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Research Data at Warwick. “The aim for research data management at Warwick in five years is that it forms an integral element of the overall University.

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Presentation on theme: "Research Data at Warwick. “The aim for research data management at Warwick in five years is that it forms an integral element of the overall University."— Presentation transcript:

1 Research Data at Warwick

2 “The aim for research data management at Warwick in five years is that it forms an integral element of the overall University portfolio of support for Warwick researchers”

3 Background Government and funder principles regarding access to/sharing of research outputs Policies on data and publications – Open Access via payment or repository – Source dataset location given in publication Penalties – Individual/institution ineligible for future funding – Non-inclusion in next REF?

4 Digital Curation Centre Data Lifecycle

5 Current Situation Data produced in all disciplines (but what is data and how to define it?) Good practice in some areas, not in others Stored locally, nationally, disciplinary Fragmented approach No understanding of how much data, what or where Institutional costs unknown

6 Governance and Activity RDM Oversight Group – PVC Chair – Academic/research staff – ITS – Library – RSS Action/Operational Group – ITS – Library – LDC/Student Careers and Skills – RSS – +?

7 …. are quantitative or qualitative data, records, files or other evidence, irrespective of their content or form…that comprise research observations, findings or outcomes. This includes primary materials and analysed data. What constitutes research data varies between disciplines. ‘What is needed to be able to reproduce, test or validate the results of research’ will be a key consideration for the researcher in determining what is research data and therefore what should be registered, managed and preserved. Research Data

8 Warwick RDM Policy (1) Heads of Departments to ensure awareness of the policy and procedures. PIs responsible for ensuring requirements are observed. All researchers expected to observe the policy. Exclusive rights to data should not be given to other bodies. Researchers must prepare and maintain data management plans. All data must be registered whether hosted here or elsewhere.

9 [RDM Policy (2)] Data retained for at least 10 years from the date of any publication, unless funder requirements are longer. Data of interest to future research to be offered for deposit. Data to be made available for access and re- use under the appropriate conditions. If data is not retained it should be disposed of according to University guidelines.

10 [RDM Policy (3)] The University will provide means and services enabling registration, deposit, storage, retention of and access to research data. The University will provide advice, training and support regarding research data management.

11 Digital Curation Centre Institutional Engagement Researcher and support agency workshop Benchmarking surveys – Physics and IER Data Management Plans Online

12 The University Needs An institutional policy and guidelines Central data catalogue Tools to create, record, manage and control data Data storage/preservation strategy and systems Systems for discovery and secure access Collection, preservation and disposal policies Skills development and guidance Resources to manage infrastructure and services Governance mechanism

13 Practical considerations…

14 connecting you with information, support and your community Research Data Management – Practical First Steps IAS-REx Advanced Workshop 1 st March 2013 Yvonne Budden, E-Repositories Manager

15 connecting you with information, support and your community Topics Covered Data management plans Data types Legal and ethical considerations Metadata Data security Data sharing options Sources of advice

16 connecting you with information, support and your community What is Data? Smallest building blocks of your thesis – E.g. a single survey response, an archive document, output of a single experiment Created, observed or collected for the purpose of analysis to validate a research question Can be analogue or digital – Digital data can be ‘born digital’ or ‘made digital’

17 connecting you with information, support and your community Research Data Lifecycle 1. What data will you produce? 2. How will you look after your data? 3. Can you/others understand the data? 4. What data will be deposited and where? 5. How will preserve the data? 1. Create 2. Active use 3. Document 4. Publication & Deposit 5. Preservation & reuse

18 connecting you with information, support and your community Data Management Plans (DMPs) Often required by funders Useful for checking you’ve considered all aspects of your data management Never to late to do one for your research DMP Online (www.dmponline.dcc.ac.uk)www.dmponline.dcc.ac.uk – Based on the checklist from the DCC – Ideal for funding applications

19 connecting you with information, support and your community 1. What data will you produce? What type of data will you produce? – Not just the file format, but how you ‘create’ the data; observational, sampling, text mining etc. How easy is it to create or reproduce? – Is it unique observational data? Will it take 1000’s computer/man hours to recreate? Need to manage the specific risks associated with each type of data

20 connecting you with information, support and your community Who owns the data and is responsible for it? Everyone has a role and should be aware of the guidelines the project is subject to People generating data: – Back up and store data securely – Document data fully Project Leaders: – Make sure you can access all the project’s data – Assess what should be archived and/or published

21 connecting you with information, support and your community Legal and Ethical Principles Plan early in research (during ethical review) Researchers need to consider: – obtaining informed consent for data sharing – protecting identities e.g. anonymisation, not collecting personal data – restricting / regulating access where needed (all or part of data) e.g. by group, use, time period – securely storing personal or sensitive data Consider jointly and in dialogue with participants Key legislation – Data Protection Act (1998)

22 connecting you with information, support and your community 2. How will you look after your data? 3, 2, 1... Backup Test your backups Access (files & backups) – Protect your hardware – At least two people of each file – Use encryption software for sensitive data – Manage passwords with a service like KeePass

23 connecting you with information, support and your community Data Organisation Directory and folder structure File naming conventions – Be consistent! Clear versioning of files

24 connecting you with information, support and your community 3. Can you/others understand the data? Contextual metadata about your data – Literally ‘data about data’ Can be very basic: – E.g. Title, ‘authors’, publication date Subject-specific metadata: – reagent names, experimental conditions, population demographic, how you created the data Use ‘read me’ files to provide information on coded survey responses etc. Credit external data used or other sources

25 connecting you with information, support and your community 4. What data will be deposited and where? Will you share your data? If so where and how? Are you required to share your data? – Either by funders or by publishers? Are there any restrictions on you sharing your data? – Commercially sensitive data, personal data, use of external data sources

26 connecting you with information, support and your community 5. How will you preserve your data? How long do you need to preserve the data? – Short term (e.g. 3-5 years) – Long term (e.g. 10 years) – Indefinite Keep all versions? Just final version? First and last? What are the re-processing costs? – Keep only software and protocol/methodology information Are there tools/software needed to create, process or visualise the data? – Archive these with your data

27 connecting you with information, support and your community File formats for preservation Unencrypted Uncompressed Non-proprietary/patent-encumbered – E.g. avoid Word, Excel, Quicktime Open, documented standard Standard representation (ASCII, Unicode) Examples: PNG, CSV, RTF, HTML

28 connecting you with information, support and your community Final thoughts Data management is important at all stages of a project There are tools available to help you Keep your data safe – Back up your data – Test your back-ups Keep your data organised – Find it – good formats and file names Understand it - check documentation and metadata Consider publishing your data so that you can get recognition for your work

29 connecting you with information, support and your community Acknowledgments Research Data MANTRA [online course] created by EDINA and Data Library, University of Edinburgh (http://datalib.edina.ac.uk/mantra)http://datalib.edina.ac.uk/mantra Padlock image by JPNavarro – (http://jpnavarro.deviantart.com/art/Padlock-in-Despair ) License: CC-BY-NDhttp://jpnavarro.deviantart.com/art/Padlock-in-Despair Desk image by noricum – (http://www.flickr.com/photos/noricum/ /) License: CC-BY-SAhttp://www.flickr.com/photos/noricum/ / Insect in Amber by By Michael S. Engel – (http://commons.wikimedia.org/wiki/File:Leptofoenus_pittfieldae_(male).JPG ) License: CC-BYhttp://commons.wikimedia.org/wiki/File:Leptofoenus_pittfieldae_(male).JPG )

30 connecting you with information, support and your community Thank you and any questions? Yvonne Budden – – – – Ext Also advice on open access, electronic theses and copyright


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