Appraise, prepare, and describe data while promoting and enabling discovery. Identify systems, tools, and applications that reduce costs and improve quality. Develop new products and services based on existing and new data that are useful on the global scale for the long-term. Data providers knowledge and skills: Prepare, document, and identify data. Recognize rights holders and restrictions. Data users knowledge and skills: Locate, identify, and access data. Acquire appropriate rights to that data. Provide attribution. DataNet Education Initiatives Data Conservancy Sayeed Choudhury – Data Conservancy: A Blueprint for Research Libraries Carole Palmer – Leveraging Data Conservancy R & D to Advance Data Curation Education Three pillars of libraries—collections, services, and infrastructure—all relevant for data. Data potentially new kind of special collections, however curation needs to start further rather than at end of data life cycle Data curation as a means and not an end. Data scientists are human interface between domain scientists and data management professionals--interoperability more difficult among humans than machines. Data professionals need to provide access to a broad landscape of information across scales, disciplines, institutions, and generations. Building on established data curation masters specialization and summer institute for professional development at Illinois, and new program integrating of field experience into masters and doctoral programs. Need to build awareness and share resources among existing programs. Greatest challenges: Documenting best practices
Appraise, prepare, and describe data while promoting and enabling discovery. Identify systems, tools, and applications that reduce costs and improve quality. Develop new products and services based on existing and new data that are useful on the global scale for the long-term. Data providers knowledge and skills: Prepare, document, and identify data. Recognize rights holders and restrictions. Data users knowledge and skills: Locate, identify, and access data. Acquire appropriate rights to that data. Provide attribution. DataNet Education Initiatives Data Conservancy Sayeed Choudhury – Data Conservancy: A Blueprint for Research Libraries Carole Palmer – Leveraging Data Conservancy R & D to Advance Data Curation Education Three pillars of libraries—collections, services, and infrastructure—all relevant for data. Data potentially new kind of special collections, however curation needs to start further rather than at end of data life cycle Data curation as a means and not an end. Data scientists are human interface between domain scientists and data management professionals--interoperability more difficult among humans than machines. Data professionals need to provide access to a broad landscape of information across scales, disciplines, institutions, and generations. Building on established data curation masters specialization and summer institute for professional development at Illinois, and new program integrating of field experience into masters and doctoral programs. Need to build awareness and share resources among existing programs. Greatest challenges: Documenting best practices