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 This is an effect of policy, and of well-established and probably outdated reward/recognition structures.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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Data Carpentry Workshop, Spring 2018

Following on from the success of previous Carpentry workshops we have hosted, the Research Data Support team organised another two day Data Carpentry workshop on 12th /13th June 2018 in the David Hume Tower teaching studio.

Students at work on the Data Carpentry workshop held in David Hume Tower teaching studio.

Data Carpentry workshops focus on introductory computational skills needed for data management and analysis in all domains of research. If you have never heard of ‘Data Carpentry’, ‘Software Carpentry’ or ‘the Carpentries’ we suggest you go take a look around the Data Carpentry and Software Sustainability Institute websites. While the ‘Data Carpentries’ follow a similar theme, the lessons can vary between different workshops, depending on the level of the learners and their requirements. The topics covered were:

  • Data Cleaning with OpenRefine
  • Programming and Data Visualisation with R
  • Relational DataBases and SQL

All the sessions received positive feedback from students on both content and delivery. The headliner for the workshop was undoubtedly the R programming: two R sessions delivered over Tuesday afternoon and Wednesday morning by the lead instructor Edward Wallace. Edward is based at King Buildings and uses R in his own research into RNA-protein interactions. He is clearly a great teacher as the feedback on these sessions indicated it was really well delivered and the pace of the course was just right. That is not easy to do when you have such a wide range of students from all disciplines.

This course was fully booked within a few hours of being advertised and there remained over 50 people registered on the waiting list indicating the demand for these data handling courses. The overwhelming feedback from the course was “more R training please!”. Keep a lookout for advertising on the RDS website and the university Events booking as more Carpentry training is on its way!

Thanks from the Research Data Support team to all the excellent helpers and trainers for making this event possible. All the trainers and helpers for this workshop were Edinburgh University staff.

Some of the students, teachers and helpers on the June 2018 Data Carpentry Workshop.

Trainers: Edward Wallace, Giacomo Peru, Manos Farsarakis, Lucia Micheilin.

Helpers: Rosey Bayne, Sean McGeever, Mario Antonioletti, Daniel Robertson, Evgenij Belikov, Jennifer Daub.

This workshop was organised in collaboration by Research Data Service, EPCC, ARCHER and the Software Sustainability Institute.

Jennifer Daub
Research Data Support
Library & University Collections

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Dealing with Data, 2017

One hundred researchers from across the University came together to present work in progress and discuss many tricky issues they face in ‘dealing with data’ at a Research Data Service sponsored event on 22nd November in Playfair Library.

A theme that emerged from this year’s event was around approaches to balancing the drive to make data open with the increasingly restrictive ethical and legal requirements for non-disclosure of personal data from research subjects.

The University’s CIO and Librarian, Gavin McLachlan, set the scene for the day’s topics in his welcome address, referencing data driven innovation through the Edinburgh Region City Deal, the aims of the European Open Science Cloud, FAIR data (Findable, Accessible, Interoperable, Reusable), and the GDPR – the new General Data Protection Regulation coming into force in May, 2018.

Videos of speakers and links to presentations may be viewed from the event page at http://edin.ac/2CypID0. Look out for the event same time next year!

Robin Rice & Kerry Miller (DWD 2017 Organiser)
Research Data Service

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The Edinburgh DataShare Awards!

The Research Data Service team applauds those researchers at the University of Edinburgh who share their data. We therefore decided to show our appreciation by presenting awards to our most successful depositors, as part of the Dealing With Data conference. The prizes themselves do not come with a cash research grant attached unfortunately. However, the winners did receive a certificate bearing an image of our mascot for the day, Databot. We think you’ll agree the winning depositors and their data demonstrate the diversity of our collections, in terms of subject matter, formats and sheer size. We were particularly pleased with the reactions from both the recipients and the attendees, both in person, by email and on twitter (#UoEData was the Dealing with Data hashtag). Who doesn’t love the drama of an awards ceremony! A video is available.

Photograph of Pauline Ward announcing the award winners

Photo: CC-BY Lorna M. Campbell

The winners in full…

MOST DATASHARING SCHOOL: Edinburgh Medical School

– the School which boasts the greatest number of Edinburgh DataShare Collections currently. Thirty-three eligible Collections (already containing at least one dataset) such as “Connectomic analysis of motor units in the mouse fourth deep lumbrical muscle”, the Edinburgh Imaging “Image Library” and “Generation Scotland”.

MOST PROLIFIC DATASHARER: Professor Richard Baldock
– the most prolific depositor into Edinburgh DataShare for the academic year 2016-17, and over the lifetime of the repository, having shared a grand total of 1,105 data items with full metadata. These are grouped together into numerous Collections under the heading of “e-Mouse Atlas”. The majority of these detailed images show microscope slides of stained tissue, others are 3D models. They accompany a book and website published by Professor Baldock, building on the seminal work of Professor Matt Kaufman in developmental biology. The metadata for each of the slides links to a lower definition version within the e-Mouse Atlas website, where the data may be viewed and navigated in context. The original slides themselves are held by the University’s Centre for Research Collections.

detail of histological slide showing stained cells

Detail from Elizabeth Graham; Julie Moss; Nick Burton; Yogmatee Roochun; Chris Armit; Lorna Richardson; Richard Baldock. (2015). eHistology Kaufman Atlas Plate 21a image d, [image]. University of Edinburgh. College of Medicine and Veterinary Medicine. http://dx.doi.org/10.7488/ds/735.

MOST PROLIFIC DATASHARER (CSE): Professor Euan Brechin
– the depositor of the greatest number of Edinburgh DataShare items from the College of Science and Engineering in academic year 2016-2017. Euan deposits his coordination chemistry research data so frequently that we set up a Collection template on the Brechin Research Group, which automatically pre-populates some of the metadata fields for him, saving Euan time. If only we could find a way to mention metallosupramolecular cubes here.

The certificate awarded to Professor Euan Brechin

The certificate awarded to Professor Euan Brechin

MOST PROLIFIC DATASHARER (CAHSS): Dr Andrea Martin
– the depositor of the greatest number of Edinburgh DataShare items from the College of Arts, Humanities and Social Sciences in academic year 2016-2017. Some of these “Language Cognition and Communication” data items are still under temporary embargo. Users may nonetheless see all the metadata.

MOST POPULAR SHARED DATA: Professor Peter Sandercock
– the depositor of the Edinburgh DataShare item which has attracted the greatest number of page views over the lifetime of the repository: “International Stroke Trial database (version 2)” (aka IST-1).  These data from the International Stroke Trial provide a great example of how clinical trial data may be anonymised to allow them to be shared. For more information, you may want to watch Prof Sandercock’s very accessible and detailed  public lecture. Admittedly, one other item is higher up DataShare’s table of page views than IST. However we believe the traffic drawn by “RCrO3-xNx ChemComm 2016” to be artifactual, arising from the appearance of the word ‘doping’ in its abstract, and the fact the deposit was made at a time when doping in sport was very prominent in the news media. Additionally, the earlier, superseded, version of the IST-1 dataset also appears in the all-time top ten, and if we combine the number of views, it is in the No.1 spot outright 🙂

MOST POPULAR DATA 2016-17: Dr. Junichi Yamagishi
– the depositor of the Edinburgh DataShare item which has attracted the greatest number of page views (1,720 to be precise, as counted by Google Analytics) over the academic year 2016-17: “Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2015) Database”. Here’s the suggested citation, which DataShare compiles automatically, and displays prominently, to encourage users to cite the data:

Wu, Zhizheng; Kinnunen, Tomi; Evans, Nicholas; Yamagishi, Junichi. (2015). Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2015) Database, [dataset]. University of Edinburgh. The Centre for Speech Technology Research (CSTR). http://dx.doi.org/10.7488/ds/298.

MOST POPULAR DATA 2016-17 (CAHSS): Professor Miles Glendinning

– the depositor of the Edinburgh DataShare item from the College of Arts, Humanities and Social Sciences which has attracted the greatest number of page views (1,374 to be precise, as counted by Google Analytics), over the academic year 2016-17: “Hong Kong Public Housing Archive”. The Research Data Service is working closely with Miles, Personal Chair of Architectural Conservation, on a series of batch imports to put his fabulous array of photographs of public housing tower blocks from all around the world on DataShare over the coming months – keep an eye on DOCOMOMO International Mass Housing Archive.

Sunny image of the façade of several tower blocks; a tree is visible in the foreground.

Image cropped from “HKI_H_Yue_Fai_Ct.jpg” from Glendinning, Miles; Forsyth, Louise; Maxwell, Gavin; Wood, Michael. (2015). Hong Kong Public Housing Database, 2006-2015 [image]. University of Edinburgh. Edinburgh College of Art. http://dx.doi.org/10.7488/ds/322.

MOST POPULAR DATA 2016-17 (MVM): Dr. Tom Pennycott
– the depositor of the Edinburgh DataShare Collection page from the College of Medicine and Veterinary Medicine which has attracted the greatest number of page views over the academic year 2016-17: “Diseases of Wild Birds”. Hundreds of grotesquely beautiful photographs of dead wild birds, bodies ravaged with viruses, bacteria and protists, found at locations all around the United Kingdom; these images support the PhD thesis of Dr Tom Pennycott from our Veterinary School.

You can see usage statistics for any DataShare Item or Collection simply by clicking on the “View usage statistics” button on the right-hand-side of the page.

Pauline Ward, Research Data Service Assistant
EDINA and Data Library

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