1. Data & Publication Submission Processes; Carrots & Sticks; Incentives & Coercion Why important? –legacy –International exchange of information –Scientist-to-scientist collaboration –Scaling up to pan-Arctic What’s involved? –Egos –Multidisciplinary data/info –Huge volumes –Education & outreach Need: active & accessible data & info system

2. Issues Data delivery-- to PI, center to center, out to public Phasing—preparation before field phase, during field phase, and after field work completed Pre-field phase –identifying data up front –PIs submit plans for data collection Strategy: make it easy to submit vs. provide incentives Recommendation: data subcommittee to implement a IPY philosophy or paradigm (as well as data policy) that is different from standard operating procedures

3. Elevate production of dataset to level of research Growing awareness of importance of data in research Link to access/barrier list from access wg Data publications – reports, section of journal, new journal IPY archive/acknowledgement policies Institutional, cultural, and educational change needed Examples: –dataset citation index? In oceanography –WDC system in Germany cited in German national library –Digital object identifier an element in this How to integrate data publication in with larger IPY research publication strategy (e.g., allow data pubs as part of IPY pubs) What are alternate approaches? –Genomic journals required that PIs submit data in advance of publication –(but not copyright submitted data!) Is there a proper e-journal? Review will still take time

4. Data management issues What about short-term access? Trust issue; how to build trust into system, and mutual benefits. Or self benefit of establishing first production of particular data In IPY social science, forming of intl consortia; basis for change in science Data management leads to benefit of improved data access Use of creative commons licensing to promote access but enforce rights related to attribution, non-commercial use Need to add separate project data into collective whole Examples in EU of projects that successfully work together and have data management strategies –EU has business and dissemination plan for its research now –Projects are rated based on different parts of project LBA example, where data management was there, but success limited –One issue is follow up of funding to period when data are being cleaned up and submitted Willingness of funding agencies to carry out and enforce funding Can be very dependent on program manager’s attitude

5. Overall Recommendation 3 parts to incentives/coercion strategy –Mutual benefit of sharing to research –Acknowledgement/publication –Funding Statement of JC to funding bodies to highlight importance of data management and follow-through (time critical since RFPs are out or coming out soon) Guidance to PIs – in short term?

6. Pre-project phase Pre-negotiation with journals PIs provide data collection plans by end of 2006 (high-level metadata) Establish a data management prize/award Identify effective tools, examples of good practice PI-Data manager interactions, e.g., regional basis Help desk for PIs on data management (e.g., working with eGY?) Work on funding agencies to support data management efforts Regional user workshops (e.g., for N. America) But regional approach not enough…need to reach PIs in other ways –E.g., WOCE successful because data node/center managers established who pursued data from PIs Funders should support IPY team involvement in data management activities, training, etc. Data issues need to be prominent in IPY scientific meetings Funding issues need to be raised NOW! In order to influence RFPs

7. Field Phase