Transcript - Meeting the most unmet need - RDM Training for researchers, HDR students and data trainers

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Meeting the most unmet need – RDM Training for
researchers, HDR students and data trainers
23 August 2017
Video & slides available from ANDS Website
START OF TRANSCRIPT
Karen Visser: Welcome everyone, welcome to our webinar for today, meeting the
most unmet need, RDM training for researchers, high degree research
students and indeed data trainers. What we have for you today is four
different models of data training and the people who have created
them. This webinar is part of a series of - will be part of a series of
webinars and this is the first one.
For those of you who are interested in FAIR Data, which has taken the
world by storm, over the next four weeks we've got four webinars
coming up which explores each of the aspects of FAIR Data, findable,
accessible, interoperable and reusable and you can see the short
URL down the bottom of this screen. So feel free to have a look at
those webinars and see if that's something that you'd be interested in
coming along to.
Today we have a pretty stellar line up I have to say, and people from
all around Australia. We've got Frankie Stevens who is going to be
talking about the Intersect model, Frankie's in Sydney.

Meeting the most unmet need – RDM Training for researchers, HDR students and data
trainers Page 2 of 17
Poh Lin Teow from Edith Cowen in Perth and Poh Lin's going to
talking to us about top 10 marine science research data things.
Roxanne Missingham and Imogene Ingram from ANU, talk data to me.
Liz Stokes there in Sydney from UTS is going to be talking about
research data management training for librarians. But what she's
talking about is actually applicable to many different groups who do
research and data training.
Now I'm going to hand over to our first speaker, Frankie Stevens.
Frankie Stevens: I'll start with a little on Intersect. We're a not-for-profit organisation that
provides a variety of e-research services to our members, which at
present are scattered across New South Wales, Victoria and the ACT.
We also edge into Queensland a little.
One of our most valued services is that of our - the training that we
provide. This year we're going to deliver over 200 courses which
equates to approximately one every working day of the year. This is
one of our most popular member services and it keeps us pretty busy.
Historically our training courses have covered rather more advanced
research computing challenges. We train in a range of different topics
that are organised into compute, software and data elements. The
data elements are ones that perhaps require less technical
background and this is where research data management sits in.
One of the challenges that we have as a company is that our
membership is broad and diverse. If you recall my first slide you would
have seen that geographically our members are in numerous
locations across a number of different states and some members
even have a number of different campuses.
Our members also have different capabilities when it comes to
supporting their researchers in data management. Some have e-
research departments, some have very active libraries that assist
researchers, and some have policies and procedures in place and so

on. Some even have infrastructure that provides tools and software to
assist with data management, but others don't.
We're also in a fortunate position in which we're being approached
more and more these days to deliver training to external organisations
such as government departments et cetera.
Given this landscape, we've been building our training capabilities to
be scalable and flexible enough to deliver research data and our other
training opportunities in a more tailored fashion to our members and
potential future members.
Traditionally we've had a very hands on approach to training. We
organise group training headed up by an expert trainer with the local
institutional Intersect e-research analysts on hand to provide a one on
one approach where this is required.
This model is hugely popular across our whole membership. It actually
enables attendees to get help with practical exercises and it
introduces them to the local e-research analysts so they can call on
them for future help.
It actually also means that our researchers can use a training course
as an opportunity to present a real-life research challenge that they've
been grappling with and they often get a resolution to this then and
there.
This model is also good for Intersect as it can lead to further research
streamlining activities that we can provide through our consultation
and software engineering service.
We actually enable all our attendees to access all course materials
and exercises after the course so they can actually continue their
technology learning after the course has concluded.
In research data management this means that our attendees leave
with the beginnings of a research data management plan which they
can actually continue to refine as their research goes on.

But as you can imagine, this model, whilst it's really popular, it doesn't
lend itself all that well to scalability. We have a number of members
who have distributed campuses which means that catering to
researchers on different campuses means holding a greater number
of courses with all the associated logistical challenges.
Along with new opportunities arising from the ACOLA review
recommendations around the HDR experience, we've actually been
able to work with some members to evolve our training model.
We've been developing a digital research program for HDR students
that provides a skills development framework which engenders
students with broader transferable skills. This program consists of six
different awareness raising and training courses. There's an
introductory course, a course on digital footprint, citizen science, big
data, data based concepts and of course research data management.
But what does this look like practically? Well the biggest change is
that we've moved to a fully digital format and this enables our
members who have distributed campuses to access webinars from
one, or two, or three or perhaps multiple universities even, at once.
Students can log in from home or wherever they like really.
This is good from the university perspective as we're catering for their
students at any location, which is something that our members report
they've always struggled to respond to when providing the teaching
resources to their more remote students. It also means that Intersect
has fewer logistics to deal with and we can train more of our members
in one go.
What about the hands on approach that I mentioned before? This is
really hugely popular. But our model that we've come up with, our
digital model, does incorporate a secondary online expert that can
respond to student questions and provide additional context, and
perhaps even enabled those solutions to real life research challenges
just as before.

We're even looking into the possibility of having local research data
management resources participate here. For example we could have
some local librarians assisting with the online moderating or
information provision. Again this enables student's awareness of the
local resources available to them which they can refer to in the future.
Where the university requires it we've also actually introduced an
assessment process into the program which consists of a series of
digital comprehension Q&As that a student completes throughout the
webinar. This verifies that we're actually providing a quality teaching
environment and let's face it, it also enforces the required attention
span.
The program materials are also being provided to students at
completion so that they can refer back to these and investigate items
accordingly. For research data management this means further info is
available on local policies, procedures, and they also get to initiate
that digital research data management plan.
Finally, we actually have the potential to blend both of these models
into one where we might have a large cohort of students assemble in
the computer lab on a main campus for the program webinars and the
local institutional ERA or e-research analyst can actually be present in
the room to provide that more traditional one on one experience
where needed.
As before this not only introduces students to the E-research Analyst
but it also provide avenues for any eventual consultation potential.
We've also been working on a continuous improvement initiative
where we enable surveys and follow up aspects. This is helping us to
build a view as to the qualitative elements to our training offerings in
addition to the more traditional quantitative ones.
I'll leave it there but I'm happy to provide more information to people
offline. Thanks Karen.

Karen Visser: Thank you Frankie. Poh Lin works with the library at the Edith Cowen
University in Perth and she's cleverly adapted the top 10 - sorry the 10
health and medical things developed last year by Kate LeMay, into a
flexible online activity based on the needs of a particular group and in
this case it's the marine science community.
Thank you Poh Lin, I'll pass over to you now.
Poh Lin: Good afternoon everyone, thank you for inviting me to talk about the
10 Marine science Things lib guide. I'm currently in the library with the
ECU library research services team, promoting awareness on RDM
issues to our researchers is one of our team's responsibilities.
Today I'll share some information on why we developed the lib guide,
how we are currently using it at ECU, the benefits of it, and a quick
demo of the lib guide.
Earlier this year the ECU library had the opportunity to work on our
third [ANDS] project, the project focused on the marine science
research area. Similar to the previous ands project, the ECU library
used this project as a means to help enhance the visibility of the ECU
research data sets and to continue to find ways to promote RDM
awareness among our researchers.
Last year 10 ECU library staffed participated in the ANDS 23 Things
program and together we learnt a lot more on RDM. The ANDS
project was very timely and provided us with the great opportunity to
apply the knowledge that we have learnt from the 23 Things.
For those who participated in the 12 Things last year you may
remember that at the end of the program a challenge was thrown to
the participants to find ways to repurpose the 23 Things material. One
of the great examples of how it could be done was of course the 10
medical and health things.
As one of the project activities we decided to do something similar in
the marine science area, but we wanted to do it using an online library
guide format.

Here's what we did, the 23 Things and 10 medical and health things
contents were first reviewed and materials that could be repurposed
for the marine science lib guide were identified. The selected
materials were then used to create a word version of the lib guide. A
copy of the word version is available from the handouts box today.
Using the work version as the basis, the marine science lib guide was
created on the library website.
What you see on the screen now is the homepage of the lib guide,
each tab links you to a different thing and in each thing you will see
the different activities.
While developing the lib guide, advice was sought from the very kind
and experienced ANDS data consultants, namely [Aggie Gideon],
Katherine Tattersall and Julia Martin, together they provided some
great examples of marine science resources that could be included in
the lib guide.
We then got our science subject library to help review the first draft of
the lib guide. Then together with another team member the existing
ECU RDM guide was reviewed and update to imbed the guide.
The lib guide went live in mid-May this year. Since this is an open
resource, anyone can now use it as a self-paced learning program to
learn on RDM.
We can also use it as a teaching tool when we run our RDM sessions
with the HDR students. The online lib guide software was chosen to
create this lib guide because it allows flexible designing of the guide. It
also enables inclusions of materials such as imbedded videos and
images. These resources make the lib guide visually attractive and
help to enhance the user's experience in the online environment.
The lib guide software also allows tracking of usage statistics. Thus
far, since it went live we have had more than 700 views on the tabs
provided.

Apart from the tabs, all the hyperlinks created in the lib guide can also
be monitored. This allows easy assessment and helps identify if there
are any gaps in the content and areas for improvement. We can easily
update or add new materials as and when necessary.
For those who are using the same lib guide software, the software
also allows very quick and efficient replication. If other librarians from
ECU or any other organisations wish to create other subject based 10
things guides.
Overall I believe the 10 marine science lib guide provides us with an
easy way to reach out to the ECU researchers with more relevant
marine science RDM materials.
Apart from benefiting our ECU users, working on repurposing the
materials to develop this lib guide indirectly allowed the librarians to
learn much more about RDM itself, especially with regards to the
marine science data sets and resources. It was great to have worked
with the different colleagues from my own library as well as with the
ANDS team developing the lib guide.
The link to the lib guide and the original word version was currently
available on the ANDS website. Recently we also found links to the lib
guide populated on the website of two other organisations. One is on
the Western Australian Marine Science Institute website, and the
other is on the Agricultural Information Management Standards blog.
Hopefully there will be more subject based 10 things that can be
developed in the future for the community.
Thank you.
Karen Visser: Thank you, that was excellent. Okay I'm now going to pass over to
Roxanne Missingham and Imogen Ingram. Roxanne Missingham is
the ANU university librarian and Imogen Ingram works for the
Information Literacy Program and ANU in Canberra. Their, talk data to
me and publish and prosper online modules are a lively mix of videos,
reading, quizzes and case studies. Over to you.

Roxanne: Thank you. Hello everybody, lovely to be here today.
We started on this journey from various interesting spaces that you do
in a university when we developed a lib guide, we developed data
management training, been doing fairly traditional stuff. We had a
community that was seeking to really understand how they should
grasp e-resource data management, e-research data management
issues and a range of different challenges within a large Group of
Eight university.
When we started on the journey that has produced the modules that
you will be able to see when you click on it at the end of the show, our
researchers felt a little bit like these penguins on this road that they
were being equipped in various places with little bits of information
and then they would try to jump in and hit their head on a sea of
barriers when they knew there were resources and support within the
university that was not transparent to them.
Some people were - knew a little bit about the super computer and felt
frustrated, some people knew a little bit about the Australian Data
Archive and we were particularly talking to early career academics
and high degree research students and they felt they were very much
at sea.
In the university we created a number of discussion areas, we've had
three e-research committees set up and complete their terms trying to
figure out what the university should do on a large scale, and that
turned out to be too big of a problem to solve in any way. But a
number of the clear gaps to us were things that we started to build.
Our first little segue after the lib guide which has been around for a
while, was to create a data management - single website for the
university where we pointed to the code of practice, all the university
policies and procedures, all the information that was on faculty
websites and we try to bring it together in one cohesive way.
That took us 12 months of discussion investigation, and there were
probably still things that we didn't find at the end, and it was a

collaborative effort between the research services staff, the library
staff, the repository staff, the IT staff, and the research training staff,
we have a separate area that supports HDR training.
Everything that we learnt from that was what we took along our
journey. When we really were talking to the audience about what we
need and there were various workshops it became clear that we
needed to use some different pedagogies and different tools to be
able to really create a very successful solution. Particularly focusing
on the researchers who were going to be researchers of the future.
So we looked at MOOCs and in looking at MOOCs we thought we're
going to be the ninjas. We may not be here from 2am to 5am but
we're going to try this new technology to see if we can use the sorts of
learning that's happening about education and knowledge transfer in a
way that will help us learn how to communicate about [unclear]
communications.
We mapped out six modules and one of them was the research data
module. We put out this lovely structure which started with the first
one so people would understand the concepts and we very quickly
decided what we needed to do was get how to publish and how to
manage your data out very quickly because the need was so strong.
MOOCs were important to us because we were thinking in many
ways, as previous speakers have, about what - how can we support
the researcher who, at 2am - our hypothetical researcher - 2am in
[unclear] on a bit of, not very good bandwidth necessarily, needs to
just do that first bit of data management or the last bit of data
management in order to finish their project, their thesis, and they don't
necessarily want to go through the whole course end to end and
they're certainly not going to come to our one hour courses.
How can we reach out to people who are living in this world of
Facebook, Instagram, Snapchat and MOOCs is the way to do it.

We really tried to bring those concepts together we talked to a lot of
people who had done MOOCs who said to us authenticity is the most
important thing. Not a huge lot of very high quality processed material.
We worked with a lot of people who we thought would be able to
contribute so that we would be able to package everything up in short,
sharp collections of information under themes with quizzes.
The two things that I wanted to particularly emphasise before I move
on to Imogen is that we used what was called, at that stage, a SPOC
so it's not a MOOC which is the Massive Online Open Courses, it's a
sort of Special Private Online Course.
Everything is fully openly available and it's not like the MOOCs where
you have to join, you can join at any time and the intention was to get
lots of three to five minute slots where people can talk about an
important issue and we had fantastic buy in from around the world.
Also to be a bit entertaining and use new technology.
You will see when you see it that it doesn't have all of the ANU
branding that you see on those slides because we went, as we say,
off-piste into an exciting space and used a number of different
technologies we hadn't used before. So that was very useful for us.
The other characteristic for us was we actually asked, all the way
through, particularly early career academics, what they wanted. I think
they would see us walking around the campus and duck sometimes
so that we wouldn't ask - sometimes we offered them coca cola and
pizza, very successful, I highly recommend it as a strategy. But we
really wanted to be quite intuitive in building our solution that met their
needs and being able to flexible.
I'll hand over to Imogen.
Imogen Ingram: Thanks Roxanne. Okay so our module, talk data to me, you can see
that we have a great line up of presenters and it was wonderful
working with all these people from NCI, from the ARC, from, let's have
a little look there.

ANDS, we also scored a presentation from Doctor Tony Hey the Chief
Data Scientist from the Science and Technology Facilities Council in
the UK.
This particular module, as Roxanne said, is one that sits amongst the
series of modules. We've looked at data management plans, data
citation, [funder's] data requirements.
Again with that idea, as Roxanne said of assisting researchers
navigate the scholarly communications and publishing environment,
specific in this case to research data management, but not just
researchers now, this is researchers of the future. Getting people into
this space thinking about what's required really early on, even as early
as say, late high school students.
Our wonderful presenters listed there, you can see them as I said, and
we have also got more in the pipeline. So those other modules are
being developed, we are really fortunate to have had, again amazing
presenters from Yale, Oxford and the input and different perspectives
from a number of experts in this area.
So watch this space, and as you can see it's definitely been a team
effort, it's been wonderful collaborating both within the library and
between other areas of the ANU as well as students who have
definitely played a role in the development of this module and the
series. Okay, thanks.
Roxanne: Thanks.
Karen Visser: Thank you, Roxanne and Imogen. I'll move on now to Liz Stoke. Liz is
a data librarian at UTS in Sydney and her presentation is about
training the data trainers. As we said, this one in particular is aimed at
librarians but she makes the case for both RDM and data science
training needs and how communities frame RDM training for their
members, in this case, librarians. Thank you Liz, over to you.
Liz Stoke: Alright hi everyone. Okay so research data management training, this
question, what are we training librarians for, has been weighing

heavily on my mind actually. So today I want to talk about how we
frame - how the library community frames research data management
for our own development as well as meeting our client community
needs and what's been happening at UTS.
When I first got here I thought that my plan was fairly simple.
Research data management is the future of libraries, all I had to do
was teach research data management to my colleagues, turn them all
into librarians - data librarians - provoke the university into action on
research data management by any means necessary, figure out what
works and do more of that. But it wasn't actually that simple.
Research data management may be the future but it's hard to promote
that future when it looks like another freaking web form.
At UTS research data management is largely driven by an asset
management imperative, which is very important actually.
We have policy which mandates data management plans for projects
including PhD students and higher degree research. We also have
stash records for research data which are mandatory as well for any
researchers publishing data, even as a supplementary item to a
journal article, that's going to be official in January next year and that
will be very interesting for us.
In general the library is responsible for research data management
training and the e-research group in the IT division at UTS develops
the infrastructure.
But my question is how you say RDM, not just how do you say it, but
how we say it. I'm increasingly uncomfortable with these ideas around
RDMs and DMPs. These are terms that we've created by and for
librarians.
I think that RDM is as much an artificial construct as a DMP, which is
more often than not an administrative requirement or a matter of
compliance rather than actual thing that is supporting the doing of
research.

I've realised that my anxiety around research data management has
come from having the responsibility of persuading my colleagues to
make space for a new area of expertise which is still as relatively
abstract as the myriad of training resources and online courses that
are available to learn it, whilst still remaining fully committed to
business as usual.
Moreover, on reflection I learnt how to be a data librarian by actually
doing it, not through doing a course. It was through working on
projects, learning how to be a - partnering with researchers. The
skillset required had more in common with a data scientist than
traditional librarians.
But of course I think every librarian here probably begs to differ with
that straight away. But as a data librarian, a growth mindset and
problem solving skills are potentially more valuable than the myriad
pieces of the puzzle that makeup the many matricies of research data
management life cycles and modules.
At UTS we're kind of doing research data management by stealth.
Internally my department is piloting a tinker time project using learning
analytics expertise from UTS data scientists to develop our growth
mindset and data literacies.
For example, I'm in a little affinity group of amateur game developers
and my project will be creating a character called Bogan the Librarian
who must curate research data for a death metal cultural studies
researcher. Well that's just level one, I haven't got beyond that yet.
Also we're developing introductory data management, which is mainly
data cleaning, but also including data visualisation skills for
undergraduate faculty classes. We're also promoting open data sets
for teaching as part of our open educational resources for our
academic teaching staff.
These examples are not strictly in the research data management
world because that tends to be skewed more towards, or aimed at,
our research communities, but I believe they're gateway drugs toward

it. I guess we could call it Seeding the Commons for want of a better
word.
Speaking of other research data management by stealth initiatives,
the recent [ResBaz] that we held in Sydney in July, is an excellent
example of that. The Research Bazar is a series of workshops on
coding and software skills for being able to teach non-computational
researchers that kind of computational thinking that comes with using
[R] or Python to harness the power of these new next generation
research tools.
We discovered that research students and staff want things like data
science training and they want supporting data management tools,
applications and software. So they want to know what will help them,
how to do research faster, smarter, more competitively. We found that,
from our pilot in July researchers also want to build a community and
learn about research tools across disciplines and institutional
boundaries.
This is where we imbed research data management by offering
training in these open source tools and software where things like
version control are integrated in things like GitHub.
Alongside the ResBaz software workshops we also provided some
research data management workshops by that very name and I was -
I fell off my chair when I realised that that was the second most
popular item in our expression of interest form that we sent out
initially.
I don't know about you but we don't get more than 40 people
registering for our regular research data management workshops. So
there's something else that is happening there that enables people to
see research data management as something valuable and useful for
them rather than just RDM on its own.
This year UTS has also established a joint steering committee in e-
research and research data management training. This is more at the
executive level, and that's going to allow us to imbed research data

management across a broader spectrum of specialised research
support and data science services.
Finally, we're integrating librarians into research - e-research
infrastructure projects such as our - the Provisioner Project that e-
research is running, and giving librarians roles such as the go-to
trainers for research tool training. For example, lab notebooks and in
the future, REDCap, the research data capture application.
Also by giving librarians roles in, say, user acceptance testing of our
in-house research data management tool stash, we can engage them
as experts developing those specifically data librarian skills.
To answer the question I started with, this is what we're training our
librarians for. Three roles as active participants in providing enhanced
research support services.
We're training them as instructors in delivering real data management
skills from undergraduate through to our researcher communities.
We're training them as advisors to deliver research data management
by stealth in a way, saying ah would you like research data
management with that as one might offer fries or curly fries or
something like that.
Finally, as engaged librarians collaborating in e-research
infrastructure development, who can knowledgeably refer clients to
more specialised data services. For example, statistical or
instructional high performance computing. Being able to perform quite
a triage role in that way.
That's the end of my presentation, thanks Karen.
Karen Visser: Thank you, Liz, that's a really interesting way that UTS has integrated
all of the - the various aspects of research data management training.
What we're going to be doing now is we're just going to be finishing off
but firstly I'd like to thank all of our presenters today, I really
appreciate the effort that you've gone to and mostly the fact that the
work that you're doing is open, and that people can talk to you, they

can reuse the work that you're doing, and that they can take the ideas
and contextualise them for their specific institution or perhaps you
may have a group in your university or institution who are particularly
keen on data management. Maybe some of them have been caught
on the publisher's policies, desperate to publish and can't because
their data linkage isn't available. So now we've got the opportunity to
come together as a big community and really to share all these things.
I'd remind you to look at 23 Things in particular because what you've
got there is you've got a group of materials, you can use a small
activity from one of them, you don't have to use all of them, you can
use it online from our site, you can take it - it's there in a PDF
document, so you can just take it down and use it in whatever format
you like.
END OF TRANSCRIPT

Transcript - Meeting the most unmet need - RDM Training for researchers, HDR students and data trainers

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Transcript - Meeting the most unmet need - RDM Training for researchers, HDR students and data trainers