Data are valuable assets when exploited to impact change, scientific thought, productivity and growth. Data is being generated at an unprecedented rate. Data are now the new currency and deemed as major assets for science and for humanity. Management and stewardship of data is an area that needs the attention of the scientific community. Big data has been discussed at various forums and the focus has been on processing huge amounts of data. While that is important, the tools and techniques needed to harness data to facilitate easy retrieval and access is also crucial.
FAIR principles emphasize that it is not only important that data produced is used, but it is crucial for it to be stored, processed and hosted in such way as to make it easily Findable, Accessible, Interoperable and Reusable. The key to efficient data retrieval lies in efficient data representation and organization. Use of standards in data representation would ensure data Interoperability and reuse. The symposium is announced with an aim of disseminating and sharing the latest developments on the topic based on research experience of teams at Drexel University and Indian Statistical Institute. The Symposium draws on International expertise in the field. It aims to attract senior researchers and faculty, young researchers and students who will benefit from the knowledge exchange and interaction with International experts who have been identified. The symposium will serve as a platform for future research thoughts in an area of scientific importance.
Introduction to Data Repositories
Standards for Data Representation
Research Data Management
Comparative study of Data Repository software
Case studies: Comparative study of data.gov sites
Comparative study RDM sites
Institutional Data Management
Comparative study of domain-specific data types
DCAT and other metadata schemas
Data Licensing: Creative Commons and other Licenses
Technology Platform for data organization and services: CKAN
Institutional repository managers, data managers, librarians, information and knowledge managers, metadata editors and catalogers, scientists in different domains involved in data cycle.