DataShare awarded CoreTrustSeal trustworthy repository status

CoreTrustSeal has recognised Edinburgh DataShare as a trustworthy repository.

What does this mean for our depositors? It means you can rest assured that we look after your data very carefully, in line with stringent internationally-recognised standards. We have significant resources in place to ensure your dataset remains available to the academic community and the general public at all times. We also have digital preservation expertise and well-planned processes in place, to protect your data from long-term threats. The integrity and reusability of your data are a priority for the Research Data Service.

Book to attend our practical “Archiving your Research Data” course

The certification involves an in-depth evaluation of the resilience of the repository, looking at procedures, infrastructure, staffing, discoverability, digital preservation, metadata standards and disaster recovery. This rigorous process took the team over a year to complete, and prompted a good deal of reflection on the robustness of our repository. We compiled responses to sixteen requirements, a task which I co-ordinated. The finished application contained over ten thousand words, and included important contributions from colleagues in the Digital Library team and from the university Digital Archivist Sara Thomson.

Our CoreTrustSeal application in full   

The CTS is a prestigious accreditation, held by many national organisations such as the National Library of Scotland, the UK’s Centre for Environmental Data Analysis and UniProt. Ours is the first institutional research data repository in the UK to receive the CoreTrustSeal (the Cambridge Crystallographic Data Centre has the CTS but, in contrast to DataShare, is a disciplinary repository which archives data from the international research community).

DataShare is a trustworthy repository, where you as a researcher (staff or student) at the University of Edinburgh can archive your research data free of charge. Bring us your dataset – up to 100 GB(!) – and we will look after it well, to maximise its discoverability and its potential for reuse, both in the immediate term and long beyond the lifetime of your research project.

Edinburgh DataShare

All CTS certified repositories

circular logo bearing a tick mark and the words 'Core Trust Seal'

The Research Data Support team has earned the right to display this CTS logo on the DataShare homepage

Pauline Ward

Research Data Support Assistant

Library & University Collections

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

New feature in Edinburgh DataShare: the REST API

Ever wanted to get a table of the details of all the datasets on DataShare to do with Scottish history? Or matching some other criteria, possibly on specified fields? If so, the new API (Application Programming Interface) can help.

DataShare now has a REST API, which you can use to query our metadata. An API makes the database’s contents accessible for requests from external servers, through a command-line, which allows external users to script such requests. The DSpace API also provides its own web-based query client and report client. These pages allow users to use a graphical interface to quickly build a query and see the results in a table, all in the browser.

The DataShare REST API page starts with a link to our plain-English explanation of how the API can be used:

Edinburgh DataShare DSpace REST API 

We would like to hear from anyone who wants to use the API. Please try it out and let us know what you find useful! Email us at data-support@ed.ac.uk .

Examples using the graphical query builder

I wanted to find datasets where I could add a link to the associated publication. This is a bit of a challenge for us, since users typically deposit their data with us under embargo before the associated paper has been published, and we do not have an automatic way to detect when or whether an associated publication has appeared.  I used the query builder to find the IsReferencedBy value for deposits accessioned in 2017. The plain-English guide on the wiki provides the steps I went through to do so:

How to use the DataShare REST API 

This feature may be of use to colleagues who support organisational units at University of Edinburgh which don’t align precisely with the Collections structure of DataShare – the API lets you query on multiple collections through the reporting tool. We’d love for colleagues to contact us if their teams have published a new paper containing a data citation of their DataShare deposit, so we can add the details of the publication to the DataShare Item’s metadata, resulting in a hyperlink appearing on the dataset landing page.

I wanted to find datasets with an embargo date in December. This is a challenge for us because users often set their embargo expiry date to Hogmanay, which means their one-week reminder would arrive on Christmas Day right in the middle of the university’s winter break. But many other fields contain dates with December in them, so it has not been practical for me to search for this using the graphical interface. So I used the API to search specifically in the dc.date.embargo field. See the screenshot below. The API helped me find the datasets whose embargo date we needed to extend, or else lift the embargo outright, allowing us to contact the depositors in good time to ask them whether a paper had been published or more time was needed.

Screenshot of the output of the REST API

Results showing datasets with an embargo date in December 2021

Thirdly, to demonstrate the power of this tool relative to the non-specific Search I chose a topic with very common words to show how to use the query builder to focus in on results avoiding spurious matches.

Using the existing ‘Search’ function on the homepage I searched for ‘history Scotland’. This produced 39 matches, some of which have nothing to do with historical research or Scotland, but merely mention a funder “NHS Research Scotland”, and mention the history of the research field in passing to provide a little context. Most of the matches are interesting, but some are not relevant.

Whereas when I set the API query builder to search for ‘history’ in the research area (subject classification), and ‘Scotland’ in the field for geographical metadata ie dc.coverage.spatial. This provided me with a short list of high quality matches, three datasets of historical research to do with Scotland – see the screenshot. This is a useful tool for narrowing a search.

Screenshot showing the input, and the output on the API query builder webpage

A search for two very common words in specific fields produces high quality results

Enabling the API

The REST API is a feature of the underlying DSpace repository software. Our sysadmins configured the API with great care to block certain commands and enable only the ‘GET’ commands that are needed for appropriate queries using DSpace config settings (further info DSpace 6 Documentation on the Lyrasis wiki ).

The Future

In the international DSpace repository community, we’re aware the API is used for integration with at least one CRIS (Current Research Information System) and quality tool applications (Andrea Bollini, 4Science, private communication). We understand the API of the newer DSpace 7 contains significant changes compared to that of DSpace 6, which we’re using for Edinburgh DataShare.

We’re aware of only a few examples of the API being used by individuals for occasional metadata queries. But we will watch with interest to see how the DSpace 7 API will be used.

 

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

Diverse climate change data in DataShare’s newest thematic collection

‘Code red for humanity’ was the galvanising message of the sixth report of the Intergovernmental Panel on Climate Change published on 9 August. The report draws on thousands of academic research projects. Research data is vital to understanding the nature and scale of the challenge of climate change, and the necessary deployment and application of solutions.

We decided to draw together the datasets relating to climate change to showcase them on a single Collection page on Edinburgh DataShare, our research data repository. In part this was prompted by a new deposit from Oliver Escobar in the School of Social and Political Science – data from citizens’ assemblies debating wind farms. Our DSpace repository allows us to ‘map’ an Item to Collections other than the one to which it belongs, resulting in the dataset being listed in more than one Collection. Edinburgh DataShare contains a wealth of research datasets from an extremely diverse array of academic disciplines, reflecting the strengths of the University of Edinburgh, and so it is with our climate change research:

Climate Change Collection

We added many datasets from our School of Geosciences: one dataset from Ian Goddard and Professor Simon Tett demonstrated how urbanisation has affected temperatures in the UK, and includes a map showing heat islands around our major cities. Professor Tett said:

“To truly understand how climate change might impact society we need to bring together many datasets developed by many researchers so that other researchers can use them for their own studies. DataShare enables this.”

Goddard, Ian; Tett, Simon. (2018). “Software and data used in the study ‘How much has urbanisation affected temperatures in the United Kingdom'”, 1990-2017 [software]. University of Edinburgh. https://doi.org/10.7488/ds/2370.

Climatological data and toolkits for public engagement around climate and natural resources came from Professor Marc Metzger – including various kinds of maps, a board game and posters showing natural resources.

One dataset was a description of an artwork, a quilt representing global temperature measurements. Posters on the wall show the years, so as to provide a time axis for the temperature data represented in the colours of the patches in the quilt:

Photo of quilt hanging on the wall of an exhibition space

World temperature quilt on display at the Data-X exhibition

Zaenker, Julia; Vladis, Nathalie. (2017). Feel The Heat – A World Temperature Data Quilt, [image]. University of Edinburgh. EDINA. https://doi.org/10.7488/ds/1998.

Another theme was renewable energy – we included data from our School of Engineering on tidal turbines, and recent wave buoy experimental data:
The big 3-0-0-0: DataShare reaches three thousand datasets

All this raises the question – why bring these data together, what for? Do the datasets measuring and defining the problem really belong with the research working on technology to reduce greenhouse gas emissions? To answer this, I think the analogy of our other thematic collection on Covid-19 is apt. To develop and implement effective treatments and public health responses to Covid-19, we do need to understand a great deal about the cause, the pathogen and the pathology it creates. We should strive to break down barriers between domains of knowledge. So yes, to tackle climate change more effectively, we should all seek to better understand the underlying processes and the behavioural and technological solutions we must employ.

By bringing together research data from diverse teams in a single DataShare Collection, we empower the user to browse those datasets using the ‘facets’ feature in DataShare, or indeed a text search within the Collection. The user can filter by geography, by data creator’s name, by keyword, funder (see the screenshot below) or they can choose their own search term. When they reach an individual dataset, the breadcrumb trail at the top of the page can lead them into the original Collection where the dataset was first deposited, leading them to other work from the same research group, centre or School. This is one small way for the curation team to enhance the findability of the data. Scientists tell us there are challenges posed by the plethora of formats and programming languages used, even within disciplines. We hope that by making the connections and common themes between these different strands of research from different disciplines more visible, we make the data more findable, and perhaps hope to inspire new research questions or approaches.

a screenshot from the Collection page

DataShare’s facets

A word about DataShare’s structure: we find our depositors prefer to place their data in a Collection that reflects the organisational placement of their research group – typically the Collection represents the research group, and sits within a Community representing a research centre, sitting within a Community representing a School, sitting within a top-level Community representing a College:
DataShare structure

If you would like to suggest a theme for a new thematic Collection on DataShare, please contact the Research Data Support team:
Research Data Service | Contact

The RDS team, like all the University of Edinburgh’s teams, has a remit to address climate change as the university is committed to contributing to the UN’s Sustainable Development Goals, including no. 13 “Take urgent action to combat climate change and its impacts”:
Social Responsibility and Sustainability | The University of Edinburgh

We can all learn more about how we can take that urgent action effectively on the university’s amazing and inspiring “Climate Solutions” MOOC, available on edX:
Climate Solutions | edX 

I recommend anyone to take this course – it is free of charge, it’s fun, it is easy to fit around other commitments. I’ve nearly completed the coursework and already passed thanks to my quiz scores, got my nice PDF certificate signed by Professor Dave Reay. The Climate Solutions MOOC inspired me to create the Climate Change thematic Collection and it has really opened my eyes to the scale and nature of the challenge, and many actions we all need to take to contribute to halting the rise in global temperatures. Everyone has their part to play.

Pauline Ward
Research Data Support Assistant
Library & University Collections
University of Edinburgh