When working with an external collaborator from another university, an industrial partner, or obtaining access to pre-existing data provided by a third party there are data management responsibilities to be aware of. Transfer of data can involve legally binding agreements governing data storage and usage. Even if a legal agreement is not required, managing the transfer and sharing of data can be challenging. Here’s a short guide to services and support at UCL.

Where to put your data?

There are several systems for storing data at UCL, depending on your needs. Here is a quick guide to determine the most suitable choice when transferring data in from external sources.

• Dropbox (www.ucl.ac.uk/dropbox/) Not to be confused with the commercial service of the same name! This service is simple and convenient if you want to transfer a small number of files to or from an external collaborator outside of UCL as a one off and needs no specific security requirements
• SharePoint and OneDrive for Business Is a better option if you need to transfer files between yourself and a collaborator more frequently. Once you are set up with this system it can be configured to allow an external user access.
• Research Data Storage Service Is for large scale data storage and supports rapid transfer of large files. Once a project is set up it can be configured to allow access for external users. This is an excellent system to use for the transfer of very large data volumes.
• Data Safe Haven This secure data storage service is suitable for personal identifiable data, and could be used in other instances when a higher level of security is desired. It conforms to the ISO 27001 standard for information security management and the NHS DSP requirements. A level of training and verification is required to get set up on the platform, so if your project requires this it’s best to begin the process as soon as possible.
• The UCL Jill Dando Institute runs a specialised laboratory for processing data which is highly sensitive such as confidential crime data. This is probably beyond the needs of the majority of UCL projects. These facilities are suitable for those that require a system which is a Police Assured Secure Facility or need to work with UK government data marked as OFFICIAL-SENSITIVE and OFFICIAL. Similar to the Data Safe Haven there is a vetting and training process to get access.

Using surveys to collect data

Recently there has been move toward doing survey work largely online to support social distancing. Using online survey tools can be an efficient way to gather responses from participants and may even allow for an increase in the size and scope of a study, but there are data security concerns to be aware of.

• Questionnaires can be constructed using a variety of online tools. For any research that doesn’t involve collection of identifiable personal information there is no special requirement here. In fact, the free google forms service might fit the needs of many projects.
• UCL has access to some in-house tools that provide some extra functionality. If identifiable or otherwise sensitive data is being collected the REDcap tool can be used to send this data directly into the Data Safe Haven.
• Of course, some projects may still make use of an in-person paper survey form. In these cases, if the forms contain identifiable or sensitive information it is necessary to store the documents in a physically secure location. If the data needs to be converted into electronic format then it should be stored in the Data Safe Haven system.
• For survey work involving in-depth interviews with participants, the situation is a little more difficult. The nature of these sorts of interviews increases the likelihood of sensitive information being given. When conducting in-person interviews consider using recording devices with built-in encryption. If recording a zoom or teams interview make sure the recording is transferred as quickly as possible to safe storage and is not left in cloud storage for any length of time.

Data Transfer Agreements

You may require a kind of contract to get data from a third party, and there might be conditions attached to the permission to use this data. These kinds of contract are called Data Transfer Agreements (DTA) might need to be in place and is very likely to be part of the process when working with a commercial partner. Academic collaborators should also consider having a DTA drawn up, just to ensure clarity of how the data is being processed and prevent any disputes that could otherwise arise.

A data transfer agreement (DTA) is a specific version of a materials transfer agreement, which is a type of contract used when physical objects materials with scientific or commercial value and transferred between UCL and a third party. Both of these are handled by UCL Research and Innovation services who can provide more information and guidance on this if required.

Do also be aware that a data transfer agreement can be put in place by UCL staff and students when giving data to an external organisation too. They work both ways! If you ever need to share data with an external collaborator always consider if a DTA is necessary. It might be a useful tool to make sure your data is used for its intended purpose and is looked after properly.

This agreement is important as it outlines your responsibilities and permissions with respect to the data and is a legally binding agreement. There may be restrictions on what it can be used for, who can access it, and what security will be in place to protect the data. The agreement will specify details such as whether the data can or cannot be shared with other staff at UCL, with external partners, and what kind of security arrangements are required for storage.

Data Sources with specific application processes

A great deal of data is collected by government departments, healthcare providers and other services which can potentially be very valuable for researchers. UK law permits data the secondary use of personal data collected for reasons such as health, policing, education to be re-used for research if it is deemed to be in the public good. While specific agreements with other universities or commercial partners can be covered with DTAs, these data providers have well defined processes for granting access as they deal with relative large volumes of requests. Depending on the type of data you may have to meet security requirements. The UCL Data Safe Haven often helps with this. Here are some examples of data access services:

• Office for National Statistics
• National Pupil database
• HM Courts and Tribunals Service
• NHS digital

Need further guidance?

This is a brief overview of a big topic, so if you want further guidance on any of these points several teams across UCL can assist.

• Information Governance assist with Data Safe Haven related questions: infogov@ucl.ac.uk
• The Data Protection team also assist with questions around handling personal data: data-protection@ucl.ac.uk
• For more general enquiries the library research data management teams are a good first contact point and can direct you to the appropriate person: lib-researchsupport@ucl.ac.uk

To mark Love Data week here at UCL, the RDM team have published the now annual RDM review: https://doi.org/10.5522/04/19070309

Research Data Management (RDM) covers the decisions made – and actions taken – to manage research outputs across the research data lifecycle, complementing other components of open science and scholarship such as: Open Access, Bibliometrics, Research Integrity and Citizen Science.

As advocates of best practice in research data management, the RDM team have continued to promote UCL’s definition of ‘research data’ which emphasises that data refers to any output of research relevant to research findings and that publishing software, models, protocols, figures etc. is equally as important as publishing data.

In 2021, we reviewed a record-breaking number of data management and sharing plans; plus, we are publishing more research outputs than ever using the UCL Research Data Repository which recorded over 97000 downloads. We also continued to provide training via Moodle with almost 300 people completing writing a data management plan to date. 2021 also saw us become known as Library, Culture, Collection & Open Science and we as a team joined the Centre for Advanced Research Computing as associate staff.

Looking forwards to 2022, we plan on working even more closely with colleagues across UCL to enhance data management services throughout the research data lifecycle. We will also continue to advocate for changes to policy and practice relating to the way UCL rewards and assigns credit to all contributors to research to better acknowledge the vital contributions made by those especially in non-academic roles.

The full report can be found here: McMahon, Christiana; Houghton, James; Wallis, Kirsty (2022): Research Data Management: The 2021 Review. University College London. Presentation. https://doi.org/10.5522/04/19070309

Here’s to 2022!

Welcome to Love Data Week!

While you have probably heard of the work of the Research Data Management Team, who support you with decisions made during the research lifecycle to handle the data you work with, use or generate, from the planning stage of your project up to the long-term preservation of your data. Good data management practices are essential to meet UCL standards of research integrity.

To summarise, planning Research Data Management effectively helps you to ensure data quality, minimise risks, save time and comply with legal, ethical, institutional and funders’ requirements. The RDM team can guide you in the creation of your Data Management Plan, read and assess your plans when complete as well as advise you throughout the research process.

Contact: lib-researchsupport@ucl.ac.uk.

Outside the RDM team, there are a range of teams across the university that can support you.

The Data Protection and Freedom of Information Team are responsible for providing advice to UCL on data protection issues and handling statutory data protection and freedom of information requests. UCL’s Data Protection Officer leads the team, which sits in the Office of the General Counsel, and we work very closely with the Legal Services team and the Information Services Group.

All research proposals that involve personal data must be registered with the data protection office before processing begins. Further information, including FAQs and guidance notes are also available.

Contact: data-protection@ucl.ac.uk.

The UCL Research Ethics Committee (REC) and Research Ethics Officers facilitate an important function in the assessment of all applications submitted for ethical review and approval. The research ethics team must ensure that all applications have rigorously considered any ethical implications arising from proposed research design, methodology, conduct, dissemination, future use and data sharing and linkage, and how this will be managed should be carefully explained within a research plan. Ethical review of data management and security is a fundamental component of the ethical review procedure and researchers must demonstrate a strategy for data storage, handling of sensitive data, data retention and sharing. The following points are frequently requested:

1. What type of data will you collect and how will you describe them?
2. How will you store and keep your data secure?
3. Will you be allowed to give access to your data once the project is completed? Who will be able to access them, under what conditions and for how long?

More information about research ethics, data protection for researchers and data management tools for handling sensitive and personal/special category data is available online.

Contact: ethics@ucl.ac.uk

The Research Contracts Team sits within Research and Innovation Services. Research Contracts assists Academics by putting in place appropriate agreements for sponsored research on behalf of UCL. This includes reviewing, drafting and providing advice to Academics and Departments and negotiating acceptable terms. This includes material transfer agreements of which data, including personal and pseudo-anonymised data are part. There are current exceptions to our remit which include: Clinical Trial Agreements and EU grants & contracts, procurement agreements and consultancy.

For queries please contact:

• SLMS: SLMSresearchcontracts@ucl.ac.uk
• BEAMS: BEAMSresearchcontracts@ucl.ac.uk
• IOE/SLASH: IOESLASHresearchcontracts@ucl.ac.uk

Visit their website for more information.

The Information Governance & Compliance team are a part of the UCL Information Security Team, with a focus on research compliance. They provide support for compliance aspects of data applications, such as DARS and CAG for NHS data, also the Department for Education. They also have experience with a wide range of requirement sets ranging from commercial organisations through to public services. However, for data that falls outside of formal external agreements, for example directly collected, they can offer suitable information governance advice that aligns with the Information Commissioner’s Office accountability Framework. Most requirements can be met by using the UCL Data Safe Haven (DSH).

For research that cannot use the DSH, we can help determine suitable technical and organisational measures. We also manage access to the ONS Secure Research Service (see the process section on the left hand side of linked page).

Contact: infogov@ucl.ac.uk

The UCL/UCLH Joint Research Office (JRO) provides research management and governance support for clinical research studies that take place across University College London and/or UCL Hospitals NHS Foundation Trust (UCLH). Support and guidance are provided to researchers wishing to conduct clinical research which recruits NHS patients and/or uses their tissue or their data.

This includes any clinical research that requires a formal ‘Sponsor’ as defined by the UK Policy Framework for Health and Social Care Research (2017), the Medicines for Human Use (Clinical Trials) Regulations 2004 and subsequent amendments and the Medical Devices Regulations. Sponsor authorisation for these studies are provided by the JRO or one of the UCL clinical trials units (CTU).

The JRO consists of specialist teams who interface with colleagues across UCL/UCLH to support researchers through the research process. This includes guiding researchers through the approvals processes (e.g. NHS REC/MHRA), research contracting, research finance, regulations and compliance, study set-up and conduct, and data management.

More information about the JRO and how to get in touch can be found on the website.

And finally, the Research Integrity Team oversees and supports a broad set of research integrity initiatives at UCL to ensure compliance with the Concordat to Support research integrity support UCL to ‘Pursue a responsible research agenda (UCL 2019 Research Strategy – Cross-cutting Theme A). This includes coordinating periodic audits of UCL’s adherence with research integrity standards, leading on policy matters relating to research integrity, and frameworks for supporting integrity in research, such as the Statement on Research Integrity, the Framework for Research Integrity and the Code of Conduct for Research.  The team also led on the development of training for staff and students and provide advice and advocacy across UCL.

Who knew there were so many wonderful places to get support, and information to support your research data journey! If you are reading this during Love Data Week, don’t forget that we are hosting a Research Data Clinic with members of these teams to answer your questions! Thursday 17th February 2022 at 10.30am – register your interest on the form and we will send you all the information. After Love Data Week, get in touch with the teams directly, comment below or get in touch on Twitter!

Forget about finding a restaurant for Valentine’s Day, join us instead in the week of the 14^th of February and love your data!

Starting on Monday 14^th February we are bringing together colleagues that support research data from across the university just for you. We will be talking about all of the different forms that data can take, featuring profiles on different teams available to support you, sources of and tools for your data, and information about how data flows through the research process.

Every day we will be launching a new blog post, sharing videos and on Thursday 17th February at 10.30am we will be hosting a drop-in clinic for all your research data questions!

If you are interested in the drop-in clinic, please let us know using this form, this will ensure that you get the link to join us! We will be trying out a new platform called Wonder for the event that allows lots of conversations to take place at once, and for you to identify the expert that you need.

New for the academic year 2021-22 the Office for Open Science and Scholarship is organising a monthly series of talks, showcases and training sessions across as many of the eight pillars as we can fit in for UCL colleagues and students at all levels.

All of the teams will be teaching their usual classes, keep watching your usual sources of training plus here and on Twitter for those, but these introductory sessions are intended to give a general overview of each subject area for a general audience with plenty of opportunities for discussion and questions. These introductory sessions will also be supplemented with ad hoc events throughout the year.

• November
  Departmental UKRI Briefings – contact catherine.sharp@ucl.ac.uk to arrange a briefing for your team
• December
  Introduction to the Office for Open Science & Scholarship – December 15th 2-3pm – Postponed, please express interest below
• January 22
  Introduction to responsible metrics – January 27th 2-3pm – Online
• February
  Introduction to Research Data Management – February 2nd 10-11am – Online
• March
  Getting started with the RDR – Friday 4th Mar 10-11am – Online
• April
  Open Science Conference (Dates TBC)
• May
  Citizen Science project showcase (Details & Dates TBC)
• June
  Citizen Science, Public Engagement & Research Impact (Dates TBC)
• July
  ORCiD, DOI and beyond – Introduction to Persistent identifiers (Dates TBC)

If you are interested in any of the sessions above then please complete the MS form and the organisers will get back to you with calendar details and joining instructions for planned sessions. Any sessions without firm dates, we will contact you as soon as details are confirmed.

UCL Publications Board and the Open Access Team are delighted to announce that on Friday 19 November UCL’s institutional repository, UCL Discovery, reached the milestone of 30 million downloads! UCL Discovery is UCL’s open access repository, showcasing and providing access to UCL research outputs from all UCL disciplines. UCL authors currently deposit around 1,750 outputs in the repository every month (average figure January-October 2021).

by Ray Hennessy on Unsplash https://unsplash.com/photos/gdTxVSAE5sk

Our 30 millionth download was of a journal article:
Huber, LR; Poser, BA; Bandettini, PA; Arora, K; Wagstyl, K; Cho, S; Goense, J; Nothnagel, N; Morgan, AT; van den Hurk, J; Müller, AK; Reynolds, RC; Glen, DR; Goebel, R; Gulban, OF; (2021) LayNii: A software suite for layer-fMRI. NeuroImage, 237, Article 118091. 10.1016/j.neuroimage.2021.118091.

This article introduces a new software suite, LayNii, to support layer-specific functional magnetic resonance imaging: the measurement of brain activity by detecting changes associated with blood flow. The software itself, which is compatible with Linux, Windows and MacOS, is also open source via Zenodo, DockerHub, and GitHub. The authors also made a preprint version of the article available via BioRxiv in advance of formal publication in NeuroImage. This demonstrates the combined value of open source software and open access to research publications.

The author of the article based at UCL, Dr Konrad Wagstyl, deposited the article in UCL Discovery in May 2021. Dr Wagstyl is a Sir Henry Wellcome Research Fellow at the Wellcome Centre for Human Neuroimaging, UCL, and co-leads the Multicentre Epilepsy Lesion Detection project, an open science collaboration to develop machine learning algorithms to automatically subtle focal cortical dysplasias – areas of abnormal brain cell development which can cause epilepsy and seizures – in patients round the world.

The UCL Office for Open Science and Scholarship recommends that researchers make any software or code they use available to aid others in reproducing their research. The Research Data Management team maintain a guide on best practice for software sustainability, preservation and sharing, and can give further support to UCL researchers as required.

Happy Birthday to us!

Birthday candles by synx508 is licensed under CC BY-NC 2.0

To celebrate the first year of the Office for Open Science and Scholarship we decided to throw ourselves a virtual party, its been a year of milestones – take a look at our highlights video below!

This year over 20,000 records were uploaded to UCL Discovery and the combined number of theses hit 21,000! On top of that, UCL Discovery is about to hit 30 million lifetime downloads!

The smaller sibling to Discovery is UCL’s Research Data Repository, specialising in Open Access Research Data and code. It’s only 3 years old but it’s growing fast! This past year the number of downloads has increased by over 700% and the team that supports it is on track to double last year’s record for Data Management Plans assessed, and the year isn’t done yet!

And finally, our good friends at UCL Press hit a huge milestone of 5 million downloads across their 200+ books!

Its been a brilliant year for Open at UCL, and we hope that the office can grow and develop in years to come, and support our community to take Open Science from strength to strength. We hope you enjoy the video!

Guest post by James Houghton – Research Data Support Officer

Why not publish a data report article?

For a researcher who produces large amounts of data or works heavily with software and code for analysis, getting proper credit for their efforts can be a problem. Traditionally, an academic article is written in a format where a hypothesis is tested, results produced and analysed, and ends with a conclusion. This format increasingly is a poor fit for the work of many and data journals are one solution to this issue. The goal of this kind of journal is to publish a type of article usually referred to as a data report which focusses on announcing and describing the output of research projects which are resources, raw data, databases or similar and can be of use to the research community in general.

Publishing with a data journal offers several benefits. First, a data report article is more formal than a publication of data files in a repository and is a peer reviewed publication which then contributes to a researcher’s publication record which is important for CVs and advancement for many. Second, they allow a more detailed explanation of a dataset and any analysis or code related to it than is usually otherwise possible. Third, the appearance of an article in a recognised journal can help to drive visibility of a dataset for other researchers. In practice it my often be the case that a repository will be used to host material which is discussed at length in a paper.

For the research community more generally, data reports are a great way to discover and understand valuable contributions which they can re-use and build on. The data report guarantees there has been some level of peer-review applied to the data and, therefore, increases the confidence in the quality.

Data journals have flourished in recent years. Many publishers have introduced titles which specialise in data announcements and many other journals have begun to allow data articles as one of their accepted formats. Publishers will have their own specific guidelines for exactly what to include (or not include), but data articles will often have the following features:

• Detailed description of the methodology of how the data was produced and processed, allowing for far more detail than generally appears in a “traditional” publication.
• Documentation on structure and format of the data and details of how to retrieve it.
• Comments on how the data could potentially be re-used.
• Very limited or no results and conclusions.

The scope of a data journal varies greatly

• Some journals publish a wide range of data reports that cover many research areas, such as Scientific Data published by Springer Nature.
• Others are more subject specific such as Big Earth Data published by Taylor and Francis focussing on ecology and climate science, or Journal of Open Psychology Data published by the Open Access Ubiquity Press and specialising in psychology and anthropology data.

Of course, you must always check individual journal’s instruction for authors before preparing an article for submission.

Repositories and data journals should be seen as symbiotic, rather than needing to choose one or the other. An openly shared data set can be made available, and a data journal can be used as a way of announcing the existence of the resource to the community along with a detailed commentary which might not be easily supported by the repository itself. In fact, depending on the journal, hosting the data with a recognised external repository may even be a requirement for the publication process.

We won’t attempt to provide a comprehensive list of all journals that support this publication type here. There are many discipline specific and several more generalist options – but we would encourage you to investigate the options available in your subject area and tell us what you find!

Text and Data Mining (TDM) is a broad term used to cover any advanced techniques for computer-based analysis of large quantities of data of all kinds (numbers, text, images etc). It is a crucial tool in many areas of research, including notably Artificial Intelligence (AI). TDM can be used to reveal significant new facts, relationships and insights from the detailed analysis of vast amounts of data in ways which were not previously possible. An example would be mining medical research literature to investigate the underlying causes of health issues and the efficacy of treatments.

The importance of having copyright exceptions in place to facilitate TDM arises from the fact that the swathes of material which need to be mined are often protected by copyright. That would be true for example of “literary works” of all kinds and of images in many cases. It is frequently the case that researchers will have lawful access to the material but will be prevented from applying TDM techniques because copying the material onto the required computer platform risks legal action for infringement on the part of the copyright owners. “Copying” is of course one of the acts restricted by copyright law and in general the greater the amount and variety of material, the greater the copyright risk.

It is worth remembering that when the Government created an exception for Text and Data Mining in 2014, it meant that the UK was ahead of the game. Other countries did not generally have an exception in their legislation at that time. Since then, other jurisdictions have caught up and, in some cases overtaken the UK. Cutting edge research is a highly competitive area and researchers working in a country which benefits from a generous TDM exception will have a distinct advantage.

The existing exception is still significant from the Open Science perspective in enabling research projects where computer analysis of large quantities of copyright-protected material is required, particularly in the context of AI.

Let’s take a closer look at the UK TDM exception and what it allows us to do, before comparing it briefly with the more recent EU exceptions. The UK exception is to be found in Section 29A of the Copyright, Designs and Patents Act 1988.

What does the exception allow us to do?

Copying copyright-protected works in order to carry out “text and data analysis” (“computational analysis” in the wording of the exception). The need to copy arises because researchers must have have the material to be analysed on a specific platform, to carry out the analysis. The need for the exception then arises because without it, the researcher would require permission from the owner of copyright in each item. Without permission (or an exception), the researchers would be infringing copyright by copying a vast swathe of protected material. That in turn would often make the research impractical to carry out.

Who may do this?

Absolutely anyone, the exception says “a person.” This is wonderfully broad and one of the more favourable aspects of the UK exception. For example you don’t need to be working for/ studying at a particular type of institution to benefit from the exception.

Are there conditions?

You must have lawful access to the material. A prime example would be the text of academic journals. We have lawful access to large numbers of e-journals because UCL Library subscribes to them. The exception would allow a UCL researcher to download large amounts of content from e-journals to carry out detailed analysis using specialised tools. It is important to note that the exception cannot be overridden by contract terms. It follows that a term in an e-journal contract seeking to prevent TDM would have no force, in circumstances where the exception applies. This makes the exception a much more useful tool than it would otherwise be.

As you might expect the copies made for TDM purposes may not be used for other purposes, shared etc under the exception.

Significantly, the analysis must be “…for the sole purpose of research for a non commercial purpose.” This is a major restriction, which would rule out many situations where TDM might be used, for example research by a pharmaceutical company developing new drugs which will be marketed commercially. A major issue with the exception is that it can be unclear at what point “non-commercial” shades into “commercial.” A project which starts out as academic research may take on commercial significance down the line and a piece of research with no commercial aspects may be funded by commercial sponsors. It is an important constraint in the legislation which can also be difficult to be sure about in real life situations. It can stand in the way of joint projects by HEIs and commercial organisations.

Still, in situations where we can claim there is no commercial aspect to the research, the exception is potentially very useful. In addition to material which is already digital it can cover projects where digitisation of copyright- protected print material is required to be analysed. It can be very useful in situations where the copyright status of the source material is unclear, since provided the exception applies, there is no need to investigate further the complexities of copyright in the material.

The new EU TDM exception or rather exceptions

The EU Directive on Copyright in the Digital Single Market (DSM Directive) offers two new exceptions, which EM member states are obliged to transpose. They can be found in Articles 3 and 4 of the Directive.

There are important differences of approach to the UK in the answer to the question:  who may carry out the TDM? Article 3 provides an exception which benefits two defined categories of organisations: “Research organisations” and “Cultural heritage organisations.” Included within those groups are for example universities, museums, publicly funded libraries. Commercial organisations are excluded. It seems that independent researchers, not associated with an organisation would also be excluded, even though their research might be “non-commercial.” In common with the UK legislation, this exception cannot be overridden by contract terms and is therefore a powerful tool. The Directive addresses the question of public-private research collaborations in the recitals to the directive, e.g. recital 11. They are not excluded from benefitting from the Article 3 exception.

Article 4 offers a separate TDM exception which is available to anyone (including commercial organisations) but which is limited in a specific way: If the rights owners explicitly reserve the rights to carry out TDM within their works, then it cannot be mined under the exception. In other words, the EU DSM Directive goes one step further than the UK by offering an exception which can be used to mine lawfully accessible works by commercial organisations (or by anyone else), but it does not apply if the rights owner has explicitly ruled out TDM.  By contrast, commercial organisations would not be able to use the UK exception, unless they can claim the specific research is for a non-commercial purpose.

Guest post by Chris Holland, UCL Copyright Support Officer. For more information or advice contact: copyright@ucl.ac.uk

Guest post by James Wilson, Head of Research Data Services

Over the last year we’ve been making a number of improvements to the Research Data Storage Service (RDSS) to help researchers store and access their data in a way that better corresponds to how they work.

The RDSS is a managed storage service that helps researchers comply with funders’ criteria for good data management. It provides a storage space for research projects so that anyone involved in that project has a secure area in which to store and share files with their collaborators. Projects in the RDSS do not need to be formal, externally funded projects – they can be for personal research, or small unfunded collaborations between colleagues – but the service is well adapted for large projects with compute and multi-terabyte storage requirements.

That said, the service has had some limitations in the past which we have been addressing. The foremost amongst these was that you needed to be a member of UCL in order to use it. Increasingly, however, research is undertaken with collaborators around the world or in partnership with industry. Covid-19 has only accelerated this trend. We have recently added external collaborator functionality, enabling PIs to add external project members via a simple email invitation from within the interface.

We have also integrated the RDSS with UCL’s Research Data Repository – a platform that enables data and other non-traditional research outputs to be published, cited, and preserved over the long term. Researchers with a project registered in the RDSS can now move files, including very large files, across to the repository, along with contextual information.
As the volume of data in the RDSS grows, so we extend our capacity. We added an additional 600 terabytes of capacity during 2020, and will be adding a further petabyte of storage this coming term. The first terabyte of storage for any project is provided free of charge, with larger projects charged at £50 per TB per year. This gets you two copies of your data on disk in two different physical data halls at UCL’s Slough Data centre. A third back-up copy is saved to tape, and there is a 30-day retention period to help protect against accidental deletion.

Further information about the RDSS can be found at https://www.ucl.ac.uk/isd/services/research-it-services