Announcement from Paul Ayris, Pro-Vice Provost, UCL Library, Culture, Collections and Open Science

How can Open Science/Open Research support career progression and development? How does the adoption of Open Science/Open Research approaches benefit individuals in the course of their career?

The UCL Open Science Office, in conjunction with colleagues across UCL, has produced a series of Case Studies showing how UCL academics can use Open Science/Open Research approaches in their plans for career development, in applications for promotion and in appraisal documents.

In this way, Open Science/Open Research practice can become part of the Research Culture that UCL is developing.

The series of Case Studies covers each of the 8 pillars of Open Science/Open Research. They can be found on a new webpage: Open Science Case Studies 4 UCL.

It is only fair that academics should be rewarded for developing their skills and adopting best practice in research and in its equitable dissemination. The Case Studies show how this can be done, and each Case Study identifies a Key Message which UCL academics can use to shape their activities.

Examples of good practice are:

• Publishing outputs as Open Access outputs
• Sharing research data which is used as the building block of academic books and papers
• Creating open source software which is then available for others to re-use and develop
• Adopting practices allied to Reproducibility and Research Integrity
• The responsible use of Bibliometrics
• Public Engagement: Citizen Science and Co-Production as mechanisms to deliver results

Contact the UCL Open Science Office for further information at openscience@ucl.ac.uk.

Guest post by Dr Christiana McMahon,  Research Data Support Officer

In June 2019, the Research Data Management team from Library Services and the Research Data Group from the Centre for Advanced Research Computing embarked on an exciting journey: the launch of the UCL Research Data Repository. As we approach our fifth anniversary, we find ourselves reflecting on the progress we’ve made, what we’ve achieved and what could be improved. To better understand the impact and gather insights from our UCL community, we invite you to complete this survey here. Join us in celebrating this important milestone!

Since its inception, the Research Data Repository has been a pivotal tool for openness and accessibility, offering UCL staff and research students a platform to archive, publish, and share their research outputs as widely and openly as possible. From datasets to figures, presentations to software, the repository has become a hub of scholarly exchange and collaboration. The journey thus far has been marked by significant milestones. Since 2019, we’ve seen over 385,000 downloads and 610,000 views, underscoring the repository’s impact and reach within the academic community.

Figure 1 Graph to show total number of items published using the Research Data Repository

The Research Data Repository enables users to:

• archive and preserve research outputs on a longer-term basis at UCL;
• facilitate the discovery and sharing of work by publishing metadata records;
• assign a digital object identifier (DOI) to permanently link to and identify a record in the online catalogue as part of a full data citation enabling others to reference published works;
• comply with the UCL Research Data policy and other applicable research policies.

Three highlights from the Research Data Repository:

The most viewed record is: Silvester, Christopher; Hillson, Simon (2019). Photographs used for Structure from Motion 3D Dental model generation Part 2. University College London. Figure. https://doi.org/10.5522/04/9939419

The most downloaded record is: Acton, Sophie; Kriston-Vizi, Janos; Singh, Tanya; Martinez, Victor (2019). RNA seq – PDPN/CLEC-2 transcription in FRCs. University College London. Dataset. https://doi.org/10.5522/04/9976112.v1

The most cited record is: Manescu, Petru; Shaw, Mike; Elmi, Muna; Zajiczek, Lydia; Claveau, Remy; Pawar, Vijay; et al. (2020). Giemsa Stained Thick Blood Films for Clinical Microscopy Malaria Diagnosis with Deep Neural Networks Dataset.. University College London. Dataset. https://doi.org/10.5522/04/12173568.v1

These milestones demonstrate the repository’s impact and reach within the academic community, serving as a testament to the collaborative efforts of our dedicated researchers and staff.

Figure 2: Stages of Research Data Lifecycle

Why is the Research Data Repository essential to supporting academic communities across UCL?

It mostly stems from wanting researchers to manage and share their outputs in line with the FAIR principles (Findable, Accessible, Interoperable and Reusable)  and embrace open science and scholarship practices. Essentially, by depositing outputs into the Research Data Repository and creating associated metadata records, other researchers and members of the public are better placed to find, understand, combine, and reuse the outputs of our research without major technical barriers. In turn, this can help to enhance transparency of the research process, promote enhanced research integrity, and ultimately maximise the value of research findings.

Going forward:

To continue building and developing the service, we are asking staff and research students to tell us what they think. What works well? What could be improved? Which functionalities would you like to see added or enhanced?

The survey closes on Friday, March 22nd, so get in touch and tell us what you think!

Survey link: https://forms.microsoft.com/e/U20yJPAi0W

More information about the Research Data Repository can be found in Open Science & Research Support dedicated webpage.

Any questions or queries about the Research Data Repository can be sent to: researchdatarepository@ucl.ac.uk.

General research data management queries can be sent to: lib-researchsupport@ucl.ac.uk.

Any questions or queries about open science can be directed to: openscience@ucl.ac.uk.

Get involved!

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities. Follow us on X, formerly Twitter, and join our mailing list to be part of the conversation!

Guest post by Michelle Harricharan, Senior Research Data Steward, in celebration of International Love Data Week 2024.

ARC Data Stewards have completed the first phase of work on the third-party datasets project, aiming to help researchers better access and manage data provided to UCL by external organisations.

The problem:

Modern research often requires access to large volumes of data generated outside of universities. These datasets, provided to UCL by third parties, are typically generated during routine service delivery or other activities and are used in research to identify patterns and make predictions. UCL research and teaching increasingly rely on access to these datasets to achieve their objectives, ranging from NHS data to large-scale commercial datasets such as those provided by ‘X’ (formerly known as Twitter).

Currently, there is no centrally supported process for research groups seeking to access third-party datasets. Researchers sometimes use departmental procedures to acquire personal or university-wide licenses for third-party datasets. They then transfer, store, document, extract, and undertake actions to minimize information risk before using the data for various analyses. The process to obtain third-party data involves significant overhead, including contracts, compliance (IG), and finance. Delays in acquiring access to data can be a significant barrier to research. Some UCL research teams also provide additional support services such as sharing, managing access to, licensing, and redistributing specialist third-party datasets for other research teams. These teams increasingly take on governance and training responsibilities for these specialist datasets. Concurrently, the e-resources team in the library negotiates access to third-party datasets for UCL staff and students following established library procedures.

It has long been recognized that UCL’s processes for acquiring and managing third-party data are uncoordinated and inefficient, leading to inadvertent duplication, unnecessary expense, and underutilisation of datasets that could support transformative research across multiple projects or research groups. This was recognised in the “Data First, 2019 UCL Research Data Strategy”.

What we did:

Last year, the ARC Data Stewards team reached out to UCL professional services staff and researchers to understand the processes and challenges they faced regarding accessing and using third-party research datasets. We hoped that insights from these conversations could be used to develop more streamlined support and services for researchers and make it easier for them to find and use data already provided to UCL by third parties (where this is within licensing conditions).

During this phase of work, we spoke with 14 members of staff:

• 7 research teams that manage third-party datasets
• 7 members of professional services that support or may support the process, including contracts, data protection, legal, Information Services Division (databases), information security, research ethics and integrity, and the library.

What we’ve learned:

An important aspect of this work involved capturing the existing processes researchers use when accessing, managing, storing, sharing, and deleting third-party research data at UCL. This enabled us to understand the range of processes involved in handling this type of data and identify the various stakeholders involved—or who potentially need to be involved. In practice, we found that researchers follow similar processes to access and manage third-party research data, depending on the security of the dataset. However, as there is no central, agreed procedure to support the management of third-party datasets in the organization, different parts of the process may be implemented differently by different teams using the methods and resources available to them. We turned the challenges researchers identified in accessing and managing this type of data into requirements for a suite of services to support the delivery and management of third-party datasets at UCL.

Next steps:

 We have been working on addressing some of the common challenges researchers identified. Researchers noted that getting contracts agreed and signed off takes too long, so we reached out to the RIS Contract Services Team, who are actively working to build additional capacity into the service as part of a wider transformation programme.

Also, information about accessing and managing third-party datasets is fragmented, and researchers often don’t know where to go for help, particularly for governance and technical advice. To counter this, we are bringing relevant professional services together to agree on a process for supporting access to third-party datasets.

Finally, respondents noted that there is too much duplication of data. The costs for data are high, and it’s not easy to know what’s already available internally to reuse. In response, we are building a searchable catalogue of third-party datasets already licensed to UCL researchers and available for others to request access to reuse.

Our progress will be reported to the Research Data Working Group, which acts as a central point of contact and a forum for discussion on aspects of research data support at UCL. The group advocates for continual improvement of research data governance.

If you would like to know more about any of these strands of work, please do not hesitate to reach out (email: researchdata-support@ucl.ac.uk). We are keen to work with researchers and other professional services to solve these shared challenges and accelerate research and collaboration using third-party datasets.

Get involved!

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities. Follow us on X, formerly Twitter, and join our mailing list to be part of the conversation!