YERUN 2018 | Exploring researcher engagement with open access through international collaboration

​The Scholarly Communication Office represented by David Walters and Chris Daley spoke to YERUN (Young European Research Universities) members this week about local open access policies and their relationship with international research collaboration.

You can find the video online at the link below and all the presentations are due to be shared on the YERUN website shortly. There were lots of other interesting talks about developing research organisations’ links with business, open science and other exciting topics.


David Walters and Christopher Daley from Brunel University London explore the complexities of the current UK open access (OA) policy landscape and examine the concurrent emergence of open science services which aim to provide global OA data. Using the results of their recent study, they will consider whether the global data on open access activity reveals tensions between natural research collaboration and policy drivers implemented at an institutional level.

Research into open access levels at Brunel

Colleagues in the Scholarly Communication Office have just had a research paper published entitled: “Enhancing Institutional Publication Data Using Emergent Open Science Services.” We have included the abstract and link to the article below, but essentially our study explores if open access infrastructures fully capture the OA activities of Brunel researchers or whether open science systems such as Unpaywall, CORE and Sherpa REF may help to provide a richer picture of their OA behaviours.

The results shows a strong culture of OA engagement. We must take a moment to congratulate all our researchers in progressing the open access agenda so successfully at Brunel University.


Title: Enhancing Institutional Publication Data Using Emergent Open Science Services
Authors: David Walters and Christopher Daley


By publication year, we see the proportion of OA growing. Just 7.7% of works in 2016 had a Green option not taken by authors

The UK open access (OA) policy landscape simultaneously preferences Gold publishing models (Finch Report, RCUK, COAF) and Green OA through repository usage (HEFCE), creating the possibility of confusion and duplication of effort for academics and support staff. Alongside these policy developments, there has been an increase in open science services that aim to provide global data on OA. These services often exist separately to locally managed institutional systems for recording OA engagement and policy compliance. The aim of this study is to enhance Brunel University London’s local publication data using software which retrieves and processes information from the global open science services of Sherpa REF, CORE, and Unpaywall. The study draws on two classification schemes; a ‘best location’ hierarchy, which enables us to measure publishing trends and whether open access dissemination has taken place, and a relational ‘all locations’ dataset to examine whether individual publications appear across multiple OA dissemination models. Sherpa REF data is also used to indicate possible OA locations from serial policies. Our results find that there is an average of 4.767 permissible open access options available to the authors in our sample each time they publish and that Gold OA publications are replicated, on average, in 3 separate locations. A total of 40% of OA works in the sample are available in both Gold and Green locations. The study considers whether this tendency for duplication is a result of localised manual workflows which are necessarily focused on institutional compliance to meet the Research Excellence Framework 2021 requirements, and suggests that greater interoperability between OA systems and services would facilitate a more efficient transformation to open scholarship.

Data Matters – Dr Nana Anokye

We’ve launched a new blog series called ‘Data Matters – data stories from Brunel’ where Brunel researchers are invited to share their data stories about their research and how they manage, share and use open data.

Dr Nana Anoyke is a Senior Lecturer in Health Economics and is Director of Research for the Department of Clinical Sciences.



Tell us about your research and the data you work with.

My research covers addressing methodological challenges in understanding why (and how) people make decisions on lifestyle behaviour change, with a view to informing the design of public health interventions and methods for assessing the value for money of such interventions.

I work with large primary (collected as part of clinical trials) and secondary datasets (publicly available international and national datasets).

Is there a culture of data sharing in your field? 

Yes, data sharing is practiced in health economics particularly regarding data for populating decision analytic models.

What kinds of data do you make openly available and how/where do you make them available?

The data I make openly available include estimates for populating economic models and dataset used for cost effectiveness analyses. I make them available via data repositories (e.g. figshare) and journals (as supplementary files).

Are there any data challenges associated with your research, in particular around managing, sharing or reusing open data? 

The data challenges associated with my research include: (a) anonymised data; (b) working in large teams with the principal data collectors often based outside Brunel; and (c) large datasets with lot of variables.

How have you overcome these challenges? 

I have overcome these challenges by developing a data management plan – this helps to identify the data challenges and potential solutions at the outset of projects.

What advice would you give a researcher just starting out about open science/open data?

Open science is the present and the future. It could increase the impact of our research.







Data Matters – Kanya Paramaguru

To coincide with Love Data Week 2018, we are launching a new blog series called ‘Data Matters – data stories from Brunel’ where Brunel researchers are invited to share their data stories about their research and how they manage, share and use open data.

Kanya Paramaguru, a PhD student in the Department of Economics and Finance.


Tell is about your research and the data you work with. 

I am a 2nd year doctoral student in the Department of Economics and Finance. I work in the field of Macroeconomics which involves looking at the economies of countries. The data that I use is in the form of Government statistics that aim to describe the economy. This data is usually available publicly through the websites of the Government statistical agencies. Understanding this data has wider public value for many different reasons. One that I can mention is one of public accountability. A deeper understanding of Government statistics by the General Public would help us to hold Politicians to account, when they make certain claims about the health of the economy.

Are there any data challenges associated with your research, in particular around managing, sharing or reusing open data?

As already mentioned , I am fortunate to not have to collect any data myself as I am using third party sources.  However, there are occasionally some issues when using third party data. Understanding the calculations that were done to create the series is often information that is a bit tricky to access. As I am looking at the statistics of various countries, I need to ensure consistency between the different data sources that I use. Ensuring consistency between the methodology of data between different countries can sometimes be tricky.

How have you overcome these challenges?

I would usually have to look in to the meta-data of the dataset to read what the statisticians methodology and definition of each series is and check if the same methodology was used across countries. This meta-data is often available along with the main data source, however, if for whatever reason I either cannot find it or access it, I often contact the third part source directly. If you are using third party data , and anything is unclear I would suggest you contact the organisers of the source of the data. I have found that being proactive in communicating with third parties about their data has led to clarification on the data which the party often did not realise was unclear. This has benefits for everyone using the data. It is sometimes even an opportunity to share your research ideas with other organisations.

What data management advice would you give to a first year doctoral student?

Starting to think about data early on is a really good idea. It can often shape the research idea itself, as research is hard to carry out without the availability of corresponding data. Thinking through the data process methodologically is a useful habit to develop. This involves steps on thinking about data harvesting, data management, ethics (if applicable) and ensuring readability over time. Talking to your supervisor about data management can be a useful thing to do as they might have some tips for you, depending on the kind of data that you are working with.