Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Similar to UK Digital Curation Centre: enabling research data management at the coalface
Similar to UK Digital Curation Centre: enabling research data management at the coalface (20)
Recently uploaded
Recently uploaded (20)
UK Digital Curation Centre: enabling research data management at the coalface
- 2. UK Digital Curation Centre : enabling research data management at the coalface Dr Liz Lyon Associate Director DCC / Director UKOLN University of Bath, UK
- 6. Diamond Light Source Synchotron National Crystallography Service University of Southampton Local Earth Sciences Lab University of Cambridge Function International service -multiple communities UK service - multiple institutions. Also uses Diamond Lone researcher at institution - uses NCS and ISIS large-scale facility Administration Peer-reviewed proposal required Vetted applications. Electronic & paper-based records –experiments, safety ERA, instrument time Multiple proposals, multiple forms Workflow Formulaic and bespoke Formulaic Complex, unrecorded Software In-house scripts In-house scripts + open-source suite In-house scripts + open-source suite Raw data storage In-house GDA store ATLAS data-store Laptop / local server Derived data storage Taken offsite on laptop / USB stick eCrystals repository Laptop / local server / USB stick Metadata Core Scientific MetaData Model eBank/eCrystals schema ? Identifiers Beam-line number DOI InChI ?
- 7. Research Outputs Citations, References User registration data; Instrument allocation data etc. Comments, annotations, ratings etc. Risk assessment data; other sample data Process & Analyse Derived Data Research Concept and/or Experiment Design Start Project Peer-review Proposal Conduct Experiment Generate, Create, & Collect Raw Data Check & Clean Raw Data Interpret & Analyse Results Data Archive, Preservation & Curation (OAIS conformant; Representation Information etc.) IPR, Embargo & Access Control Discover, Access, Validate, Reuse & Repurpose Data Publish Research Results Data Derived Data Processed Data Raw Data Documentation, Metadata & Storage (Reference, Provenance, Context, Calibration etc.) Acquire Sample Write Proposal (include DMP) Scholarly Knowledge Write Usage Report Research Activity Administrative Activity Curation Activity Information Flow KEY: Peer Review Prepare Manuscript Prepare Supplementary Data Publications Database Publication Activity An Idealised Scientific Research Activity Lifecycle Model Appraisal & Quality Control Programs (generate customised software) Papers, articles, presentations, reports
- 8. Existing work : mappings and gaps Data Management and Provenance (CSMD, OPM?) Bibliographic records (FRBR, SWAP) Curation (OAIS, PREMIS?) DC, Ontologies Software descriptions (??) Slide : Brian Matthews, STFC PROCESS
- 10. Requirements Analysis Report “… it is apparent that the greatest need is for a robust data management infrastructure which supports each researcher in capturing, storing, managing and working with all the data generated during an experiment . Internal sharing of research data amongst collaborating scientists … is also a primary concern as is a requirement for access to research data in the long run so that a researcher … can return to and validate the results well into the future.”
- 12. Incremental Project Report, June 2010 “ 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.” The majority of people felt that some form of policy or guidance was needed.... http://www.flickr.com/photos/mattimattila/3003324844/
- 13. Emerging funder requirements
- 15. http://www.dcc.ac.uk/dmponline DMP Online Currently updating Version 2.0 Version 3.0 summer 2010
- 17. Research Outputs Citations, References User registration data; Instrument allocation data etc. Comments, annotations, ratings etc. Risk assessment data; other sample data Process & Analyse Derived Data Research Concept and/or Experiment Design Start Project Peer-review Proposal Conduct Experiment Generate, Create, & Collect Raw Data Check & Clean Raw Data Interpret & Analyse Results Data Archive, Preservation & Curation (OAIS conformant; Representation Information etc.) IPR, Embargo & Access Control Discover, Access, Validate, Reuse & Repurpose Data Publish Research Results Data Derived Data Processed Data Raw Data Documentation, Metadata & Storage (Reference, Provenance, Context, Calibration etc.) Acquire Sample Write Proposal (include DMP) Scholarly Knowledge Write Usage Report Research Activity Administrative Activity Curation Activity Information Flow KEY: Peer Review Prepare Manuscript Prepare Supplementary Data Publications Database Publication Activity An Idealised Scientific Research Activity Lifecycle Model Appraisal & Quality Control Programs (generate customised software) Papers, articles, presentations, reports
- 18. Data citation, credit, metrics, attribution Incentives?
- 24. Chicago Mart Plaza, 6-8 December 2010 Thank you… www.dcc.ac.uk
Editor's Notes
- Microsoft Research Faculty Summit 2010 © 2010 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION
- Microsoft Research Faculty Summit 2010 © 2010 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION
- The I2S2 project aims to understand and identify the requirements for a data-driven research infrastructure in the Structural Sciences. The work is focused on the exemplar domain of Chemistry, but with a view towards inter-disciplinary application. This Idealised Scientific Research Data Lifecycle Model produced by the I2S2 project seeks to extend and adapt from a “researcher perspective”, the Keeping Research Data Safe (KRDS) Activity Model. It adapts KRDS from an archive-centric to a researcher-centric view by: Defining and emphasising more of the activities in the research (KRDS “Pre-Archive” ) phase where research data is created; Adding a “Publication” set of activities; Concatenating the KRDS “Archive” phase activities in the centre of the model for simplification and presentational purposes; Adding some specific local research administration activities. In addition for the purposes of the project, it adds some selective detail of information flows and information objects between the activities. Note this is an idealised model and several activities such as peer review or conduct experiment may have multiple instances or repetitions. It also represents a project view as of June 2010 and may be subject to further changes.
- The I2S2 project aims to understand and identify the requirements for a data-driven research infrastructure in the Structural Sciences. The work is focused on the exemplar domain of Chemistry, but with a view towards inter-disciplinary application. This Idealised Scientific Research Data Lifecycle Model produced by the I2S2 project seeks to extend and adapt from a “researcher perspective”, the Keeping Research Data Safe (KRDS) Activity Model. It adapts KRDS from an archive-centric to a researcher-centric view by: Defining and emphasising more of the activities in the research (KRDS “Pre-Archive” ) phase where research data is created; Adding a “Publication” set of activities; Concatenating the KRDS “Archive” phase activities in the centre of the model for simplification and presentational purposes; Adding some specific local research administration activities. In addition for the purposes of the project, it adds some selective detail of information flows and information objects between the activities. Note this is an idealised model and several activities such as peer review or conduct experiment may have multiple instances or repetitions. It also represents a project view as of June 2010 and may be subject to further changes.
- Microsoft Research Faculty Summit 2010 © 2010 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION