Open Science at Web-Scale: Breaking
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1 Open Science at Web-Scale: Breaking all Barriers? Dr Liz Lyon, Director, UKOLN, University of Bath, UK Associate Director, UK Digital Curation Centre eresearch Australasia, November 2009 This work is licensed under a Creative Commons Licence Attribution-ShareAlike 2.0 UKOLN is supported by:. k A centre of expertise in digital information management UKOLN / DCC Consultative Report Six areas for consultation Published 10 Nov
2 Roadmap Research Data Signposts : Directions of travel Barriers, Fuel or Freeway : Scale, Openness, Attribution Capacity and Capability :Driving transformational change Research Data Signposts : Directions of travel
3 Your data in their Cloud? all too many observations lie isolated and dforgotten on personal lhard ddi drives and CDs trapped by technical, legal and cultural l barriers...
4 Share my data? November 2009 Why? Lack of awareness of potential? Reluctance to collaborate and share?
5 The slow socialisation of science Inter-institutional collaboration better science (Brian Uzzi, 2008) Team science at Web-Scale? Science as a social activity Tweet Blog Comment Rate Vote Recommend Tag Share Mash Barriers, Fuel or Freeway : Scale Openness Attribution
6 k A centre of expertise in digital information management Pacific Biosciences California Next-next generation sequencing Single molecule sequencers Complete human genome in 15 minutes by 2013
7 k A centre of expertise in digital information management k A centre of expertise in digital information management
8 Infrastructure for Integration in the Structural Sciences (I2S2) Bridging the chasm between large scale facilities and the laboratory bench Integrated Information Model based on the Core Scientific MetaData Schema and the DCC Curation Lifecycle Model Use cases and Inter-disciplinary Pilots Cost-benefit analysis: before and after Transcalar 4D data modelling of pancreatic organogenesis in mouse Virtual pancreas computational ti model anticipates in vivo biological findings
9 72 partners (Europe) >40 models (coastal seas) > 15 institute i feeds Citation of models? Curation & preservation of models? Validation & verification? Societal implications? We can accurately estimate the current level of weekly influenza activity in the US with a reporting lag of about one day.
10 Barriers, Fuel or Freeway : Scale Openness Attribution Participation Citizen science Volunteers interested amateurs Continuum of Openness Professional, experts Lone scholar dark data Closed Creative Commons Attribution-Non-Commercial-Share Alike 2.0 Open access Access
11 Radical? Fringe? Transferable to other disciplines? Peer Production Can this model be applied to other disciplines? Cost benefits?
12 An early citizen scientist? 110 years later Still engaging g g the public in science...
13 Working with professional scientists
14 How can scientists learn from citizen journalists? Pi Privacy issues?
15 You have zero privacy anyway. Get over it Scott McNealy, CEO Sun Microsystems, 1999 Solve puzzles for science
16 Crowdsourcing science? Collaboration market New business model?
17 Costs? Benefits? Risks? Attitudes to citizen science? Strategy & policy implications for funders? Impact on research quality? Societal implications? Barriers, Fuel or Freeway : Scale Openness Attribution
18 H Factor from Google Scholar Grant/Manuscript t Review Factor cumulated authenticated reviews Annotations/Software/Datasets ti /D t t Factor cumulated entries to OA archive (data, sequences, software) Web Factor authenticated ti t blog / wiki posts Dec 16, Washington DC Formal recognition? Incentive and reward structure? Research funder position? Publisher / learned society view?
19 Capacity and Capability: Driving transformational change Research Infrastructure: t primary components Skills People Workflows Research Infrastructure Data Services Process Is your institution ready for open science at Web-Scale?
20 New academic structures? New policies? IPR issues? Library and Information Services roles? Open Science at Web-Scale Report 2009
21 New roles, new skills, new curricula? Advocacy & support? Capacity Community curation Peer production Data scientists, LIS Professional scientist Data Informatics: Logistics dilemma Annotation Audit Data cleansing Data management plans Metadata schema Observations Ontologies Preservation Selection & Appraisal Training Visualisation Capability Citizens Volunteers, interested amateurs Creative Commons Attribution-Non-Commercial-Share Alike 2.0 Professional scientist
22 Take homes 1. Open Science = accessible data + wider participation 2. We need new metrics 3. Are our institutions ready? 4. Capacity : Capability 5. Articulate range of values and benefits For Rosalind Franklin For whom, open science came too late...
23 Moving to Multi-Scale Science: Managing Complexity & Diversity Thank you Slides will be available ailable at :
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