What is-rdm
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The document discusses research data management (RDM), defining it as the systematic handling of data throughout the research lifecycle, highlighting its importance for data discovery, validation, and sharing. It outlines key components of RDM, including planning, creating, documenting, storing, sharing, and preserving data, along with best practices for data management. Additionally, it emphasizes the need for documentation, storage solutions, and engagement with support resources to enhance research outcomes.
What is-rdm
- 1. What is Research Data Management and why does it matter? Sarah Jones & Joy Davidson HATII, University of Glasgow sarah.jones@glasgow.ac.uk joy.davidson@glasgow.ac.uk Funded by: •POPP conference, CCA, Glasgow
- 2. What is research data? All manner of things that you produce in the course of your research
- 3. Defining research data Research data are collected, observed or created, for the purposes of analysis to produce and validate original research results Both analogue and digital materials are 'data' Digital data can be: created in a digital form ("born digital") converted to a digital form (digitised)
- 4. What is research data management? 5. Preservation 1. “the active management and Create & Re-Use appraisal of data over the lifecycle of scholarly and scientific interest” 4. 2. Deposit Active Use PhD & Data Data management is part of 3. Selection & good research practice Evaluation
- 5. Why manage your data well? - so you can find and understand it when needed - to avoid unnecessary duplication - so you can finish your PhD! - to validate results if required - so your research is visible and has impact - to get credit when others cite your work
- 6. What is involved in RDM? - Data management planning - Creating data - Documenting data - Storing data - Sharing data - Preserving data
- 7. Good data management is about making informed decisions
- 9. Data management planning Write a brief plan at the start of your project to define: • how your data will be created? • how it will be documented? • who will access it? • where it will be stored? • who will back it up? • whether (and how) it will be shared & preserved? DMPs are often submitted as part of grant applications, but are useful whenever you’re creating data.
- 10. Data management planning: advice Decide what do you (and others) want to do with the data? make decisions that allow for this Talk to support staff to see which option works best Use the guidance and templates that are available DMP template for PhD students: http://blogs.bath.ac.uk/research360/2012/03/postgraduate- dmp-template-first-draft How to write a DMP: www.dcc.ac.uk/resources/how-guides/develop-data-plan
- 11. Creating data What type and format of data will you create? - formats may be determined by the tools/software you use - common, widespread formats may be better to enable reuse How will you create your data? - What methodologies and standards will you use? - How will you address ethical concerns and protect participants? - Will you control variations to provide quality assurance?
- 12. Creating data: advice Data can take many forms • Still images, video & audio • Notebooks & lab books • Survey results & interview transcripts • Experimental observations • Text corpuses • Models & software • ….
- 13. Good formats for long-term access • Unencrypted • Uncompressed • Non-proprietary/patent-encumbered • Open, documented standard • Standard representation (ASCII, Unicode) Type Recommended Avoid for data sharing Tabular data CSV, TSV, SPSS portable Excel Text Plain text, HTML, RTF Word PDF/A only if layout matters Media Container: MP4, Ogg Quicktime Codec: Theora, Dirac, FLAC H264 Images TIFF, JPEG2000, PNG GIF, JPG Structured data XML, RDF RDBMS •Further examples: http://www.data-archive.ac.uk/create-manage/format/formats-table
- 14. Use existing models Sample consent form from Managing and Sharing Data a guide by UK Data Archive http://data-archive.ac.uk/media/ 2894/managingsharing.pdf
- 15. Documenting data What information do users need to understand the data? - descriptions of all variables / fields and their values - code labels, classification schema, abbreviations list - information about the project and data creators - tips on usage e.g. exceptions, quirks, questionable results How will you capture this? Are there standards you can use?
- 16. Documenting data: advice Document at the time – it’s hard to do later, as you forget Think about how to name, structure & version your files www.jiscdigitalmedia.ac.uk/crossmedia/advice/choosing-a-file-name Record contextual information in a text file (such as a ‘read me’ file) in the same directory as the data Be consistent so your first year data makes sense when you come to write up!
- 17. Storing data What is available to you? What facilities do you need? - remote access to work from home - file sharing with others - high-levels of security for sensitive data How will the data be backed up?
- 18. Storing data: advice Speak to your local IT Team for advice Use managed storage (i.e. the uni network) if possible Remember that all storage is fallible – need to back-up if this is not already done for you (e.g. by uni) - keep 2+ copies on different types of media in different locations - manage back-ups (migrate media, test integrity) Choose appropriate methods to transfer / share data - email, dropbox, ftp, encrypted media, filestore, VREs...
- 19. One copy = risk of data loss •CC image by momboleum on Flickr kr Flic on row n Mor ary y Sh ge b ima •CC
- 20. Sharing & preserving data Are you expected to share / preserve your data? Do you need to destroy some data e.g. because of consent How will you share your data - can anyone help?
- 21. Sharing & preserving data: advice Know what you’re expected to share/preserve (or not!) Use available data centres - http://datacite.org/repolist Share your data where possible - there are benefits! More citations: 69% ↑ (Piwowar, 2007 in PLoS)
- 22. Tips for managing your data Find out what support is available – Speak to the library & local IT support – Ask your supervisor for advice – Check out what facilities are in your department – See what others in your discipline are doing Training course on managing creative arts data www.projectcairo.org/module/unit1-0.html
- 23. Thanks - any questions? For DCC guidance, tools and case studies see: www.dcc.ac.uk/resources Follow us on twitter @digitalcuration and #ukdcc Content for various slides adapted from Research360 project at University of Bath
- 24. Discussion exercise • What types of data are you creating? • What issues do you have in managing your data? – Storage & backup – Accessing data from home – Understanding your data – ... • What have you learnt that may help in the future?
Editor's Notes
- #11: These seem to be the five main questions asked across the board by RCs First link takes you to a document that provides a comparison of what each funder asks for and the DCC link is to our guidance on data planning. We’re also providing an online tool to help in the formulation of data management and sharing plans.
- #16: Think of all the different types of information users (and you!) will need to understand the data in the future. If these aren’t captured at the time it’s very hard to do later. Using standards can make it easier to share / combine data later.
- #17: Think of all the different types of information users (and you!) will need to understand the data in the future. If these aren’t captured at the time it’s very hard to do later. Using standards can make it easier to share / combine data later.