UKOLN is supported by:

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Monica Duke m.duke_at_ukoln.ac.uk Project Manager,
SageCite Project http//blogs.ukoln.ac.uk/sagecite
/ sagecite Developing Data Attribution and
Citation Practices and Standards An International
Symposium and Workshop August 22-23, 2011
UKOLN is supported by
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• Citation in the domain of disease network
  modelling
• Funded August 2010 July 2011

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SageCite project overview

• Review of data citation (issues, technology)
• Understanding the domain
• Sage Bionetworks partners in project
• Site visit
• Documenting processes (workflow tools)

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SageCite project overview

• Demonstrator
• Adding support for data citation
• Using DataCite services
• Working with publishers
• Benefits analysis KRDS Taxonomy

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www.sagebase.org

• US-based non-profit organisation
• Creating a resource for community-based,
  data-intensive biological discovery
• Community-based analysis is required to build
  accurate model

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www.sagebase.org

• US-based non-profit organisation
• Creating a resource for community-based,
  data-intensive biological discovery
• Community-based analysis is required to build
  accurate models

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Slide by Lara Mangravite Sage Bionetworks
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Sage data and processes

• Idealised 7-stage process
• A combination of phenotypic, genetic, and
  expression data are processed to determine a list
  of genes associated with diseases
• Different people are responsible for different
  stages of the modelling process. One person
  oversees the whole process.

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• Stage 1 Data Curation
• basic data validation to ensure integrity and
  completeness
• datasets include microarray data and clinical
  data.  
• ensures that the format of the data is understood
  and the required metadata is present.

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Agreeing standards to support sharing

• Derry J et. al Developing predictive Molecular
  Maps of Human Disease through Community-based
  Modeling.
• http//precedings.nature.com/documents/5883/versio
  n/1/files/npre20115883-1.pdf

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Workflow capture using Taverna http//www.vimeo.co
m/27287109

• Documenting data processes through workflow tools
  
• supports better citation
• makes the cited resource more re-usable
• strengthening the reproducibility and validation
  of the research.

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Data Citation Purposes

• For attribution
• Leading to credit and reward
• For reproducibility
• Supports validation, re-use
• Eric Schadt at Sage Bionetworks Congress 2011
• http//fora.tv/2011/04/16/Eric_Schadt_Map_Building
  (start at 4.28)

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Open challenges attribution

• Preserving link with original data
• Some discipline-based repositories have their own
  identifiers
• Bi-directional links
• Attributing data creators
• including individuals?
• Defining creation of new intellectual object e.g.
  curated dataset?
• Cultural challenge in recognising non-standard
  contributions microattribution
• New metrics
• Identification of contributors

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Open challenges reproducibility

• Identification and granularity
• Discipline identifiers, global identifiers
• How much value has been added since the data
  entered the workflow?
• Identifying processes and software

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Acknowledgements

• University of Manchester
• Carole Goble
• Peter Li
• British Library
• Max Wilkinson
• Tom Pollard
• Sage Bionetworks

• UKOLN
• Liz Lyon
• Monica Duke
• Nature Genetics
• Myles Axton
• PLoS Comp Bio
• Phil Bourne