN instance. The CKAN datastore API is proxied by the DSpace-CRIS/GLAM module, enhancing the access conditions set on the original DSpace bitstream (e.g.: the preview function is available under the same conditions of the uploaded bitstream: open access, embargo, etc.).
If structured data is uploaded or linked to CKAN as a .csv or Excel table, the DataStore loads it into a database, allowing CKAN to give a range of ways to view and process the data. Initially the data is displayed as a table. The user can sort the data on particular columns, filter or facet by values, or hide columns entirely. The data can also be displayed on a graph, choosing the variables on the axes and comparing a number of variables by graphing them together on the same y-axis.
