UKOLN is supported by: - PowerPoint PPT Presentation

About This Presentation
Title:

UKOLN is supported by:

Description:

Monica Duke m.duke_at_ukoln.ac.uk Project Manager, SageCite Project http://blogs.ukoln.ac.uk/sagecite/ #sagecite JISC Digital Preservation Benefits Tools Project ... – PowerPoint PPT presentation

Number of Views:43
Avg rating:3.0/5.0
Slides: 24
Provided by: Monica207
Category:

less

Transcript and Presenter's Notes

Title: UKOLN is supported by:


1
Monica Duke m.duke_at_ukoln.ac.uk Project Manager,
SageCite Project http//blogs.ukoln.ac.uk/sagecite
/ sagecite JISC Digital Preservation Benefits
Tools Project Dissemination workshop Tuesday 12th
July 2011, London South Bank University
UKOLN is supported by
2
Overview
  • What is the SageCite project
  • What is Sage Bionetworks
  • Specifics of this case study
  • Outcomes of applying the tool
  • Next steps
  • What weve learnt

3
  • Citation in the domain of disease network
    modelling
  • Funded August 2010 July 2011

4
SageCite project overview
  • Review of data citation (issues, technology)
  • Understanding the domain
  • Sage Bionetworks partners in project
  • Site visit
  • Documenting processes (workflow tools)

5
SageCite project overview
  • Demonstrator
  • Adding support for data citation
  • Using DataCite services
  • Working with publishers
  • Benefits analysis KRDS Taxonomy

6
Sage Bionetworks overview
  • US-based non-profit organisation
  • Creating a resource for community-based,
    data-intensive biological discovery
  • Community-based analysis is required to build
    accurate models
  • www.sagebase.org

7
Sage data and processes
  • The idealised Sage modelling process can be
    divided into 7 stages
  • 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.

8
(No Transcript)
9
Additional steps for citing data
10
Slide by Jonathan Derry Sage Bionetworks
11
Slide by Lara Mangravite Sage Bionetworks
12
Case Study summary
  • Case Study undertaken by a project
  • Based on an organisation whose main
    business/expertise is science
  • Immature stage of addressing digital asset
    management
  • Citation focus for benefits analysis
  • Earlier version of the Benefits Tools

13
Benefits of Data Citation (Direct)
  • Better discovery of network models
  • citation makes the model explicit and creates a
    link between the model and parameters on which
    discovery services can be based e.g. contributor
    names help in building a service which can find
    all models linked to a specific researcher.
  • Better access
  • a citation can provide information and mechanisms
    to locate and retrieve network models.

14
Benefits of Citation (Indirect)
  • Increasing trust and reproducibility of research
  • Research assessment metrics
  • Assessment is more equitable
  • Improved career development path
  • The public has more trust and belief in the work
    of scientists
  • Enabling more inclusive research metrics
  • improves the range of metrics that are considered.

15
Benefits of citation (Near Term)
  • In the short term, more of the people in the
    value chain producing the models benefit if all
    types of contributions are attributed (more
    equitable attribution)
  • Machine readibility
  • Recognition for contributors as early pioneers in
    data contributions
  • Journal articles are able to provide more of the
    evidence supporting the article. 

16
Slide by Lara Mangravite Sage Bionetworks
17
Benefits of citation (Longer Term)
  • Wider interdisciplinary work
  • the concept of interdisciplinarity will grow but
    that is a longer term benefit
  • Scholarly record enriched for future generations
  • better able to understand development of methods
    and data over time (how we got here) because of a
    stronger evidence base.
  • Longer-term track record and reputation of
    contributors grows over time.
  • Cumulative metrics can be computed and different
    metrics can be devised.

18
Benefits (Internal project)
  • Funders (JISC) citation of data in one domain
    helps to inform future programs and transfer of
    lessons to other domains.
  • Policy makers informs policy on what metrics to
    include in their assessments.
  • Sage bionetwork scientists and network team
    larger range of measures for assigning credit for
    contributions becomes possible.
  • Datacite/BL a complex case study to inform
    technical development Sage Bionetworks for
    improving their infrastructure
  • Nature/PLoS (publishers) papers can be
    validated strengthens the peer-review process a
    stronger evidence base supports the article.

19
Benefits (External)
  • Society better disease treatments in the longer
    term
  • Funders (e.g. Wellcome Trust) enhanced ROI
    cascaded research funding
  • Other scientists able to create metamodels
  • Increased public trust in science
  • public benefits because of diminished bad
    feeling about science
  • science benefits from better public support for
    funding?
  • Other publishers have a model to follow

20
Next steps
  • Validate the analysis with the domain experts
    (ongoing)
  • Update the analysis using the new versions of the
    tools
  • Further (mediated) work on Impact

21
What we have learnt
  • The benefits framework was easy to apply and
    helped articulate benefits
  • An intermediary may be required to facilitate the
    process
  • Digital Management background and motivation
    matters
  • Terminology matters

22
In summary..
  • We have tested the Benefits Framework in one
    domain against one aspect of curation (citation)
  • We have seen positive changes to the tools and
    their documentation
  • More work needed on ability of researchers to use
    the tools directly
  • Validate outcomes of analysis

23
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
Write a Comment
User Comments (0)
About PowerShow.com