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Bridging Data Policy Gaps: Future Trends and Challenges in Data Sharing and Storage

Exploring current data practices, challenges, and future landscapes in data storage and sharing, addressing incremental changes and policy gaps. Discusses incentives, hurdles, and potential for personalized medicine, predictive models, genome informatics, and participatory research.

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Bridging Data Policy Gaps: Future Trends and Challenges in Data Sharing and Storage

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  1. Mind the Gap: Reflections on Data Policies and Practice Dr Liz Lyon, Director, UKOLN, University of Bath, UK Associate Director, UK Digital Curation Centre JISC/CNI Conference, Edinburgh, July 2010 . UKOLN is supported by: This work is licensed under a Creative Commons LicenceAttribution-ShareAlike 2.0

  2. Overview • UK Data Policy Context • Institutions & open science • Data practice today • Future landscape • Scale and complexity • Open and personal • Drivers and incentives • Challenges & Actions • Planning tools • Policy Gaps

  3. 1. Current Practice • Scale, Complexity, Predictive Potential • Continuum of Openness • Citizen Science • Credentials, Incentives, Rewards • Institutional Readiness & Response • Data Informatics Capacity & Capability • Open Science at Web-Scale Report http://www.ukoln.ac.uk/ukoln/staff/e.j.lyon/publications.html#november-2009

  4. Scoping study : institution perspective • Creating & organising data • Storage and access • Back-up • Preservation • Sharing and re-use INCREMENTAL Project

  5. http://www.flickr.com/photos/mattimattila/3003324844/ “Departments don’t have guidelines or norms for personal back-up and researcher procedure, knowledge and diligence varies tremendously. Many have experienced moderate to catastrophic data loss” Incremental Project Report, June 2010

  6. “Data sharing was more readily discussed by early career researchers.” “While many researchers are positive about sharing data in principle, they are almost universally reluctant in practice. ..... using these data to publish results before anyone else is the primary way of gaining prestige in nearly all disciplines.” INCREMENTAL Project

  7. Heather Piwowar …but many researchers don’t share… …and are reluctant to re-use data…

  8. “Interviewees were often unaware of existing guidance, resources.... and policy documents.” “They found the documents ....to be dense, wordy, theoretical, ambiguous and un-engaging.” Incremental Project Report, June 2010

  9. “Many people are suspicious of ‘policies’ which sound like hollow mandates, but are receptive to ‘procedures’ or ‘advice’ which may be essentially the same thing, but convey a sense of purpose and assistance rather than requirement.” The majority of people felt that some form of policy or guidance was needed.... Incremental Project Report, June 2010

  10. 2. Future Data Landscape ? Genomics exemplar

  11. $1000 genome in <15 minutes ....by 2013? ...Next next generation technology race to market

  12. Researchers need.... • Large-scale data storage that is: • Cost-effective (rent on-demand) • Secure (privacy and IPR) • Robust and resilient • Low entry barrier / ease-of-use • Has data-handling / transfer / analysis capability • Cloud services? • “....analyse an entire human genome in a single day sitting with a laptop at your local Starbucks.”

  13. Data storage policy? The “new” genome informatics ecosystem The case for cloud computing in genome informatics. Lincoln D Stein, May 2010

  14. Post-genome decade Human genomes: >24 published & almost 200 unpublished

  15. They have shared their data….

  16. Share my data Data sharing policy?

  17. “P4 medicine : Predictive, Personalised, Preventive, Participatory.”Leroy Hood – Institute for Systems Biology ...“medicine is going to become an information science”... Image from Scientific American

  18. P4 medicine • Each patient’s genome sequenced • Your genome is basis of your medical record • New method to anonymise medical records for genomics research at Vanderbilt Univ (April ‘10) • New Predictive models of health and disease • Personalised treatments focus on Preventative therapies Genome scale network biology Genomic data as a commodity

  19. Sage Bionetworks : Integrative genomics Open data in the Sage Commons repository Human and mouse: clinical and genetics data Develop predictive models of disease: liver / breast / colon cancer, diabetes, obesity Crowd-sourced effort : global scope Stephen Friend

  20. Participatory medicine : share data & empower the patient... Sage Congress San Francisco April 2010

  21. Significant implications for Faculty • Awareness of wider societal benefits • University Ethics Committee “You have zero privacy anyway. Get over it” Scott McNealy, CEO Sun Microsystems, 1999 Data Ethics & Privacy Policy?

  22. Public participation, citizen science Results data : validate in professional press

  23. Faculty attitude & culture • Professional : amateur Data policy for public engagement?

  24. Incentives? Calls for action, new metrics

  25. Journal Article Workflow Visualisation Model Data Annotation Concept Complexity : what are we citing? Macro Micro / Nano Attribution granularity

  26. Large-scale predictive network models of disease Data citation policy? • Multiple datasets • Visualise: Cytoscape • Workflow: Taverna

  27. 3. Policy guidance, planning tools, Code of Conduct

  28. State-of-the-Art Report : Models & Tools (Alex Ball, June 2010) Data Lifecycles Data Policies (UK) incl DMP Standards & tools Data Asset Framework (DAF) DANS Seal of Approval Preservation metadata Archive management tools Cost / benefit tools

  29. Data types, formats, standards, capture • Ethics and Intellectual Property • Access, sharing and re-use • Short-term storage & data management • Deposit & long-term preservation • Adherence and review

  30. DMP Online Currently updating Version 2.0 Version 3.0 summer 2010 http://www.dcc.ac.uk/dmponline

  31. Making DMPs work : the start of a long process… • Embed DMPs in funder policies & research lifecycles as the norm • Code of Conduct for Research • Assess & review DMPs (not just the science content of proposals) • Educate reviewers (DCC guidance for social science in prep) • Manage compliance of researchers • Infrastructure to share DMPs • Analyse cost-benefits for UK HE

  32. Take homes... • Practice is disconnected from policy • Policy Gaps • Data Storage (& Appraisal: DCC guidance in prep) • Data Sharing (& Licensing: DCC guidance in prep) • Ethics and Privacy • Citizen Science & Public Engagement • Data Citation and Attribution • Collaborate with funders to make DMPs work • Digital Curation Centre DMP tool & resources www.dcc.ac.uk

  33. Thank you… Chicago Mart Plaza, 6-8 December 2010

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