An Introduction to Research Data Management Things To Do With Data – Michaelmas 2014 Slides provided by Research Support Team, IT Services, University of Oxford

What does data include? “A reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing.” Digital Curation Centre Slide adapted from the PrePARe Project

What does data include? Any information you use in your research Slide adapted from the PrePARe Project

What does research data management cover? Storage Organizing Preservation Documenting Sharing Choosing technology Versioning Structuring Backing up Curation Security

Relevant throughout the research process Planning and applying for funding Setting up and starting work Day-to-day work during the project Project conclusion

Carrots and sticks  Enable efficient day- to-day work  More time for the meat of the research process  Avoid problems in the future  University of Oxford Policy on the Management of Research Data and Records  Funding body requirements

University of Oxford policy Introduced July 2012

University of Oxford policy  The full policy can be viewed on the Research Data Oxford websiteResearch Data Oxford  Research data is defined as the information needed ‘to support or validate a research project’s observations, findings or outputs’  Research data should be:  Accurate, complete, identifiable, retrievable, and securely stored  Able to be made available to others

Funders’ requirements  Funding bodies are taking an increasing interest in what happens to research data  You may be required to make data publicly available at the end of a project  Many funders require a data management plan as part of grant applications  RDO website provides a summary of requirementssummary of requirements

Setting up and starting work Day-to-day work during the project Project conclusion

Data management plans  A document created early on in a project  While planning, applying for funding, or setting up  An initial plan may be expanded later  Details plans and expectations for data  Nature of data and its creation or acquisition  Storage and security  Preservation and sharing

Benefits of data management plans  Ask key questions before problems arise  Have time to look for solutions  Saves time and reduces stress  Many tasks are straightforward if planned from the beginning, but much harder in retrospect  A framework for ongoing review of data management practices

DMP Online  Online data management planning tool  Can be customized according to funding body

Planning and applying for funding Day-to-day work during the project Project conclusion

What storage media are in use? How about file formats? Slide adapted from the PrePARe Project

Storage  Departmental IT support may be able to provide server space or a shared drive  IT Services’ NSMS offers server rental and management, storage on the University’s private cloud, and other storage solutionsNSMS

Data security  Is there data that needs special treatment?  Sensitive or confidential information  Commercial potential  InfoSec at IT Services can provide advice – see for more detailshttp://

Backing up is easier than replacing lost data… Slide adapted from the PrePARe Project

LOCKSS – Lots Of Copies Keeps Stuff Safe Keep copies in different places Can the process be automated? Slide adapted from the PrePARe Project

IT Services: data back-up on the HFS  HFS is Oxford’s central back-up and archiving service HFS  Free of charge to University staff and postgraduates  Automated back-ups of machines connected to University network  Copies kept in multiple places

Choosing the right tools for the job  Are current software and methods meeting your needs?  Sticking with old familiars can be false economy  Ask friends and colleagues for recommendations

Tools and technologies for managing data  Spreadsheets may be fine for small, straightforward tasks  More complex projects might benefit from a relational database  Microsoft Access, FileMaker Pro, etc.  Or a qualitative data analysis package  Nvivo, Atlas.ti, etc.  Or an XML database...

ORDS – Online Research Database Service  Specifically designed for academic research data  Cloud-hosted and automatically backed up  Web interface makes collaboration straightforward  If desired, databases can easily be made public  Designed to permit easy archiving  Launched in the summer of 2014 

Other data management tools and systems  LabTrove – an electronic lab notebook system LabTrove  NeuroHub – an information environment for managing data from lab-based research NeuroHub  DataStage – a secure personalized file management environment DataStage  myExperiment – record and share scientific workflows myExperiment  Taverna – for managing scientific workflows Taverna

Research Skills Toolkit  Website and hands- on workshops  A guide to software, University services, and other tools and resources for research

Planning and applying for funding Setting up and starting work Project conclusion

What’s obvious now might not be in a few months, years, decades… Adapted from ‘Clay Tablets with Linear B Script’ by Dennis, via Flickr: / / MAKE SURE YOU CAN UNDERSTAND IT LATER Slide adapted from the PrePARe Project

Documentation and metadata  Documentation is the contextual information required to make data intelligible and aid interpretation  A users’ guide to data  May be given at study level or data level  Metadata is similar, but usually more structured  Conforms to set standards  Machine readable 2014 HBS Survey Results Joe Bloggs

M. Farinelli et al. (2012) PLoS ONE 7(3): e34047 Who created the data, when and why Description of the item Methodology and methods Units of measurement Definitions of jargon, acronyms and code References to related data Documentation – what needs to be included Slide adapted from the PrePARe Project

Maintaining consistency  Agree a set of standard working practices as early as possible in a project  Method of recording what’s been done to data – and who did it  File naming conventions  Version information  Have these clearly documented, and store the documentation centrally

Planning and applying for funding Setting up and starting work Day-to- day work during the project

Long term solutions  Data repositories or archives offer a secure long-term home for research data  Data can be embargoed if needed  Databib and Re3Data.org offer searchable catalogues of repositories DatabibRe3Data.org  Figshare offers a DIY option Figshare

ORA-Data (formerly known as DataBank)  University of Oxford’s institutional data archive  Will work alongside ORA-Publications to form a composite University archive  Long term preservation for datasets without another natural home  Plus records for data archived elsewhere

Planning ahead  Data sharing needs to be planned from the beginning of a project  With sensitive data, consent may be needed  Third party data may come with restrictions  If data is destined for a particular archive, they may have specific requirements  Do they use a specific metadata schema, for example?

Data licensing  A licence clarifies the conditions for accessing and making use of a dataset  User knows what’s allowed without asking further permission  Doesn’t exclude possibility of specific requests to go beyond the terms of the licence  Licences used for data include Creative Commons and Open Data CommonsCreative CommonsOpen Data Commons

Further resources

Digital Curation Centre A national service providing advice and resources for the whole research data lifecycle

UK Data Archive  Largest UK collection of social sciences and humanities data  Advice on best practice for creating, preparing, storing and sharing data

IT Services: Research Support Team  Can assist with technical aspects of research projects at all stages of the project lifecycle  Help with DMPs, selecting software or storage, modelling data, etc.  But the earlier you seek advice, the better  For more information, see:

Research Data Oxford website  Oxford’s central advisory website  University policy is available  Questions?

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Rights and re-use  This presentation is part of a series of research data management training resources prepared by the Research Support Team at IT Services, University of Oxford.Research Support Team  Parts of this slideshow draw on material produced as part of the Oxford-based DaMaRO Project, and on resources produced by the PrePARe ProjectDaMaRO Project PrePARe Project  With the exception of clip art used with permission from Microsoft, and commercial logos and trademarks, and images specifically credited to other sources, the slideshow is made available under a Creative Commons Attribution Non-Commercial Share-Alike LicenseMicrosoft Creative Commons Attribution Non-Commercial Share-Alike License  Within the terms of this licence, we actively encourage sharing, adaptation, and re-use of this material