DataShare upgraded to v2.3 – The embargo enhancement release

The latest upgrade of Edinburgh DataShare, from version 2.2 to 2.3, brings in several useability improvements.

  • Embargo expiry reminder
    If you want to deposit your data in DataShare, but you want to impose a delay before your files become freely downloadable, you can apply an embargo to your submission – see our “Checklist for deposit” for a fuller explanation of the embargo feature. As of DataShare v2.3, if you apply an embargo to your deposit, DataShare will now send you an email reminder one week before the embargo is due to expire. This gives you time to make us aware if you need the embargo to be extended, or to send us the details of your paper if it has been published, so that we can add those to the metadata, to help users understand your data.
  • DOI added to the citation field immediately
    When your DataShare deposit is approved by the curator, the system mints a new DOI for you. As of version 2.3, DataShare now immediately appends the URL containing that DOI into the “Citation” field, which is visible at the top of the summary view page of your item. The “Citation” field makes it easy for others to cite your data, because it provides them with text which they can copy and paste into any manuscript (or any other document where they want to cite the data). Previously you would have had to click on “Show full item record” to look for the DOI in the “Persistent identifier” field, or wait for an overnight script to paste the DOI onto the end of the “Citation” field.
  • Tombstone records
    We now have the ability to leave a ‘tombstone’ record in place for any DataShare item that is withdrawn. We only withdraw items in exceptional circumstances – for example where there is a substantive error or omission in the data, such that we feel merely labelling the item as “Superseded” is not sufficient. Now, when we tombstone an item, the files become unavailable indefinitely, but the metadata remain visible at the DOI and handle URLs. Whereas until now, every withdrawn item has become completely invisible, so that the original DOI and handle URLs produced a ‘not found’ error.
Screenshot of a DataShare item's citation field with the DOI

Cortical parcellation citation – now with DOI!

Enjoy!

Pauline Ward

Research Data Service

P.S. Many thanks to our software developer at EDINA, George Hamilton, who actually coded all these enhancements to DataShare, which uses the open-source DSpace system. EDINA’s DataShare code is available at https://github.com/edina/dspace .

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Data-X Symposium

Registrations have been coming in thick and fast for the Data-X Symposium to be held on 1 December, Main Lecture theatre, Edinburgh College of Art (programme below).

Data-X is a University of Edinburgh IS Innovation Fund initiative supported by the Data Lab & ASCUS | Art & Science. It brings together PhD researchers from the arts and sciences to develop collaborative data ‘installations’.

To register visit: https://www.eventbrite.com/e/data-x-symposium-tickets-29076676121

Programme:

10.00 – 10.30: Registration & coffee

10.30 – 10.40: Welcome – Stuart Macdonald (Edina, Data-X Project Manager) & Introduction – Dr Martin Parker (Director of Outreach, Edinburgh College of Art)

10.40 – 11.20: Guest speaker: ASCUS & the ASCUS Lab: catalysts for Artiscience- Dr James Howie (Co-Founder, ASCUS)

Session 1 presentations: Chair – Dr. Rocio von Jungenfeld (School of Engineering & Arts, University of Kent)

· 11.20 – 11.35: PUROS Sound Box – Dr Sophia Banou, Dr Christos Kakalis (both School of Architecture & Landscape Architecture, Edinburgh College of Art), Matt Giannotti (Reid School of Music)

· 11.35 – 11.50: eTunes – Dr Siraj Sabihuddin (School of Engineering)

· 11.50 – 12.05: Inside the black box -Luis Fernando Montaño (Centre for Synthetic and Systems Biology) & Bohdan Mykhaylyk (School of Chemistry)

· 12.05 – 12.20: Wind Gust 42048 – Matt Giannotti (Reid School of Music)

· 12.20 – 12.30: Session 1. wrap-up

12.30 – 13.15: Lunch

Session 2 presentations: Chair – Martin Donnelly (Digital Curation Centre)

· 13.15 – 13.30: Elegy for Philippines Eagle – Oli Jan (Reid School of Music)

· 13.30 – 13.45: Feel the Heat: World Temperature Data Quilt – Nathalie Vladis (Centre for Integrative Physiology) & Julia Zaenker (School of Engineering)

· 13.45 – 14.00: o ire – Prof. Nick Fells (School of Culture and Creative Arts, University of Glasgow)

· 14.00 – 14.15: Sinterbot – Adela Rabell Montiel (Queen’s Medical Research Institute) & Dr Siraj Sabihuddin (School of Engineering)

· 14.15 – 14.25: Session 2. wrap-up

14.25 – 15.05: Guest speaker: FUSION – where art meets neuroscience – Dr Jane Haley (Edinburgh Neurioscience)

15.05 – 15.15: Closing remarks: Stuart Macdonald (Edina, Data-X Project Manager)

15.20: Close

Data-X is supported by: The Data Lab, ASCUS, Information Services

Stuart Macdonald
DATA-X Project Manager / Associate Data Librarian
EDINA

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Twenty’s Plenty: DataShare v2.1 Upload Upgrade

We have upgraded DataShare (to v2.1) to enable HTML5 resumable upload. This means depositors can now use the user-friendly web deposit interface to upload numerous files at once via drag’n’drop. And to upload files up to 15 GB in size, regardless of network ‘blips’.

In fact we have reason to believe it may be possible to upload a 20 GB file this way: in testing, I gave it 2 hours till the progress bar said 100%, and even though the browser then produced an error message instead of the green tick I was hoping for, I found when I retrieved the submission from the Submissions page that I was able to resume, and the file had been added.

*** So our new advice to depositors is: our current Item size limit and file size limit is 20 GB. Files larger than 15 GB may not upload through your browser. If you have files over 15 GB or data totalling over 20 GB which you’d like to share online, please contact the Data Library team to discuss your options. ***

See screenshots below. Once the files have been selected and the upload commenced, the ‘Status’ column shows the percentage uploaded. A 10 GB file may take in the region of 1 hour to upload in this way. 15 GB files have been uploaded with Chrome, Firefox and Internet Explorer using this interface.

Until now, any file over 1 GB had caused browsers difficulties, meaning many prospective depositors were not able to use the web deposit interface, and instead had to email the curation team, arrange to transfer us their files via DropBox, USB or through the Windows network, and then the curator had to transfer these same files to our server, collate the metadata into an XML file, log into the Linux system and run a batch import script. Often with many hiccups concerning permissions, virus checkers and memory along the way. All very time-consuming.

Soon we will begin working on a download upgrade, to integrate a means for users to download much bigger files from DataShare outside of the limitations of HTTP (perhaps using FTP). The aim is to allow some of the datasets we have in the university which are in the region of 100 GB to be shared online in a way that makes it reasonably quick and easy for users to download them. We have depositors queueing up to use this feature. Watch this space.

Further technical detail about both the HTML5 upload feature and plans for an optimised large download release are available on the slides for the presentation I made at Open Repositories 2016 in Dublin this week: http://www.slideshare.net/paulineward/growing-open-data-making-the-sharing-of-xxlsized-research-data-files-online-a-reality-using-edinburgh-datashare .

NewUploadPage

A simple interface invites the depositor to select files to upload.

 

 

Upload15GB

A 15 GB file uploaded via Firefox on Windows and included in a submitted Item.

 

 

A 20 GB file uploaded and included in an incomplete submission.

A 20 GB file uploaded and included in an incomplete submission.

Pauline Ward, Data Library Assistant, University of Edinburgh

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Publishing Data Workflows

[Guest post from Angus Whyte, Digital Curation Centre]

In the first week of March the 7th Plenary session of the Research Data Alliance got underway in Tokyo. Plenary sessions are the fulcrum of RDA activity, when its many Working Groups and Interest Groups try to get as much leverage as they can out of the previous 6 months of voluntary activity, which is usually coordinated through crackly conference calls.

The Digital Curation Centre (DCC) and others in Edinburgh contribute to a few of these groups, one being the Working Group (WG) on Publishing Data Workflows. Like all such groups it has a fixed time span and agreed deliverables. This WG completes its run at the Tokyo plenary, so there’s no better time to reflect on why DCC has been involved in it, how we’ve worked with others in Edinburgh and what outcomes it’s had.

DCC takes an active part in groups where we see a direct mutual benefit, for example by finding content for our guidance publications. In this case we have a How-to guide planned on ‘workflows for data preservation and publication’. The Publishing Data Workflows WG has taken some initial steps towards a reference model for data publishing, so it has been a great opportunity to track the emerging consensus on best practice, not to mention examples we can use.

One of those examples was close to hand, and DataShare’s workflow and checklist for deposit is identified in the report alongside workflows from other participating repositories and data centres. That report is now available on Zenodo. [1]

In our mini-case studies, the WG found no hard and fast boundaries between ‘data publishing’ and what any repository does when making data publicly accessible. It’s rather a question of how much additional linking and contextualisation is in place to increase data visibility, assure the data quality, and facilitate its reuse. Here’s the working definition we settled on in that report:

Research data publishing is the release of research data, associated metadata, accompanying documentation, and software code (in cases where the raw data have been processed or manipulated) for re-use and analysis in such a manner that they can be discovered on the Web and referred to in a unique and persistent way.

The ‘key components’ of data publishing are illustrated in this diagram produced by Claire C. Austin.

Data publishing components. Source: Claire C. Austin et al [1]

Data publishing components. Source: Claire C. Austin et al [1]

As the Figure implies, a variety of workflows are needed to build and join up the components. They include those ‘upstream’ around the data collection and analysis, ‘midstream’ workflows around data deposit, packaging and ingest to a repository, and ‘downstream’ to link to other systems. These downstream links could be to third-party preservation systems, publisher platforms, metadata harvesting and citation tracking systems.

The WG recently began some follow-up work to our report that looks ‘upstream’ to consider how the intent to publish data is changing research workflows. Links to third-party systems can also be relevant in these upstream workflows. It has long been an ambition of RDM to capture as much as possible of the metadata and context, as early and as easily as possible. That has been referred to variously as ‘sheer curation’ [2], and ‘publication at source [3]). So we gathered further examples, aiming to illustrate some of the ways that repositories are connecting with these upstream workflows.

Electronic lab notebooks (ELN) can offer one route towards fly-on-the-wall recording of the research process, so the collaboration between Research Space and University of Edinburgh is very relevant to the WG. As noted previously on these pages [4] ,[5], the RSpace ELN has been integrated with DataShare so researchers can deposit directly into it. So we appreciated the contribution Rory Macneil (Research Space) and Pauline Ward (UoE Data Library) made to describe that workflow, one of around half a dozen gathered at the end of the year.

The examples the WG collected each show how one or more of the recommendations in our report can be implemented. There are 5 of these short and to the point recommendations:

  1. Start small, building modular, open source and shareable components
  2. Implement core components of the reference model according to the needs of the stakeholder
  3. Follow standards that facilitate interoperability and permit extensions
  4. Facilitate data citation, e.g. through use of digital object PIDs, data/article linkages, researcher PIDs
  5. Document roles, workflows and services

The RSpace-DataShare integration example illustrates how institutions can follow these recommendations by collaborating with partners. RSpace is not open source, but the collaboration does use open standards that facilitate interoperability, namely METS and SWORD, to package up lab books and deposit them for open data sharing. DataShare facilitates data citation, and the workflows for depositing from RSpace are documented, based on DataShare’s existing checklist for depositors. The workflow integrating RSpace with DataShare is shown below:

RSpace-DataShare Workflows

RSpace-DataShare Workflows

For me one of the most interesting things about this example was learning about the delegation of trust to research groups that can result. If the DataShare curation team can identify an expert user who is planning a large number of data deposits over a period of time, and train them to apply DataShare’s curation standards themselves they would be given administrative rights over the relevant Collection in the database, and the curation step would be entrusted to them for the relevant Collection.

As more researchers take up the challenges of data sharing and reuse, institutional data repositories will need to make depositing as straightforward as they can. Delegating responsibilities and the tools to fulfil them has to be the way to go.

 

[1] Austin, C et al.. (2015). Key components of data publishing: Using current best practices to develop a reference model for data publishing. Available at: http://dx.doi.org/10.5281/zenodo.34542

[2] ‘Sheer Curation’ Wikipedia entry. Available at: https://en.wikipedia.org/wiki/Digital_curation#.22Sheer_curation.22

[3] Frey, J. et al (2015) Collection, Curation, Citation at Source: Publication@Source 10 Years On. International Journal of Digital Curation. 2015, Vol. 10, No. 2, pp. 1-11

http://doi:10.2218/ijdc.v10i2.377

[4] Macneil, R. (2014) Using an Electronic Lab Notebook to Deposit Data http://datablog.is.ed.ac.uk/2014/04/15/using-an-electronic-lab-notebook-to-deposit-data/

[5] Macdonald, S. and Macneil, R. Service Integration to Enhance Research Data Management: RSpace Electronic Laboratory Notebook Case Study International Journal of Digital Curation 2015, Vol. 10, No. 1, pp. 163-172. http://doi:10.2218/ijdc.v10i1.354

Angus Whyte is a Senior Institutional Support Officer at the Digital Curation Centre.

 

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