Lunchtime Seminar Series – digestible bites of knowledge on data and computing tools at the University of Edinburgh

For 2023/2024, Digital Research Services have organised a new iteration of the Lunchtime Seminar Series. These one-hour hybrid seminars will examine different slices of the research lifecycle and introduce you to the data and computing expertise at the University of Edinburgh.

The seminars have been designed to answer the most common questions we get asked, offering valuable bite-sized learning opportunities for research staff, postgraduate research students, and professional staff alike. You will gain an understanding of how digital research fits in with wider research support teams and good research practices. Your sessions will cover research funding, research planning, tailored skill development, data management and advancements in AI.

Oh, and did we mention there is free lunch for in-person attendees? That is truly the cherry on top.

DRS Lunchtime Seminars – 2024 Calendar

Have a look at the upcoming seminars:

Seminar 1: How to plan and design your research project better.                        22nd January 12:00 – 13:00

This session is all about making sure researchers head off with a strong start. Did you know that the University has tools that help you optimise your data management plan, with funder specific templates and in-house feedback? We will make sure you get the best use out of DMPOnline and the Resource Finder Tool. We will also introduce you to some key concepts in data management planning, research funding and digital skill development.

Seminar 2: How to store and organise your data properly.                                    27th February 12:30-13:30.

Discover how to best store and organise your data using University of Edinburgh’s tools: DataStore, DataSync and GitLab. If you work in a wet lab, you might be particularly interested in electronic lab notebooks. We will introduce you to the functionalities of RSpace and protocols.io. Finally, the University has just launched an institutional subscription to the Open Science Framework (OSF). You will discover that it is much more than a tool for data storage, as it can help manage complex workflows and projects as well.

Seminar 3: How to interpret and analyse your data efficiently.                              13th March 12:00-13:00

This seminar is mainly about big computers, such as UoE’s Eddie and Eleanor. Through EPCC, researchers can get also access to large scale national supercomputers, such as Archer and Cirrus. At the same time, we will show a glimpse on some developments on the AI front.

Seminar 4: How to manage, publish, share and preserve your work effectively.  2nd April 12:00-13:00

The final seminar is all about making sure your work is published and preserved in the best way. We will talk you through different (open access) publishing pathways such as Journal Checker, Edinburgh Research Archive, Read & Publish journal list, Edinburgh Diamond. We will also be talking about data repositories (e.g. DataVault, DataShare) and our research output portal, Pure.

For info and booking:
https://digitalresearchservices.ed.ac.uk/training/drs-seminars

Blog post by Dr Sarah Janac                                                                     
Research Facilitator – The University of Edinburgh

University of Edinburgh’s new Research Data Management Policy

Following a year-long consultation with research committees and other stakeholders, a new RDM Policy (www.ed.ac.uk/is/research-data-policy) has replaced the landmark 2011 policy, authored by former Digital Curation Centre Director, Chris Rusbridge, which seemed to mark a first for UK universities at the time. The original policy (doi: 10.7488/era/1524) was so novel it was labeled ‘aspirational’ by those who passed it.

"Policy"

CC-BY-SA-2.0, Sustainable Economies Law Centre, flickr

RDM has come a long way since then, as has the University Research Data Service which supports the policy and the research community. Expectation of a data management plan to accompany a research proposal has become much more ordinary, and the importance of data sharing has also become more accepted in that time, with funders’ policies becoming more harmonised (witness UKRI’s 2016 Concordat on Open Research Data).

What has changed?

Although a bit longer (the first policy was ten bullet points and could fit on a single page!), the new policy adds clarity about the University’s expectations of researchers (both staff and students), adds important concepts such as making data FAIR (explanation below) and grounding concepts in other key University commitments and policies such as research integrity, data protection, and information security (with references included at the end). Software code, so important for research reproducibility, is included explicitly.

CC BY 2.0, Big Data Prob, KamiPhuc on flickr

Definitions of research data and research data management are included, as well as specific references to some of the service components that can help – DMPOnline, DataShare, etc. A commitment to review the policy every 5 years, or sooner if needed, is stated, so another ten years doesn’t fly by unnoticed. Important policy references are provided with links. The policy has graduated from aspirational – the word “must” occurs twelve times, and “should” fifteen times. Yet academic freedom and researcher choice remains a basic principle.

Key messages

In terms of responsibilities, there are 3 named entities:

  • The Principle Investigator retains accountability, and is responsible as data owner (and data controller when personal data are collected) on behalf of the University. Responsibility may be delegated to a member of a project team.
  • Students should adhere to the policy/good practice in collecting their own data. When not working with data on behalf of a PI, individual students are the data owner and data controller of their work.
  • The University is responsible for raising awareness of good practice, provision of useful platforms, guidance, and services in support of current and future access.

Data management plans are required:

  • Researchers must create a data management plan (DMP) if any research data are to be collected or used.
  • Plans should cover data types and volume, capture, storage, integrity, confidentiality, retention and destruction, sharing and deposit.
  • Research data management plans must specify how and when research data will be made available for access and reuse.
  • Additionally, a Data Protection Impact Assessment is required whenever data pertaining to individuals is used.
  • Costs such as extra storage, long-term retention, or data management effort must be addressed in research proposals (so as to be recovered from funders where eligible).
  • A University subscription to the DMPOnline tool guides researchers in creating plans, with funder and University templates and guidance; users may request assistance in writing or reviewing a plan from the Research Data Service.

FAIR data sharing is more nuanced than ‘open data’:

  • Publicly funded research data should be made openly available as soon as possible with as few restrictions as necessary.
  • Principal Investigators and research students should consider how they can best make their data FAIR in their Data Management Plans (findable, accessible, interoperable, reusable).
  • Links to relevant publications, people, projects, and other research products such as software or source code should be provided in metadata records, with persistent identifiers when available.
  • Discoverability and access by machines is considered as important as access by humans. Standard open licences should be applied to data and code deposits.

Use data repositories to achieve FAIR data:

  • Research data must be offered for deposit and retention in a national or international data service or domain repository, or a University repository (see next bullet).
  • PIs may deposit their data for open access for all (with or without a time-limited embargo) in Edinburgh DataShare, a University data repository; or DataVault, a restricted access long-term retention solution.
  • Research students may deposit a copy of their (anonymised) data in Edinburgh DataShare while retaining ownership.
  • Researchers should add a dataset metadata record in Pure to data archived elsewhere, and link it to other research outputs.
  • Software code relevant to research findings may be deposited in code repositories such as Gitlab or Github (cloud).

Consider rights in research data:

  • Researchers should consider the rights of human subjects, as well as citizen scientists and the public to have access to their data, as well as external collaborators.
  • When open access to datasets is not legal or ethical (e.g. sensitive data), information governance and restrictions on access and use must be applied as necessary.
  • The University’s Research Office can assist with providing templates for both incoming and outgoing research data and the drafting and negotiation of data sharing agreements.
  • Exclusive rights to reuse or publish research data must not be passed to commercial publishers.

Robin Rice
Data Librarian and Head, Research Data Support
Library & University Collections

End of an era – 2017-2020 RDM Roadmap Review (part 1)

Looking back on three years that went into completing our RDM Roadmap in this period of global pandemic and working from home, feels a bit anti-climactic. Nevertheless, the previous three years have been an outstanding period of development for the University’s Research Data Service, and research culture has changed considerably toward openness, with a clearer focus on research integrity. Synergies between ourselves as service providers and researchers seeking RDM support have never been stronger, laying a foundation for potential partnerships in future.

thumbnail image of poster

FAIR Roadmap Review Poster

A complete review was written for the service steering group in October last year (available on the RDM wiki to University members). This was followed by a poster and lightning talk prepared for the FAIR Symposium in December where the aspects of the Roadmap that contributed to FAIR principles of research data (findable, accessible, interoperable, reusable) were highlighted.

The Roadmap addressed not only FAIR principles but other high level goals such as interoperability, data protection and information security (both related to GDPR), long-term digital preservation, and research integrity and responsibility. The review examined where we had achieved SMART-style objectives and where we fell short, pointing to gaps either in provision or take-up.

Highlights from the Roadmap Review

The 32 high level objectives, each of which could have more than one deliverable, were categorised into five categories. In terms of Unification of the Service there were a number of early wins, including a professionally produced short video introducing the service to new users; a well-designed brochure serving the same purpose; case study interviews with our researchers also in video format – a product of a local Innovation Grant project; and having our service components well represented in the holistic presentation of the Digital Research Services website.

Gaps include the continuing confusion about service components starting with the name ‘Data’___ [Store, Sync, Share, Vault]; the delay of an overarching service level definition covering all components; and the ten-year old Research Data Policy. (The policy is currently being refreshed for consultation – watch this space.)

A number of Data Management Planning goals were in the Roadmap, from increasing uptake, to building capacity for rapid support, to increasing the number of fully costed plans, and ensuring templates in DMPOnline were well tended. This was a mixed success category. Certainly the number of people seeking feedback on plans increased over time and we were able to satisfy all requests and update the University template in DMPOnline. The message on cost recovery in data management plans was amplified by others such as the Research Office and school-based IT support teams, however many research projects are still not passing on RDM costs to the funders as needed.

Not many schools or centres created DMP templates tailored to their own communities yet, with the Roslin Institute being an impressive exception; the large majority of schools still do not mandate a DMP with PhD research proposals, though GeoSciences and the Business School have taken this very seriously. The DMP training our team developed and gave as part of scheduled sessions (now virtually) were well taken up, more by research students than staff. We managed to get software code management into the overall message, as well as the need for data protection impact assessments (DPIAs) for research involving human subjects, though a hurdle is the perceived burden of having to conduct both a DPIA and a DMP for a single research project. A university-wide ethics working group has helped to make linkages to both through approval mechanisms, whilst streamlining approvals with a new tool.

In the category of Working with Active Data, both routine and extraordinary achievements were made, with fewer gaps on stated goals. Infrastructure refreshment has taken place on DataStore, for which cost recovery models have worked well. In some cases institutes have organised hardware purchases through the central service, providing economies of scale. DataSync (OwnCloud) was upgraded. Gitlab was introduced to eventually replace Subversion for code versioning and other aspects of code management. This fit well with Data and Software Carpentry training offered by colleagues within the University to modernise ways of doing coding and cleaning data.

A number of incremental steps toward uptake of electronic notebooks were taken, with RSpace completing its 2-year trial and enterprise subscriptions useful for research groups (not just Labs) being managed by Software Services. Another enterprise tool, protocols.io, was introduced and extended as a trial. EDINA’s Noteable service for Jupyter Notebooks is also showcased.

By far and away the most momentous achievement in this category was bringing into service the University Data Safe Haven to fulfil the innocuous sounding goal of “Provide secure setting for sensitive data and set up controls that meet ISO 27001 compliance and user needs.” An enormous effort from a very small team brought the trusted secure environment for research data to a soft launch at our annual Dealing with Data event in November 2018, with full ISO 27001 standard certification achieved by December 2019. The facility has been approved by a number of external data providers, including NHS bodies. Flexibility has been seen as a primary advantage, with individual builds for each research project, and the ability for projects to define their own ‘gatekeeping’ procedures, depending on their requirements. Achieving complete sustainability on income from research grants however has not proven possible, given the expense and levels of expertise required to run this type of facility. Whether the University is prepared to continue to invest in this facility will likely depend on other options opening up to local researchers such as the new DataLoch, which got its start from government funding in the Edinburgh and South East Scotland region ‘city deal’.

As for gaps in the Working with Data category, there were some expressions of dissatisfaction with pricing models for services offered under cost recovery although our own investigation found them to be competitively priced. We found that researchers working with external partners, especially in countries with different data protection legislation, continue to find it hard work to find easy ways to collaborate with data. Centralised support for databases was never agreed on by the colleges because some already have good local support. Encryption is something that could benefit from a University key management system but researchers are only offered advice and left to their own mechanisms not to lose the keys to their research treasures; the pilot project that colleagues ran in this area was unfortunately not taken forward.

In part 2 of this blog post we will look at the remaining Roadmap categories of Data Stewardship and Research Data Support.

Robin Rice
Data Librarian and Head of Research Data Support
Library and University Collections

Research Data Training: Semester Two, 2020/21

As we are still facing significant restrictions on movement and in-person events during the whole of semester 2 we have decided to continue offering our RDM (Research Data Management) training courses online only. Details of the upcoming courses are below.

For undergraduate and taught masters students we have a new course called Data Mindfulness: Making the most of your dissertation, which can be enroled on via Learn on MyEd. Alternatively the videos and workbook are available on our training page.

Our online, self-paced RDM training course, Research Data MANTRA, has also been undergoing a significant update, which will be the subject of a future blog post – it is openly accessible at https://mantra.edina.ac.uk.

Full details about each course are on our training webpage https://www.ed.ac.uk/information-services/research-support/research-data-service/training

Workshop Audience Date Time Booking Link
Writing A Data Management Plan for Your Research (RDS002) Research Staff 24th March 2021 09:30 – 11:30 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleId=44117
Writing A Data Management Plan for Your Research (RDS002) All Staff & PGR’s 13th April 2021 10:00 – 12:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44862
Working with Personal and Sensitive Data (RDS003) Research Staff 15th April 2021 09:30 – 11:30 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleId=44118
Realising the Benefits of Good Research Data Management (RDS001) All Staff & PGR’s 21 & 22 April 2021 13:30 – 15:00 Part 1 – https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44856

Part 2 – ttps://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44861

Edinburgh DataVault: supporting users archiving their research data (RDS008) Support staff 22nd April 2021 10:30 – 12:00 https://www.events.ed.ac.uk/index.cfm?event=showEventDetails&scheduleId=44924
Working with Personal and Sensitive Data (RDS003) All Staff & PGR’s 26th April 2021 14:00 – 16:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=44863
Realising the Benefits of Good Research Data Management (RDS001) Research Staff 04 & 05 May 2021 13:30 – 15:00 Contact IAD directly https://www.ed.ac.uk/institute-academic-development

The following courses will not run during semester 2, but we plan to relaunch them as soon possible. In the meantime if you need any support just get in touch with us via data-support@ed.ac.uk and we’ll be happy to help.

  • Data Cleaning with OpenRefine (RDS004)
  • Handling Data Using SPSS (RDS005)
  • Assessing Disclosure Risk in Quantitative Data (RDS006)
  • Assessing Data Quality in Quantitative Data (RDS007)
  • Introduction to Visualising Data in ArcGIS (RDS011)
  • Introduction to Visualising Data in QGIS (RDS012)

A final note, the Research Data Management and Sharing MOOC which we launched with the University of North Carolina in 2016 has enjoyed its most successful period during the pandemic, with people wanting to reskill for the digital world. Over 2,700 learners have successfully completed the 5 week course and passed assessments, with over 25,000 people engaging with the highly rated course since the beginning.

Kerry Miller
Research Data Support Officer
Library and University Collections