research.chalmers.se

The aim to break the circle of despair

Kristin Olofsson

Chalmers University of Technology

Rolf Henrik Mikael Urban Kristin

An (extra) ordinaryresearch.chalmers.se-team

Make a research information system!

(projects first)

???

What showed up in our minds?

Pure at Aarhus university

Another picture

Converis at Åbo Akademi University

Another

(Part of) our data modell

My picture

Moritz Stefaner. Truth and beauty operations

Wise or ignorant?

executive group

” Teams [..] must be

empowered to design the solution to the business

problems they are tasked

Jeff Gothelf

Dr Rachel Curwen, Univ of YorkUniv. of York

Implementing

Pure – a case

study

@IFFIS14, Stockholm, Sweden

© Rachel Curwen

CRISCurrent Research Information System

● Research output (publications, patents…)● Grants & Projects● Persons research events & activitites● Researcher CV● ...

Step 1:

a service that handles grant funded research projects

It doesn’t matter which system you choose, if you don’t have caught the incentive to use it

1. What service would be valuable for whom, and actually being used?

2. How can we get the data and keep it updated?

Existential angst

That’s where UX comes in...

SCRUM + (Lean) UX

Value curve

Sketch!

On whiteboards,

together, visualize

everything.

Outstanding for

shared

understanding.

GOB!!(Get out of the f*n building)

Effect / impact map

Academic

First question from everyone we talked to...

● Vice chancellor’s order

● Money

● Personal benefit and reuse in valuable

places

Possible incentives

There is one thing you need in these systems, commercial or self-build, to have any use for

them - that’s DATA.

1. Local grants database

2. Cordis (EC)

3. Manual registration -Library

4. (Big Swedish funding agencies)

From where do we get the data?

Personal judgement needed

Launch 1

“If they say a service will solve

everything for everyone, it will probably solve very little for very

few.

Me and a lot of other ppl

Academic

Will not update until personal benefit. This is later, folks!

[Possible personal values]

research.chalmers.se

research.chalmers.se

research.chalmers.se

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1. Systems, technique or data modelling is not the hard part. The tricky part is to find incentives and ways to keep the data updated.

2. Libraries are good at data modelling beyond publications.

Lessons learned

3. In house development makes it possible to act agile and to quickly adapt to your organisation’s needs.

Lessons learned

The answer?

Be sure that someone has incentives to update the data or

do it yourself!

kristin.olofsson@chalmers.se@krolofsson