Matthew Sillence: You.

Welcome to our second series of PGR matters. It's great to be

back recording again after a few months off the microphone. We

open our new season with three episodes that relate to a single

theme that I feel is important to address in the postgraduate

context, that's open research. The principles and practices of

open research are now widespread in universities in the UK and

internationally, developing from policies around open access of

academic outputs since 2005

in 2013 RCUK, now UK Research and Innovation published its

revised policy on publicly funded research outputs. The

latest version from August 2021 states that it's intended, and I

quote, to make published outputs of UKRI funded research widely

and freely accessible under conditions that allow maximum

reuse. Now, a recent analysis of 19 million research outputs has

shown, and I'm quoting here from the report by Chun Kai Huang,

Cameron Neyland, and Lucy Montgomery in 2024 that not only

do open access outputs receive more citations, but those

citations also from more geographically diverse locations

as well as more diverse fields of research. This all seems very

positive,

as well as open access to publications. The rubric of open

research encompasses research methods, data, licensing, peer

review, public engagement, or what is often called Citizen

Science. Although open research implies transdisciplinary

engagement, the term open science invokes an established

discourse for early stage and senior researchers from the

physical and in some cases, the social sciences. However, as

Marcel Knöchelmann on noted in 2019

researchers in the arts and humanities have lacked the

integrated discourse of an open humanities, which is partly due

to differences in ontology, epistemology and methodology

between the two great cultures of academia. Subsequent work by

Paul Longley Arthur and Lydia Hearn proposed that the

fragmented nature of discourse combined with perceived

practical and financial barriers, in turn, weakens

engagement with the underlying principles and practices of open

research. So although open research can be seen as a vital

mission of the university, in reality, it manifests in very

different ways. Over three episodes, we'll begin by

exploring what open research means for postgraduate

researchers and why it matters, drawing on the current policies

and practices in the higher education sector in the UK.

In episode two, we'll focus on the humanities and some of the

current work in universities to inform scholars about open

research barriers and opportunities as part of a

research training initiative with the University of Essex,

funded by the Consortium for humanities and the arts South

East England, CHASE, we'll talk to those who've released open

access books in these interviews, we'll Consider the

ways that early career scholars can navigate the many options

around open access publishing that are available today.

open research is now articulated explicitly as part of research

management. This places greater expectation on all early career

researchers to make, and I quote here from the RDF research

processes results and outputs transparent and as freely

accessible as possible to understand what we mean by open

research. I spoke with Grant young head of Open Research at

the University of East Anglia Library. I

Grant Young: Hey, Matthew, come on in. Looking forward to our

chat Absolutely. Thanks very much. Thank you. Busy out there.

At the moment,

it's a busy time. It's great, great to be talking to you and

and talking to you about open research, because I know we've.

Matthew Sillence: Passionate about that we are indeed, yeah,

so. So, just to get a sense of what your role is, you're the

Head of Open Research here in the University of East Anglia

library. That sounds it sounds impressive, but

Grant Young: leading up a small, a small team to to to try

better, to support open, open research here within the within

the university. So I'm so we're very new, new team, less less

usually in UEA, open research was a bit more distributed in

the past, and we've pulled that together over the last year. So

we can give it a bit more, a bit more focus. And so it's an

exciting area to be, to be working in and and particularly,

I'm particularly excited about thinking about its application

to the humanities, yeah, because often, you know, open research,

and particularly open science, which is a term that sometimes

bracketed with this really doesn't, doesn't quite resonate

with many humanities colleagues. So, so that's I mean, why I'm

particularly keen to have this discussion as well for us to to

think about the ways in which open research does, does

connect, is important for anyone undertaking research in the

university, so often open research? Well, it's kind of

particularly grown out of open access and open publications. I

know you've got another conversation lined up. Little

about publications, then, really, there's been, more

recently, some attention to data, and we're going to, we're

going to have a discussion around around data. But I think

open research is more holistic than that. It's not just about

those, those outputs, those things that you kind of spit out

at the end of a project. It's around thinking about the

project as a whole, the research as a whole, and where

transparency and openness and sharing can come into into the

whole whole project. So that's something where we're trying to

look at as a team and think about how we communicate that,

how we get across that it's not, it's not just about, you know,

an open article, or now an open book, yeah, absolutely, but or

sharing your data. And of course, data is something we

need to unpack a bit for the Humanities, but it's other forms

of openness as well. But I'm, anyway, yeah, I'm hogging the

mic here, so you can tell I'm enthusiastic. It's topic.

Matthew Sillence: Well, that's, that's one of the things I love

working with you for grant, is your enthusiasm around this. And

I think, you know, we've, we've worked together a bit over the

years around things like the research, data, lifecycle, and

trying to talk to students about that process a bit more, but I'd

like to just back up a little bit, because you you mentioned a

really important word there, which was transparency. And I

was kind of trying to understand what what it actually means to

be transparent in research. So how does that work with an open,

open research practice, I suppose, how is that understood

in terms of transparent practices?

Grant Young: So Well, again, I think, I mean, I think of it in

terms of that, that whole, that whole life cycle, it's been,

it's been clear about so not just, you know, I've done this

research. And here's this summary, this condensation,

condensation of this, of this research, you know, formal

publication of some sort, maybe some tidied up data. But it's

understanding how, how you got there.

Matthew Sillence: Yeah, so the journey basically,

Grant Young: well that, I think, I think so it's, it's, it's the

journey, and that can be scary to think about, kind of opening

up some of that, some of that messiness, and some of those,

those false starts, and some, some of that decision making and

thinking I and I understand that, and I understand in some

cases, the need to, to not be transparent. I mean,

particularly if you know, I mean, research project is so

diverse. But if your research involves, you know, lots of

human participants, and there's and there's needs to be quite

protective or careful about the subjects of your of your

research. There are, there are cases where you can't be

transparent, and you can't say exactly what went on and all of

all of those conversations and all of that. But where you can,

I think it's helpful. It's helpful for you because it kind

of encourages you. Be a bit more reflective on your on your

practice. It's helpful for other researchers, so they can, they

can, they can think about that process if they want to do

something similar, and they can also better understand your,

your outputs. So, so how did you get there? What decisions fed

into into that, into the those outputs, into into the thesis,

into into whatever you produce from it. So, so that's rather

vague, and that, of course, so transparency, I think, can

differ depending on what, on what that project, on project

is. But it's a kind of, I think of it. It's kind of a, it's kind

of an attitude, or an Orient, yeah, it's, it's, it's thinking,

actually there is value to me, sharing and being and being

transparent in what I do, and I will gain from that, and others

will gain from that.

Matthew Sillence: And I can see that there's a lot of value

there. Because you'll think, I mean reflection, something that,

you know, we teach on research training program is actually

around the reflective practice and reflexivity, so thinking

about your kind of, you know, your your your position, your

decision making, and how it impacts some other people. But

why is this drive towards transparency so important for

universities? What it what? What's really kind of lying

behind this institutionally and in higher education.

Grant Young: So so some, some of it is driven from funders and

those that are evaluating our research and awarding money for

our for our research. There are, there are increasingly

expectations there about openness and research and

including transparency in the way that we, that we conduct our

research. But there are, there are very many other good reasons

besides. It's about, you know, universities are also

increasingly focused on their on civic engagement and on and on

impact and so and telling stories about the research that

goes on and the value that they they add to to their

communities. And so this is this is also supporting that work.

So, you know, universities are looking at openness because they

have to if they want to achieve funding, and if they want to

tick the right boxes. But I think, and I and I'm hoping that

it is much more than that. It's about connecting the work of the

university that it does to communities as well, and

recognizing that in in that kind of broader communication and

openness can come further further projects and

collaborations. There's that benefit as well from being open

in the in the work that you're doing, in the projects, it can

lead to further to further work and further projects. So what if

I'm this?

Matthew Sillence: Yeah, you say about research funding there.

And one of the, I suppose, big things that we need to recognize

is UKRI and the research councils, as they've

historically been, you know, that sit within that

are

with us, part of RCUK, they, they're using public funds. So,

you know, very, very often, you know, this is taxpayers money

which is coming in to support and advancing research and and

as you rightly say, that there is a sense of expectation around

you know, how is this? How is this money being used, what are,

what are the benefits to society? And we've seen that

with the Economic and Social Research Council statements on

research impact, which is that it can have different forms of

impact. It can be economic, it could be, you know, two specific

groups, and it could be around those societal benefits that we

might think of that improve access to healthcare or

education, or whatever that happens to be. So there's, yeah,

there's a there's a really, there's some big incentives

there. Your team's got quite a job, though, because you're

sitting in the middle of this mechanism, I suppose, because

you're based in the library and and there's funds coming. In for

different projects or studentships, in some cases, for

PhD students, and they're the ones carrying out the work. So

those researchers are there, you know, working on the projects.

They're the ones developing, deciding the outputs. But what?

So, what does your what

Grant Young: does your what do we do? Open research team,

Matthew Sillence: what, what do you do around supporting

accessibility, I suppose, of that research output, because

that's, I suppose, one of the first things people would ask

exactly, well, where is it, you know, where's the where's the

stuff, where's the outputs that I that I can. Benefit from

Grant Young: so that so that's that's a key, key part of our

work to to enable these, these outputs, particularly, to be, to

be more accessible. A big part of our work isn't, is naturally

around open, open access publication, yeah. So

supporting, supporting that, and unfortunately, in the current,

in the current world in which we live, that involves payment,

often payment, of finding the funding of money in order to

enable those outputs to be, to be opened up. And it's because,

you know, we've come from this traditional infrastructure where

pub, you know, where, where publishers got money, usually

from libraries through subscriptions and and now we're

shifting towards kind of open access. That's a long it's a

long transition. I was talking to some PGRs

the other week, and I said to them, you know, it's, it's, it's

unfortunate in a way, you're in this kind of messy middle phase.

So twenty years ago, would have been straightforward, and you

would have been pitching your your article to a journal, and

they would have said, that's great. We'll publish it, and

then it would be produced and likely to buy it, and it would

become, become available, hopefully in a few decades,

probably it will be straightforward. But we're in

this we're in this middle, middle phase where there there

are publishers who are asking for payment,

where we have a mix of direct payments or deals with

publishers that allow public publishing, where we have other

kinds of journals and other platforms where things can be

made more more cheaply and easily Open Access. So it's a

kind of quite a messy, complicated environment that

we're working in now, and funders that have expectations

and sometimes give you money for this and sometimes don't. So So

a key part of our role is to help people navigate that

ecosystem and to help people where we can fund some of this

opening up of of outputs. So we, so we have an inquiry service

where people will come to us and say, you know, I'm, you know, I

want to do this. How do I do it? And often that's around

publications, but it's, it's around other things too, like,

Where can I put my data, and we'll talk data in a bit. And so

there's there's an inquiry service. We're developing a kind

of a hub of information resources, a website, web pages,

and we're doing some work to make those a bit clearer and to

connect those a bit more with our researchers. And then we are

looking at our training offer as well. So we're looking at

expanding this. And you know, some of what we will be doing

together in the project around gamification is around looking

at looking at training and looking at how we communicate

that. So we're doing that more broadly as well. So, so it's

that, it's not just, as I say, about publications. It's about

data and practices as well. And so it's it's giving some advice

and guidance on good practice around data, and I think we can

talk a bit more about that later in this discussion. It's also

signposting where this data might be put, and how this

might, this might be shared. And then it's also thinking about as

we've, as we talked about before, about not just focusing

on those outputs, but focusing on open practices throughout the

project, throughout the life cycle. So it's thinking about

how we can enable and encourage some of that. So, so, so yes,

inquiry service websites are training portfolio and

conversations like this.

Matthew Sillence: Yeah, absolutely, yeah. We, we will

get on to to have a to have a think about data. And because, I

guess I know that, you know, we've worked with quite a lot of

people in digital humanities work over the years, and that's

been, that's been one area where I think data is probably

slightly more tangible. Tangible, yeah, tangible is a

great word. Yeah, definitely. But if, maybe, if we just sort

of take the sort of bigger views. So I've heard, I've heard

of these key principles around

open, open research practices. And one of the there's an

acronym which is F, A, I, R: FAIR. So.

In a nice one, easy to remember, so Findable, Accessible,

Interoperable and Reusable. So we've talked a bit about

accessibility already, I suppose, in terms of their

research outputs. But so maybe we could start with a slightly

trickier word, which is interoperable.

Grant Young: Sometimes it's even a hard word to say, isn't it?

What

Matthew Sillence: do we what do we mean by that when

researchers, or, you know, whether it's a postgraduate

research or, you know, senior academic is thinking about

their, you know, their research data and the materials, what is

that sort of interoperability?

Grant Young: So, I mean, I'm interested in your thoughts on

this too, but for me, for me, it's about ensuring that this

data, this and I use data in a very broad sense, can be used

alongside other data, so that You can potentially bring, you

know, multiple data sets together and maybe build

something more out of out of that. So it would be about

paying attention to standards where they exist, and that might

be file formats, or it might be the way that the meta data about

data, about this, about this data now that now that's also

serving the purpose of helping you to find this stuff, this

stuff, and to understand what this data is. But can us also

support the interoperability of this, of this data? So the way

we kind of label these things and and categorize these things.

And if those are, those are standards that others are using

as well, then that will enable data to be put together and to

put into into interoperate. So that's one key aspect of

interoperability, of course. I mean these, these acronyms. I

mean these these letters. I mean they all shade into in together,

don't they? So I've already said, you know, interoperability

is supported by metadata, and so is a fine, you know, find

ability, discovering, discovering that stuff

interoperability is. We're talking there about supporting

reuse in a way, not well, you know, reuse that involves this

data working alongside other other content of it, other data,

the there's also, so the method, so the metadata supports there.

But also there's, there's some thinking that needs to go on

around license, licensing. So, so are there? Are there? Are

there licenses that you should or shouldn't use in to enable

reuse and interoperability. So these things, these things are

connected, but help it helpful to think of them in turn as

well. Yeah. So an

Matthew Sillence: example of that might be, you know,

research student has as many people do if you're trying to

sort of tabulate data, one of the sort of go tos in many

universities is just open up an Excel spreadsheet and start, you

know, filling in columns and rows with information. So, and

that's a very simple way of, you know, you could be keeping

records of, perhaps the number of images that appear in your

thesis, or it might be you're actually tabulating, you know,

account books that you've discovered in an archive

somewhere, and you're you're restructuring that data

digitally. But that's all very well as you for you as a

researcher. But if somebody else comes along and they and they

want to use that, that that file, what's the problems there?

Is this fine. It's fine if we just, you know somebody just

emails over file or the I mean, you

Grant Young: may, you know, you may, you may have a good

understanding of what, of what that label in that column or

that row means, but others may interpret that differently. I

mean, you know, you may want to think about, you know whether

you need a data dictionary, whether you need an explanation

of what you actually meant and how you got who went about

gathering that, that that thing that sits in that in that cell.

Now, in a previous, previous life, I was working, as you say,

more in digital humanities on the kind of archival side. So I,

I was working with PhD students who were who were using

materials from from the the archive, and I would seek

conversations with them. I would say, if you're capturing all

this rich data, it would be really helpful if you captured

them in these categories, because these are the categories

that that I use in my archives database, and so I can help you,

and you can help me, and that data that you produce can be

interoperable, that I you know, that can, that can be go into a

catalog and be useful for someone, for someone else as

well, and for me to understand. This thing that's in my archive,

which I'll never have time to look at in detail, but you have

so So, I mean, I think those are, those are some things to

think about if you're doing that archival research. But whatever

you know, whatever information you're capturing, I think it's

helpful to think about how you're structuring that. Yes,

and if there are standard ways to structure and to describe

that, then it may make sense to adopt, to adopt those, or to at

least understand how, how your data might map to some of these

other standards and structures to make them more interoperable

and understandable and reusable. So, I mean, I'm talking, yeah,

hope, hopefully our listeners can can think of some

applications there. I mean, that's one, you know, kind of

doing some archival research. You mentioned images as well,

yeah. And so it's thinking moving images or still images.

It's thinking about your choice of formats, and maybe, for

example, the image that you're taking is just needed for kind

of quick reference, but you could take a higher quality,

higher resolution image of this while you were there, and that

might be beneficial, because down the line, someone may be

able to make better, you know, other use of that image, or if

it's an image of text, you know, in the future, handwriting

recognition may be sufficiently advanced that Actually you can

do something more with that image, or someone else can do

something more with that image. So it's kind of thinking about

those broader uses and applications. And it's not just

thinking about that. I mean, it's about those other people,

those imaginary people who might you know at some stage want to

use your data, but it's thinking about you as a future researcher

as well. So it's thinking, as you're gathering this data, what

might I want to be doing with this in 10 years time? Will I

remember? Will I remember all the information I need to know

about this, about this data in 10 years time. Or is it, is it

helpful for me to do a bit more documentation as I go so, you

know, or, you know, I've got this now, and I think of it as

just a step towards something a bit more polished and a bit more

finished. I can probably throw that away. But actually, maybe,

you know, maybe that is, is useful. Maybe, maybe I want to

hold on to that. Now, there are lots of issues around holding on

to data, around file size and where am I going to put it? And

particularly if you're collecting human data, should I

be holding on to that absolutely? And in some cases,

you shouldn't be, you know, you'll be, you'll be seeking

ethical approval, and so that will help inform the decisions

that you make around that. But I think it's helpful to think

beyond, beyond the initial project and the focus now to

think about I'm investing all of this work now. Could this be

more broadly useful? Could this be useful to me if I do a bit

more work now around this,

Matthew Sillence: I think that's a really, really excellent piece

of advice to give is to think about that kind of, you know,

the the people or the users of the future. And I suppose now

we're in, you know, we're in the, whatever the official term

is the age of AI. And one of the, you know, one of the terms

that very often comes up is sort of human readable and machine

readable data. So we assume perhaps, that there's going to

be a human being who's going to be looking at how the decisions

have been made and interpreting, mapping the information across

somehow, but, but actually in many, many areas of research,

where there's been semi automation of practices, or

there's very big data sets, you might actually be running a

computer program which is interpreting the data. In order

for a machine to do that, it needs to be in a very specific

data structure very often, or it needs to be recognizable to that

machine to be processed. So So interoperability, I guess, is,

is that sort of compatibility for human benefits? But there's

also the mission kind of machine element to that that's nicely

put in the mean, we could talk about file formats and stuff

until, till, you know, the cows come home. But, I mean, one of,

one of the, one of the things that, I suppose, from a sort of

data deposit standpoint, so obviously, we've got a digital

repository here at UEA, which people can actually upload data.

It too. There's also other sort of national data centers I

understand in the UK where people can or repositories.

Grant Young: Yes, that's right. So for example, it was more of a

social science like project the UK Data Archive in Essex, that

that will, that may take in that that data set. So sometimes

there are very clear places to put this. Sometimes these things

are a little less clear, and that's something we're looking

at as an institution as well, and how we might better support

support data. And you know, like many institutions, we've got

somewhere to go to go there. But that's certainly something where

we're looking at, yeah, yeah. I, you know, I'm glad you touched

on on AI. And this is something that is kind of a fast moving,

moving, moving area, and something that certainly we're

thinking about in terms of of openness as well. And, and it's

and it is. It is an issue of interest and concern within open

open research, and, and it's something that needs to be

thought of in relation to the licensing as well, so that reuse

and what we what we're enabling, and in many cases, we want to

enable this kind of machine reuse, and in other cases, we

might need to think about, think about that as well. And I guess

that brings me back to point I did want to make, which is

often, often there's, there's a line, you know, with with

openness, you know, we want this, this data or this

information to be kind of as open as possible and as closed

as necessary. So, you know, in some cases, you know, we need to

recognize that that some things can be open, some things can't.

And so that's something to think about as well. So of course,

much of much of the work that's been done around around open

research has come out of STEM and out of the sciences. And so,

as I said early earlier on, I think there's we're particularly

keen to do some work around, you know, what does this mean for

humanities? And certainly, much of the information we've got up

at the moment is is cast in that kind of language of science and

and of STEM, and so we're doing some work as we think about our

website and our training, how we, how we translate that I

don't really translates the right word, how we, how we

communicate that effectively to humanities. And I don't think

it's actually that just unidirectional. I think

actually, there's, you know, there's been some really

interesting work that's been done around the humanities and

the qualitative social sciences, and the way that research is

conducted there, and the and the openness that is already, you

know, being done through, through some of those projects,

which, which, I think sort of the STEM subjects could benefit

from. So thinking, thinking about, you know, openness with

your participants. So kind of openness in terms of kind of

your theory and methodology, and so I think there's some really

interesting practices, kind of openness in the way that we

communicate our research, often within the humanities and social

sciences. So I think actually there's a lot that the Sciences

and Health can benefit from, from understanding some of the

practices that, some of the open practices that we already do

within, within the humanities. So that's something that I'm

keen that we promote us as well. And it's not just about saying,

Okay, there's, there is this open agenda. How can we flip the

terminology so, so it's actually meaningful for Humanities. But

actually, let's think about openness in a big in a bigger

way, and let's think about whether some of the work we do

within the humanities might actually help our colleagues in

other disciplines, great

Matthew Sillence: as grant young notes in this conversation, how

a project is conducted is at the heart of open research, this

might include clear statements about the size of a data set,

the number of participants involved, and the analytical

methods that have been applied. This is relevant to both

quantitative and qualitative approaches to research. A major

project involving researchers across the Universities of

Cambridge.

Sheffield and Southampton, called Materializing Open

Research Practices in the Humanities and Social Sciences,

or MORPHSS, has reported on the two practices that will be

relevant to listeners of this podcast, open documentation of

creative methods in which the process of making is documented

in some way, for example, through images, videos, audio

recording and digitized textual or graphic notebooks or

sketchbooks. The second is similar to the first and

probably more familiar to those in the social sciences, which is

a detailed methodological description provided as an open

access appendix to the project report or outputs or a methods

based article for a journal

in many STEM disciplines, the aims of open data, materials and

methods are designed to facilitate reproducibility, so

that other researchers could perform the same analysis with

the same data to produce the Same result. This can be

facilitated through the practice of pre-registration, so that a

project at the outset and in progress is documented in a

digital repository, and later processes and reported findings

are compared with the original research design. Replicability,

which sounds very similar, differs from the former in that

the same analysis might be run on different data. There are

obvious challenges here for many humanities researchers whose

projects are distinctly ideographic meaning that they

focus on phenomena in very specific contexts outside these

situations and interactions that involve both documentation and

interpretation by the researcher. It may be impossible

or even undesirable to come to the same conclusions or for the

analysis to function on a different phenomenon. Despite

the fundamental ontological and epistemological differences

here, there's still a value in striving for openness as a

researcher, there may be an ethical imperative to do so.

Adams, Barnes, Moore, Pinfield and Soni who have authored a

MORPHSS report published in February 2026

Pre-registration might be part of this, but other forms of

documentation can improve the transparency of a project, both

for the academic community, but also for many other communities

who have a stake in the conduct of the research, for example,

indigenous groups or policy makers,

the latest MORPHSS report illuminates some of the

limitations to the original FAIR principles that we discussed a

few moments ago, as we have seen findability, accessibility,

interoperability and reusability are all important to design into

a research project, and they speak to particular technical

processes involving metadata platforms such as repositories

compatible data structures and file formats and standardized

licensing. However, in recent years, researchers have also

called for the adoption of CARE principles, which stands for

Collective benefit, Authority to control, Responsibility and

Ethics. This means providing equal attention to the conduct

of open research in human society.

Adams and colleagues explain how important the care principles

are when working with data from marginalized communities who may

not wish to share knowledge and materials in certain ways, this

relates to that all important statement that grant mentioned

earlier, as open as possible, as closed as necessary, researchers

from across the stem arts, Humanities and Social Sciences

will need to confront the ethics of open practices. We'll return

to the MORPHSS project in episode three, when we explore

the ways in which researchers in the humanities learn to engage

with open research principles and practices. In our next

episode, we'll focus on open access publishing through three

interviews with colleagues at the University of Essex, most

postgraduate researchers will encounter open access through

the accessibility of the thesis through an institutional

repository. This has been standard practice in

universities for many years. However, there are many other

ways of publishing scholarship which we'll explore, including

different forms of journals and long form texts such as books.

In recent years, the UK's Research Excellence Framework,

REF, has stipulated that such research outputs are made open

access, but there are several routes for doing so.

Matthew Sillence: On. You.