FAIR dues to the Research Data Alliance

It has been a while since we’ve blogged about the Research Data Alliance (RDA), and as an organisation it has come into its own since its beginnings in 2013. One can count on discovering the international state of the art in a range of data-related topics covered by its interest groups and working groups which meet at its plenary events, held every six months. That is why I attended the 13th RDA Plenary held in Philadelphia earlier this month and I was not disappointed.

I arrived Monday morning in time for the second day of a pre-conference sponsored by CODATA on FAIR and Responsible Research Data Management at Drexel University. FAIR is a popular concept amongst research funders for illustrating data management done right: by the time you complete your research project (or shortly after) your data should be Findable, Accessible, Interoperable and Reusable.

Fair enough, but we data repository providers also want to know how to build the ecosystems that will make it super-easy for researchers to make their data FAIR, so we need to talk to each other to compare notes and decide exactly what each letter means in practice.

Borrowed from OpenAire 

Amongst the highlights were some tools and resources for researchers or data providers mentioned by various speakers.

  • The Australian Research Data Commons (ARDC) has created a FAIR self-assessment tool.
  • For those who like stories, the Danish National Archives have created a FAIRytale to help understand the FAIR principles.
  • ARDC with Library Carpentry conducted a sprint that led to a disciplinary smorgasbord called Top Ten Data and Software Things.
  • DataCite offers a Repository Finder tool through its union with re3data.org to find the most appropriate repository in which to deposit your data.
  • Resources for “implementation networks” from the EU-funded project GO FAIR, including training materials under the rubric of GO TRAIN.
  • The Geo-science focused Enabling FAIR Data Project is signing up publishers and repositories to commitment statements, and has a user-friendly FAQ explaining why researchers should care and what they can do.
  • A brand new EU-funded project, FAIRsFAIR (Fostering FAIR Data Practice in Europe) is taking things to the next level, building new networks to certifying learners and trainers, researchers and repositories in FAIRdom.

That last project’s ambitions are described in this blog post by Joy Davidson at DCC. Another good blog post I found about the FAIR pre-conference event is by Rebecca Springer at Ithaka S+R. If I get a chance I’ll add another brief post for the main conference.

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

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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 will be published on MediaHopper in the coming weeks.

Other resources

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

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“Archiving Your Data” – new videos from the Research Data Service

In three new videos released today, researchers from the University of Edinburgh talk about why and how they archive their research data, and the ways in which they make their data openly available using the support, tools and resources provided by the University’s Research Data Service.

Professor Richard Baldock from the MRC Human Genetics Unit explains how he’s been able to preserve important research data relating to developmental biology – and make it available for the long term using Edinburgh DataShare – in a way that was not possible by other means owing to the large amount of histology data produced.

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Dr Marc Metzger from the School of GeoSciences tells how he saves himself time by making his climate mapping research data openly available so that others can download it for themselves, rather than him having to send out copies in response to requests. This approach represents best practice – making the data openly available is also more convenient for users, removing a potential barrier to the re-use of the data.

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Professor Miles Glendinning from Edinburgh College of Art talks about how his architectural photographs of social housing are becoming more discoverable as a result of being shared on Edinburgh DataShare. And Robin Rice, the University’s Data Librarian, discusses the difference between the open (DataShare) and restricted (DataVault) archiving options provided by the Research Data Service.

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For more details about Edinburgh’s Research Data Service, including the DataShare and DataVault systems, see:

https://www.ed.ac.uk/is/research-data-service

Pauline Ward
Research Data Service Assistant
Library and University Collections
University of Edinburgh

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Research Data Service use cases – videos and more

Earlier this year, the Research Data Service team set out to interview some of our users to learn about how they manage their data, the challenges they face, and what they’d like to see from our service. We engaged a PhD student, Clarissa, who successfully carried out this survey and compiled use cases from the responses. We also engaged the University of Edinburgh Communications team to film and edit some of the user interviews in order to produce educational and promotional videos. We are now delighted to launch the first of these videos here.

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In this case study video, Dr Bert Remijsen speaks about his successful experience archiving and sharing his Linguistics research data through Edinburgh DataShare, and seeing people from all corners of the world making use of the data in “unforeseeable” ways.

Over the coming weeks we will release the written case studies for internal users, and we will make the other videos also available on Media Hopper and YouTube. These will address topics including data management planning, archiving and sharing data, and adapting practices around personal data for GDPR compliance and training in Research Data Management. Staff and users will talk about the guidance and solutions provided by the Research Data Service for openly sharing data – and conversely restricting access to sensitive data – as well as supporting researchers in producing meaningful and useful Data Management Plans.

The team is also continuing to analyse the valuable input from our participants, and we are working towards implementing some of the helpful ideas they have kindly contributed.

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