Quicker, easier interface for DataVault

We are delighted to report that Edinburgh DataVault now has a quicker and easier process for users. The team have been working hard to overhaul the form for creating a new ‘vault’ to improve the user experience. The changes allow us to gather all the information we need from the user directly through a DataVault web page. The users no longer need to first login to Pure and create a separate dataset record there. Instead, that bit will be automated for them.

I have explained the new process and walked users through the new form in a new and updated how-to video, now combining the getting started information with the demo of how to create a vault:

Get started and create your vault! (8 mins)

The new streamlined process for users is represented and compared to our open research data repository DataShare in this workflow diagram. DataVault is designed for restricted access, but can also handle far larger datasets than DataShare.

The diagram shows the steps users go through in DataShare and DataVault. Common steps are deposit and approval.

The DataVault process includes the gathering of funding information, and review and deletion none of which are present in the DataShare workflow since they would not be relevant to that open research data repository.

The arrow showing DataVault metadata going to the internet represents the copying of selected metadata fields into Pure, where they are accessible as dataset records in the university’s Edinburgh Research Explorer online portal.

Our new course “Archiving Your Research Data”, featuring Sara Thomson, Digital Archivist, provides an introduction to digital preservation for researchers, combined with practical support on how to put digital preservation into practice using the support and systems available here at University of Edinburgh such as the DataVault. For future dates and registration information please see our Workshops page.

A recording of an earlier workshop (before the new interface was released) is also available: Archiving Your Research Data Part 1: Long-term Preservation.

If you are a University of Edinburgh principal investigator, academic, or support professional interested in using the Edinburgh DataVault, please get in touch by emailing data-support@ed.ac.uk.

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

The big 3-0-0-0: DataShare reaches three thousand datasets

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Confetti banner says "3,000th deposit!!!" 2021-08-02

Timestamp showing the accession of the deposit on the 2nd of August.

We’re thrilled Edinburgh DataShare has just ingested its 3,000th deposit:

Davey, Thomas; Draycott, Samuel; Pillai, Ajit; Gabl, Roman; Jordan, Laura-Beth. (2021). Wave buoy in current – experimental data, [dataset]. University of Edinburgh. School of Engineering. Institute for Energy Systems. FloWave Ocean Energy Research Facility. https://doi.org/10.7488/ds/3105.

The depositor was Dr Tom Davey, Senior Experimental Officer in the School of Engineering, who said:

“It is a pleasure for us all in FloWave to see one of our datasets achieve this milestone for Edinburgh DataShare. This is also the tenth DataShare upload making use of experimental outputs from the FloWave Ocean Energy Research Facility. Providing a reliable and accessible repository of our project outputs is not only important for our funders, but also promotes new research collaborations and builds lasting impact for our experimental programmes. This particular project will aid in the understanding measuring wave and currents at deployment sites for offshore renewable energy technologies, and adds to the existing FloWave portfolio of datasets in the field of wave energy, tidal energy, advanced measurement, and remote operated vehicles.”

You can explore more data generated at FloWave in the IES DataShare Collection:

Collection – The Institute for Energy Systems (IES) (ed.ac.uk)

Although the ‘wave buoy in current’ dataset is under temporary embargo, currently set to expire on the 5th of September, it is possible to request the data using DataShare’s request-a-copy feature in the meanwhile. Embargoes may be extended, or lifted early, usually reflecting publication dates.

You might also enjoy this hilarious and very popular video about FloWave:

 

Pauline Ward

Research Data Support Assistant

Library & University Collections

University of Edinburgh

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

Two new Quick Guides for good Research Data Management

The Research Data Support team have recently published two new Quick Guides, the latest in a series of short, user-friendly documents intended to help our research staff and students plan, manage and preserve their data effectively, safely, and for the long-term.

Quick Guide 5 takes the topic of “Open Research” – also known as Open Science, particularly in a European context. The drive towards research transparency and the removal of barriers to accessibility has gathered a great deal of momentum over recent years, to the extent that “Open by default” is an increasingly common approach. Open research enables scientific findings to be tested, reproduced and built upon far more quickly than traditional approaches allowed. The benefits of Open Research are being demonstrated in real time, right in front of our noses, as researchers at Edinburgh tackle various aspects of the Covid-19 pandemic. We recently tweeted about one such project which examined the effectiveness of face coverings in reducing the range travelled by breath, which of course helps transmit the virus. The data underpinning this research is freely available to everyone via Edinburgh DataShare.

The latest Quick Guide, the sixth in the series, addresses the ‘FAIR’ principles, which state that research data should – so far as possible, and appropriate – be Findable, Accessible, Interoperable and Reusable. These principles emphasise machine-actionability (i.e. the ability of automated computational systems to find, access, interoperate, and reuse data with minimal or no human intervention) as humans increasingly rely on computational means to discover and work with data as a result of the increase in volume, complexity, and creation speed of data.

These two new publications join our existing guidance on topics such as the basics of Research Data Management (RDM), RDM and data protection, and research data storage options at the University. Future topics planned include conducting research safely online, FAIR approaches to research software, and an overview of the systems and services available at Edinburgh in support of Open Research. If there is a particular topic you would find useful, please get in touch with us via data-support@ed.ac.uk or the IS Helpline.

All of our Quick Guides can be found at https://www.ed.ac.uk/information-services/research-support/research-data-service/guidance

Martin Donnelly
Research Data Support Manager
Library and University Collections