Dealing with Data 2019 (January 2020): Collaboration Across the Nations

Picture the scene: A cold January day, the wind blowing the scarves of the passers-by through the large windows of the Informatics Forum meeting room. The group inside listens, takes notes, tweets, and asks questions of the speakers, representing a range of disciplines across the University…

Dealing with Data is an annual event hosted by the Research Data Service. Its aim is to engage the University community of researchers and support professionals around a theme, to share success stories and challenges in the myriad, everyday issues involved with data-driven research. The theme this year reflected the difficulty of managing research data in large, collaborative projects. Due to industrial action, the original November event was postponed to January. Around a hundred researchers – staff and students – participated, along with support staff who gave lightning talks about research-focused services. Full presentations and videos are now available.

So Benjamin Bach, our keynote speaker, inspired us with state of the art data visualisation software and techniques for both exploration and presentation. But he also illustrated the difficulties of portraying all of the data in all of its facets of a rich dataset, and the consequences of making necessary choices for its interpretation.
The first session began with Tamar Israeli’s study of researchers’ use of collaborative and institutional tools showed the challenges of making local infrastructure user friendly enough to attract new users familiar with slick cloud-based services. Then Mark Lawson demonstrated his ingenuous ‘ethical hacking’ to piece together a set of APIs to create a research workflow for samples and images for histology research. Minhong Wang conveyed a higher level view of data management focused not just on data-driven, but knowledge-driven phenotyping.

Next were the lively lightning talks, in which Mike Wallis of Research Services warned of a new Digital Dark Age, and David Creighton-Offord spoke of the dillemmas in Information Security user support where shiny doesn’t always equal safe. Lisa Otty spoke of innovative training and text mining projects bringing data science to the Humanities, and Rory MacNeil demonstrated how the RSpace electronic lab notebook can connect to a host of popular open science tools.

Following a lively lunch with chat between delegates and with hosts of the service exhibitions, Alex Hutchison showed a highly programmatic view of data management and ethics control from the UNICEF collaboration, in collecting and analysing real world data about children in need. Caileen Gallagher offered a case study of how food courier data could be used to empower workers. Sanja Badanjak shared her data integration problems of peace agreements around the world, conveying both innovative solutions and time-consuming workarounds.

In the final session Edward Wallace brought in the Edinburgh Carpentries to the rescue of poor data skills within Biological Sciences and the wider University – itself a great example of cross-community collaboration building a community of trainers. Gillian Raab showed us how any data problem however intractable can be solved by resourcefulness and determination, making use of DataShield for multi-party computation when datasets are too sensitive to be shared. Johnny Hay and Tomasz Zielinski demo’d their Plasmo ‘boutique repository’ for plant-systems biology modelling and Holly Tibble described tackling an international collaboration in linking administrative datasets via ‘ridiculously detailed’ statistical analysis plans. Representing the Research Data Service, I wrapped up proceedings with some of these very observations.
Both presentations and videos are available.


  • Jeremy Upton, Director of Library and University Collections. [Presentation]


  • Data Visualization for Exploration and Presentation, Prof. Benjamin Bach. Lecturer in Design Informatics and Visualization. [Presentation] [Slides]

Session 1 – Chair: Theo Andrew

  • “Data Something”: Assessing Tools, Services and Barriers for Research Data Collaboration at the University of Edinburgh – a small-scale study carried out by Dr Tamar Israeli with support from the Research Data Support team. Robin Rice – Data Librarian & Head of Research Data Support Services. [Presentation] [Slides]
  • Integrated secure web application to deliver centralised management of research samples, histology services and imaging data. Mark Lawson, Data & Project Manager, MRC Centre for Reproductive Health, QMRI. [Presentation] [Slides]
  • Building the Knowledge Graph for UK Health Data Science Minhong Wang et. al, Deanery of Molecular, Genetic and Population Health Sciences. [Presentation] [Slides]

Session 2 – Chair: Kerry Miller

  • The Data Opportunities & Challenges when Collaborating across Organisations
    Alex Hutchison, Delivery Director – Data for Children Collaborative with UNICEF. [Presentation] [Slides]
  • Restoring Gig Workers to Power: Personal Data Portability, Supply of Digital Content and Free Flow of Data in the European Data Economy. Cailean Gallagher, Scottish Trades Union Congress, & St Andrews University Institute of Intellectual History. [Presentation] [Slides]
  • Dealing with data in peace and conflict research. Sanja Badanjak, Postdoctoral Research Fellow, School of Law. [Presentation] [Slides]

Session 3 – Chair: Robin Rice

  • Bringing researchers to data: computing skills training with Edinburgh Carpentries.
    Edward Wallace, Sir Henry Dale Fellow, Institute of Cell Biology. [Presentation] [Slides]
  • Running an analysis of combined data when the individual records cannot be combined. Gillian M Raab and Chris Dibben, Scottish centre for Administrative Data Research. [Presentation] [Slides]
  • The grant is dead, long live the data. Johnny Hay and Tomasz Zieliński, School of Biology, University of Edinburgh. [Presentation] [Slides]
  • International collaborations using linked administrative data: Lessons from the MARIC study. Holly Tibble, Usher Institute, University of Edinburgh. [Presentation] [Slides]

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


Research Data Workshops: Electronic Notebooks Summary of Feedback

In the spring of this year (March & May) the Research Data Service ran two workshops on Electronic Notebooks (ENs) where researchers from all three colleges were invited to share their experiences of using ENs with other researchers. Presentations and demos were given on RSpace, Benchling, Jupyter Notebooks, WikiBench, and Lab Archives. Almost 70 research and support staff attended and participated in the discussions.

This post is a distillation of those discussions and we will use them to inform our plans around Electronic Notebooks over the coming year. It was obvious from the level of attendance and engagement with the discussions that there was quite a lot of enthusiasm for the idea of adopting ENs across a variety of different schools and disciplines. However, it also quickly became clear that many researchers and support staff had quite justified reservations about how effectively they could replace traditional paper notebooks. In addition to the ENs which were the subject of presentations a number of other solutions were also discussed, including; LabGuru, OneNote, SharePoint, and Wikis.

It appears that across the University there are a very wide range of platforms being used, and not all of them are intended to serve the function of an EN. This is unsurprising as different disciplines have different requirements and an EN designed for the biological sciences, such as Benchling, is unlikely to meet the needs of a researcher in veterinary medicine or humanities. There is also a huge element of personal preference involved, some researchers wish a simple system that will work straight out of the box while others want something more customisable and with greater functionality for an entire lab to use in tandem.

So, within this complex and varied landscape are there any general lessons we can learn? The answer is “Yes” because regardless of platform or discipline there are a number of common functions an EN has to serve, and a number of hurdles they will have to overcome to replace traditional paper lab books.

Firstly, let’s look at common functional requirements:

  1. Entries in ENs must be trustworthy, anyone using one has to be confident that once an entry is made it cannot be accidentally deleted or altered. All updates or changes must be clearly recorded and timestamped to provide a complete and accurate record of the research conducted and the data collected. This is fundamental to research integrity and to their acceptance by funders, or regulators as a suitable replacement for the traditional, co-signed, lab books.
  2. They must make sharing within groups and between collaborators easier – it is, in theory, far easier to share the contents of an EN with interested parties whether they are in the same lab or in another country. But in doing so they must not make the contents inappropriately available to others, security is also very important.
  3. Integration is the next requirement, any EN should be able to integrate smoothly with the other software packages that a researcher uses on a regular basis, as well as with external (or University central) storage, data repositories, and other relevant systems. If it doesn’t do this then researchers may lose the benefits of being able to record, view, and analyse all of their data in one place, and the time savings from being able to directly deposit data into a suitable repository when a project ends or a publication is coming out.
  4. Portability is also required, it must be possible for a researcher to move from one EN platform to another if, for example, they change institutions. This means they need to be able to extract all of their entries and data in a format that can be understood by another system and which will still allow analysis. Most ENs support PDF exports which are fine for some purposes, but of no use if processing or analysis is desired.
  5. Finally, all ENs need to be stable and reliable, this is a particular issue with web based ENs which require an internet connection to access and use the EN. This is also an area where the University will have to play a significant role in providing long-term and reliable support for selected ENs. They also need the same longevity as a paper notebook, the records they contain must not disappear if an individual leaves a group, or a group moves to another EN platform.

Secondly, barriers to adoption and support required:

  1. Hardware:
    1. Many research environments are not suitable for digital devices, phones / tablets are banned from some “wet” labs on health and safety grounds. If they are allowed in the lab they may not be allowed out again, so space for storage and charging will need to be found. What happens if they get contaminated?
    2. Field based research may not have reliable internet access so web based platforms wouldn’t work.
    3. There is unlikely to be space in most labs for a desktop computer(s).
    4. All of this means there will still be a need for paper based notes in labs with later transfer to the EN, which will result in duplication of effort.
  1. Cost:
    1. tablets and similar are not always an allowable research expense for a grant, so who will fund this?
    2. if the University does not have an enterprise licence for the EN a group uses they will also need to find the funds for this
    3. additional training and support my also be required
  2. Support:
    1. technical support for University adopted systems will need to be provide
    2. ISG staff will need to be clear on what is available to researchers and able to provide advice on suitable platforms for different needs
    3. clear incentives for moving to an EN need to be communicated to staff at all levels
    4. funders, publishers, and regulatory bodies will also need to be clear that ENs are acceptable for their purposes

So, what next? The Research Data Support service will now take all of this feedback and use it to inform our future Electronic Notebook strategy for the University. We will work with other areas of Information Services, the Colleges, and Schools to try to provide researchers in all disciplines with the information they need to use ENs in ways that make their research more efficient and effective. If you have any suggestions, comments, or questions about ENs please visit our ENs page ( You can also contact us on

The notes that were taken during both events can be read here Combined_discussion_notes_V1.2

Some presentations from the two workshops are available below, others will be added when they become available:

Speaker(s) Topic Link
Mary Donaldson (Service Coordinator, Research Data Management Service, University of Glasgow) Jisc Research Notebooks Study Mary_Donaldson_ELN_Jisc
Ralitsa Madsen (Postdoctoral Research Fellow, Centre for Cardiovascular Science) RSpace 2019-03-14_ELN_RSpace_RRM
Uriel Urquiza Garcia (Postdoctoral Research Associate, Institute of Molecular Plant Science) Benchling
Yixi Chen (PhD Student, Kunath Group, Institute for Stem Cell Research) Lab Archives 20190509_LabArchives_Yixi_no_videos
Andrew Millar (Chair of Systems Biology) WikiBench
Ugur Ozdemir (Lecturer – Quantitative Political Science or Quantitative IR) Jupyter Notebooks WS_Talk
James slack & Núria Ruiz (Digital Learning Applications and Media) Jupyter Notebooks for Research Jupyter_Noteable_Research_Presentation

Kerry Miller, Research Data Support Officer, Research Data Service


DwD2018 – Videos now on Media Hopper

Dealing with Data 2018 was once again a great success in November last year with over 100 university staff and Post-Graduate students joining us to hear presentations on topics as diverse as sharing data in clinical trials and embedding sound files in linguistics research papers.

As promised the videos of each presentation have now been made publicly available on Media Hopper (, while the PDFs can be found on You can also read Martin Donnelly’s reflections on the day

We hope that these will prove both useful and interesting to all of our colleagues who were unable to attend.

We look forward to seeing you at Dealing with Data 2019.


Dealing With Data 2018: Summary reflections

The annual Dealing With Data conference has become a staple of the University’s data-interest calendar. In this post, Martin Donnelly of the Research Data Service gives his reflections on this year’s event, which was held in the Playfair Library last week.

One of the main goals of open data and Open Science is that of reproducibility, and our excellent keynote speaker, Dr Emily Sena, highlighted the problem of translating research findings into real-world clinical interventions which can be relied upon to actually help humans. Other challenges were echoed by other participants over the course of the day, including the relative scarcity of negative results being reported. This is an effect of policy, and of well-established and probably outdated reward/recognition structures. Emily also gave us a useful slide on obstacles, which I will certainly want to revisit: examples cited included a lack of rigour in grant awards, and a lack of incentives for doing anything different to the status quo. Indeed Emily described some of what she called the “perverse incentives” associated with scholarship, such as publication, funding and promotion, which can draw researchers’ attention away from the quality of their work and its benefits to society.

However, Emily reminded us that the power to effect change does not just lie in the hands of the funders, governments, and at the highest levels. The journal of which she is Editor-in-Chief (BMJ Open Science) has a policy commitment to publish sound science regardless of positive or negative results, and we all have a part to play in seeking to counter this bias.

Photo-collage of several speakers at the event

A collage of the event speakers, courtesy Robin Rice (CC-BY)

In terms of other challenges, Catriona Keerie talked about the problem of transferring/processing inconsistent file formats between heath boards, causing me to wonder if it was a question of open vs closed formats, and how could such a situation might have been averted, e.g. via planning, training (and awareness raising, as Roxanne Guildford noted), adherence to the 5-star Open Data scheme (where the third star is awarded for using open formats), or something else? Emily earlier noted a confusion about which tools are useful – and this is a role for those of us who provide tools, and for people like myself and my colleague Digital Research Services Lead Facilitator Lisa Otty who seek to match researchers with the best tools for their needs. Catriona also reminded us that data workflow and governance were iterative processes: we should always be fine-tuning these, and responding to new and changing needs.

Another theme of the first morning session was the question of achieving balances and trade-offs in protecting data and keeping it useful. And a question from the floor noted the importance of recording and justifying how these balance decisions are made etc. David Perry and Chris Tuck both highlighted the need to strike a balance, for example, between usability/convenience and data security. Chris spoke about dual testing of data: is it anonymous? / is it useful? In many cases, ideally it will be both, but being both may not always be possible.

This theme of data privacy balanced against openness was taken up in Simon Chapple’s presentation on the Internet of Things. I particularly liked the section on office temperature profiles, which was very relevant to those of us who spend a lot of time in Argyle House where – as in the Playfair Library – ambient conditions can leave something to be desired. I think Simon’s slides used the phrase “Unusual extremes of temperatures in micro-locations.” Many of us know from bitter experience what he meant!

There is of course a spectrum of openness, just as there are grades of abstraction from the thing we are observing or measuring and the data that represents it. Bert Remijsen’s demonstration showed that access to sound recordings, which compared with transcription and phonetic renderings are much closer to the data source (what Kant would call the thing-in-itself (das Ding an sich) as opposed to the phenomenon, the thing as it appears to an observer) is hugely beneficial to linguistic scholarship. Reducing such layers of separation or removal is both a subsidiary benefit of, and a rationale for, openness.

What it boils down to is the old storytelling adage: “Don’t tell, show.” And as Ros Attenborough pointed out, openness in science isn’t new – it’s just a new term, and a formalisation of something intrinsic to Science: transparency, reproducibility, and scepticism. By providing access to our workings and the evidence behind publications, and by joining these things up – as Ewan McAndrew described, linked data is key (this the fifth star in the aforementioned 5-star Open Data scheme.) Open Science, and all its various constituent parts, support this goal, which is after all one of the goals of research and of scholarship. The presentations showed that openness is good for Science; our shared challenge now is to make it good for scientists and other kinds of researchers. Because, as Peter Bankhead says, Open Source can be transformative – Open Data and Open Science can be transformative. I fear that we don’t emphasise these opportunities enough, and we should seek to provide compelling evidence for them via real-world examples. Opportunities like the annual Dealing With Data event make a very welcome contribution in this regard.

PDFs of the presentations are now available in the Edinburgh Research Archive (ERA). Videos from the day are published on MediaHopper.

Other resources

Martin Donnelly
Research Data Support Manager
Library and University Collections
University of Edinburgh