Data Providers Dissemination – Access, cost, formats, size, metadata, service, support, findability, Policies – Copyright, fees, confidentiality, preservation, mandate (who are they serving?) Mission – Decisions-based? Is dissemination a mission? Control. Motivation for providing access.

Data Providers Over abundance of providers (hard to find, hard to choose, bad interfaces, duplication) Producers that do not disseminate their data (or do not do enough or control too tightly) Producers who treat data as commodity

Data Providers Movement to data-sharing and preservation – Open data, e-science, policies at NIH, NSF, UNESCO preservation declaration, OECD access to publically funded research data Data archives recognizing need for collaboration and partnerships between data archives (DATA PASS) Emerging national digital information strategies 2003 Berlin declaration of open access to knowledge

Data Providers National statistical agencies making statistics more easily available online (StatCan, Eurostat) Funding agencies learning more about value of data beyond their original intent – Movement to educate funders – Funding better informed E-science is generating awareness and funding for data sharing, data preservation, data access, data infrastructure

Technology Rapidly changing technologies IR Visualization Open access publishing policies Migration from desktop to network, from one computer to the cloud Changing nature of data for social sciences – Larger datasets, mixed methods, streaming data

Technology Digital curation Open data and metadata formats Collaborative environments (social networking, collaborative computing, etc.) Extremes between haves and have-nots of technology Issues of control Training is essential, continuing, expensive

Educational Sector Move to IRs and trusted, certified digital repositories Consumer driven post secondary education – distance ed., emphasis on undergraduates and continuing ed, competition for students, etc. Quantitative reasoning and literacy Undergraduate research emphasis Student expectation of instant delivery of information

Educational Sector Interdisciplinary studies: challenges by students and administrators to traditional disciplines Cyberinfrastructure Technology-driven teaching

External factors Mistrust – Fear, privacy, confidentiality, abuse of power. – Who can be trusted with your personal data, your research? Standards – Emerging international standards (DDI) – Need for standards

Data Profession Still more accidental than intentional data librarians Profession has shifted to life cycle management of data More opportunities for training No standard curriculum or professional track, yet. Geographic differences

Data Profession Major generational shift Big disparity in training, background, experience among professionals Big disparity in part time/full time positions Split between specialists and generalists