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Shareable by Design: Making Better Use of your Research
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Shareable by Design: Making Better Use of your Research


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Presentation on data sharing that outlines five layers that must be addressed to enable data to be located, obtained, access, understood and use, and cited.

Presentation on data sharing that outlines five layers that must be addressed to enable data to be located, obtained, access, understood and use, and cited.

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  • Think of – you have a website where you can enter search criteria and find items that match this search
  • - Accessible - esoteric formats- Understandable - lack of sufficient contextual information, vocabularies- reusable - proprietary technologies
  • ProvenanceDocumentationRights – licence information
  • Transcript

    • 1. Shareable by Design Make better use of your research Gareth Knight This work is licensed under a Creative Commons Attribution 2.0 UK: England & Wales License Gateways to Research 23 September 2013
    • 2. Data Sharing in the News
    • 3. Funder Requirement Expectation that projects will take steps to manage & share data • DM Plan to accompany research proposal • Data created & managed in accordance with relevant standards • Minimum retention period • Strategy for sharing data, indicating when, where and how Funder Requirements for Data Management and Sharing
    • 4. Research Impact Open Data citation benefit (Craig et. al. 2007): • Increased visibility through promotion of paper and data as distinct entities, as well as additional cross-linking • Research considered to be more credible • Papers with available datasets can be used in ways that papers without data Piwowar & Vision (2013): • Papers with associated data receive higher citation (9%) in comparison to those that do not, in study of 10,555 gene expression papers Piwowar H, Vision TJ. (2013) Data reuse and the open data citation advantage. PeerJ PrePrints 1:e1v1 Craig, et al, (2007) Do open access articles have 2 greater citation impact?A critical review of the literature. Journal of Informetrics 1 (3) 239- 3 248
    • 5. Enabling Better Research 1. Recognise all sources Greater clarity on contribution by data creator to research activity 2. Supports research validation Save time when locating and reproducing research findings 3. Supports new research Data can be analysed in new ways & for different purposes: • Piwowar & Vision Gene expression study identified increase in no. of datasets analysed in secondary studies
    • 6. Data Sharing Pyramid Usable Accessible Available Locatable Citable
    • 7. Ability to locate • Publish information in digital form that enables a user to discover: – Existence of dataset – Content & origin of dataset • Referred to as discovery/descriptive metadata • Descriptive information may include: – Creator, Institution, creation date, description, temporal coverage, geographic coverage, rights • Should be possible to find through search engines and relevant portals
    • 8. Ability to obtain • Entire dataset or subset, e.g. Anonymised/non-confidential data • Different access methods: – Public: Available to anyone – Registered: Time-limited access to registered users – Approved: User must state intended use – Contract: User must complete a formal agreement to access & use Make research data available for access to interested parties
    • 9. To Share or not to Share 1. Is the Sharing justified? • What benefits will it provide? • What are the risks associated with sharing data? 2. Do you have the ability to share? • Ability to anonymise • Intellectual Property Rights (IPR) • Participant Consent • Other obligations, e.g. confidentiality 3. Are there any conditions associated with sharing? • What measures need to be in place to protect data? (e.g. record access requests, specific use only) Information Commissioner Office. Data Sharing Code of Practice Information Commissioner Office: Anonymisation Code of Practice
    • 10. Data Rights • Informed Consent – Obtain authorisation from project participants • Clarify rights holders at early stage of project – Ownership rights – Roles & responsibilities, e.g. For long-term management – Permitted access and use • Document in an appropriate form – Standard data licence (e.g. Creative Commons, Open Data Commons License) – Tailored licence form, e.g. Data Transfer Agreement • Particularly important when performing collaborative research involving multiple rights holders Rights issues must be addressed to enable access and use
    • 11. Ability to access Accessible using available software • Is it held in a format that can be imported into a wide-range of software tools? Stored in form that enables analysis Use published standards to encode data, rather than invent your own approach • Simplify cross-analysis of studies • Save times on documentation Address issues that will limit access and use to data “turning [a] PDF into XML is like turning a hamburger into a cow” Peter Murray-Rust on the challenges of extracting data from published research papers UK Data Service: Formatting Data
    • 12. Ability to Use Provide document sufficient to interpret content How is this value calculated? What are the boundaries of this measurement? What does this column refer to? Where and how was this data captured? What processing has been performed? Provide documentation (e.g. Codebook, research protocol) to accompany data 1. Check reqs in your field (e.g. Clinical trials) 2. Look at other collections for inspiration (e.g. Via UK Data Service) 3. Consider Qs that may be raised by a user unfamiliar with research What are the permitted uses of this data?
    • 13. Ability to Cite 1. References, without broken links • Web -based data change location over time, resulting in broken URLs (‘link rot’) • Many persistent identifier schemes exist. Digital Object Identifier (DOI) is preferred standard 2. Research data and citation standards • No formal standard for citing data using Harvard, Vancouver, but many different guides – Author names. Title of resource [medium type]. Host institution name: Physical location; Year of publication [Date accessed]. Available from: Identifier 2. Citation granularity • Referencing intra-object components (e.g. Tables, paragraph) remains a concern Provide structure to identify and acknowledge sources used in research paper
    • 14. Things to remember • To increase research visibility: Publish metadata on research data through an appropriate research portal • To enable access: Evaluate benefits and risks and address barriers to data sharing • To manage access: consider the conditions that need to be met • To encourage uptake and citation: Ensure that your data is easy to access and use • To recognise your sources and credit data creators: Cite the datasets that you use in research papers
    • 15. A Few Useful References • Funder Requirements for Data Management and Sharing • Information Commissioner Office. Data Sharing Code of Practice • Information Commissioner Office: Anonymisation Code of Practice • • MANTRA – Data Management training for PhD students • UK Data Archive – Managing and Sharing Data • LSHTM Information Management support material • Guidelines on good research practice: Implementing research governance: • Information Management and Security Policy:
    • 16. Thank You for your attention! Gareth Knight. RDM Support Service Project Manager Email: Questions