D4Humanities: Deposit of Dissertation Data in Social Sciences & Humanities – A Project in Digital Humanities
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Lecture/Conference
Transcript: English(auto-generated)
00:00
Good morning everybody. Before starting to describe our project, just one preliminary remark. I think in the panel I'm the only one who's not a service provider. I'm scientist and consultant and I'm accompanying and steering project but without any responsibility
00:30
of the service. So this will explain the character, the nature of what I will describe now
00:42
because it's a mixed project. It's a project with a developmental aspect and research funded by our regional government and the European Institute of Social Science and Humanities.
01:01
It's a project in Digital Humanities, D for Humanities. We are a team with academic librarians and scientists and the course of the paper is in this room, Helene. This is for the overview. So some of people here in the audience will remember we started our work
01:32
on dissertation on PhDs many years ago. We started with studies about findability of French
01:44
dissertations and then moved on later with studies about accessibility in open context and then the last part of our studies was about research data. Research data
02:06
is a complementary material to a PhD dissertation. You may remember two years ago we presented a keynote at Amsterdam conference and now we are moving on with a research development project on the one hand to implement what we evaluated and assessed
02:27
so far and then to move on further with research on dissertation as data and the impact of the open science environment and e-science environment on the dissertation themselves.
02:48
So there are four parts in our project. I will present them very shortly here. The paper will contain more information and if you are interested in we can discuss it. The first part is a survey we conducted two years ago and we presented
03:05
results at Amsterdam. A large online survey on our campus about research data management, literacy and needs and to be continued this year with qualitative survey interviews with
03:24
volunteers. The first result is it's not a hot topic on our campus. Very few volunteers we continue and we now contact directly the head of projects and project managers
03:48
with more success so far. Very few volunteers, one part conscious about guidelines, about standards. I think the most interesting thing so far in our survey was the impact
04:10
on our campus social science and humanities, the impact of ethics committee for research data management colleagues especially from sociology or psychology. They do not speak about data
04:23
management plan but they have a long since a long time experience with exactly what we call because they are submitting procedures and discussing procedures with the committee.
04:43
Their needs are advice, specifically legal advice, so this is topic cast here and we discussed also in other conferences, legal advice and advice from
05:02
the West technology department and ethics committee. Some of this this advice is already in place, IT department ethics, other we have to manage perhaps through the academic library and data service. They need data storage
05:25
and they are interested to discuss topics on the individual and particular with information professionals. The second perhaps for data provision, the most important part of this project
05:43
is a data workflow. We are implementing right now a data workflow for PhD thesis with data. We do not create a new infrastructure but we use the national infrastructure in place
06:00
for ETDs. This is in place for 10 years now as a star system and what we are doing is to create a second workflow from the moment on the PhD will submit his or her dissertation
06:23
in the national star system for related data if he or she wants to deposit the related data sets so can do it in a national system based in Paris specifically for social science and humanities.
06:45
It's called NACALA, NACALA is a data repository for data sets and we collect those. That's all what we are doing but all what you're doing is
07:04
needs a lot of adjustment between metadata, between standards, issues about granularity, data structure and description. So we made a couple of choices
07:23
about identifier for instance the NACALA system normally uses handle not the UIs so we start with handle legal aspects how to be sure at the moment of the submission that the data set is cleared and what quality are the good data are not good data
07:46
it's an open question so far. So far we suppose that when a PhD is accepted
08:03
the data set related data set should be okay but probably there will be a stronger investment by the PhD committee. Third part of our research project is about research data
08:22
just as Mark yesterday I remember his first question was yo what are data what is your definition of data and this each time when you present research about data and surveys the first question is yes tell us what is data so we included this part in our study and
08:45
we started to communicate about it will take a long time to present this in details there's a exhaustive paper in French good for Mark bad for the rest you will find it it's
09:01
openly freely available already we presented it at a conference in Toulouse earlier this year what you should know about data is there is no definite exhaustive definition about data there's a link with a big data definition volume you may know and then a different aspect you
09:29
should keep in mind the link with the community so data signification different relevance according to the different communities and communities does not mean only disciplines but
09:44
instruments tools there's a link with the finality with the process research process and with the function of research data in this research project especially for the validation of
10:02
of results and publications then there's a link with recording there's a professional if you prefer library related aspects with a liquid creation and structure our sense the granularity of data and then a strong link also with a factual nature
10:29
often when you have a bit you find this definition about of data you will get a typology definition of a very different type of data and then
10:42
there will be a long list of typology of a different type of data this is something we will wait at the moment study about types in the recipe data repository and not only in the repository but we're going
11:03
to the directory directory to the repository themselves and looking for definition of content what does it mean spreadsheet what does it mean textual documents and so on and so on the last part of the project is a project in
11:28
two years we are in the first year and this will be a project for the second half it's about the evolution of phd dissertations themselves this i think it's the relevant part here for
11:50
community how do the dissertation develop in this new environment especially the
12:04
prescription impact about writing content format submission process and legal status and think of phd dissertation from text and data mining approach dissertations are data so
12:26
how can we exploit dissertation as a data and perhaps also in the future and i think there already are data dissertation as we already have data papers so
12:41
this is the part we will do this year a landscape study and then we will create a scientific consortium more of a larger project we submit next year or the year after and this is the
13:04
end of my presentation if you're interested in this specific topic the evolution development of dissertation in the field of context of open science and e-science and data infrastructure and so on so come join us tell us what you're doing and perhaps join the consortium thank you
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