Detailed program

Fair data management and open science in ecology, wildlife management and conservation

June 11. – 12. 2019

Seminar invitation can be found here.

June 11th:

Open seminar at NINA-huset



09:30 – 10:00

Registration and coffee

Session chair: Bob O’Hara, NTNU

10:00 – 10:10

Welcome (Einar Hjorthol, Director of Norwegian Biodiversity Information Centre)

10:10 – 10:30

Towards FAIR data management of ecological data? (Erlend B. Nilsen, NINA)

10:30 – 10:50

Challenges in dissemination of biodiversity knowledge (Arild Lindgaard, Norwegian Biodiversity Information Centre)

10:50 – 11:10

Why, when and how do we need ecological data for environmental policy and management (Ingunn Limstrand, Norwegian Environment Agency)

11:10 – 11:30

Norwegian participation in international biodiversity research infrastructures (Frank Hanssen, NINA)

11:30 – 12:30


Session chair: Eveliina Päivikki Kallioniemi, NBIC

12:30 – 13:00

Open Science in the Nordics and the EOSC-Nordic project (Andreas Jaunsen, Special advisor, NeIC)

13:00 – 13:30

The new joint Swedish Biodiversity Data Infrastructure (SBDI)

(Debora Arlt, Swedish University of Agricultural Sciences)

13:30 – 14:00

Data integration on the global stage and the forward direction of GBIF (Tim Robertson, Head of informatics – GBIF)

14:00 – 14:30

Coffee break

Session chair: Katrine Eldegard, NMBU

14:30 – 15:00

New statistical methods for data integration in ecology and beyond (Nick Isaac, Centre for Ecology and Hydrology)

15:00 – 15:30

Education and training resources for FAIR data management and scientific reuse of data (Vigdis Vandvik, University of Bergen)

15:30 – 16:00

Summary and discussion (Anders G. Finstad, NTNU)


June 12th:

Workshop 1: NeIC and Nordic collaboration

Workshop-leader: Frank Hanssen, NINA



Workshop 2: Legacy data: prioritization, data types, sources and tools

Workshop leader: Anders G Finstad, NTNU.

What kind of ecological data should be prioritized for archiving and re-use retrieval preparation? We will have a special focus on legacy data. Legacy data include a large backlog of digitalization and documentation of data collected throughout (mainly) the last century. In particular, as a consequence of increased focus on ecological research during the 1970s, a large surge of ecologist is currently passed or closing in on retirement. Consequently, Irreplaceable observations from the last decades are being lost due to inappropriate storage formats or lack of documentation. Concurrently, in a field such as ecology that relies on unique non-replicable observations from nature, data rescue missions to secure legacy data and make them available to the current generation of scientists are a most pressing task. However, the task is daunting, both due to the share volume of information, due to the huge variety of storage formats and common lack of associated documentation (metadata), but also due to legal issues. Here, we will ask questions and facilitate discussions around:

  • Practical solutions for data discovery, data rescue and FAIRification of legacy data
  • How do we prioritize between data-sets and data-types?
  • Licencing and legal issues?



09:00 – 09:10

Welcome and intro (Anders G. Finstad, NTNU)

09:10 – 09:20

Example of a successful data-rescue mission: the case of ptarmigan monitoring in Norway (Erlend B. Nilsen, NINA)

09:30 – 09:40

Digitizing legacy data through crowdsourcing: “Dugnadsportalen” as case study (Rukaya Sarah Johaadien, GBIF Norway)

09:40 – 10:05

Why does legacy data matter? New tools and approaches for the integration of unstructured and historical data in ecological research (Joseph Chipperfield, NINA)

10:05 – 10:20

Discussion and comments

10:20 – 10:35

Coffee break

10:35 – 11:10

Legal issues and licencing (Wouter Koch)

11:10 – 12:00

Data paper discussion (Bob O’Hara)

12:00 – 13:00




Workshop 3: How could and should Open Science be implemented in biodiversity education?

Workshop leaders: Vigdis Vandvik and John-Arvid Grytnes, UiB and Dag Endresen, GBIF-Norway

The Open Science movement represents a paradigm shift in science – it is currently transforming not only the standards and payment schemes for scientific publication, but how we think and act around every aspect of science, from our daily research practices, data, scientific publications, to teaching, learning, and communication of science. Future researchers will need to know and master new tools and practices, but also think about data and science in new ways, to succeed in the new landscape.

The current science curricula taught at the biology programmes at our universities are not reflecting this rapid transformation – we are not making use of the opportunities represented by Open Science, but we are also not preparing students for the challenges.

There are new opportunities rapidly emerging to integrate open data in education – students can reuse available data in their studies, and we can teach them to make their own data openly available as part of their course or thesis work. In this way, students can be part of the ‘real’ scientific enterprise during their studies, using and contributing to ‘real’ science.

The aim of this workshop is to discuss these issues, share experiences and ideas. The intended outcome is to write a discussion piece in a journal (e.g., commentary in Methods in Ecology and Evolution)



12:00 – 13:00


13:00 – 13:30

What is Open Science, and why is it important for students? (Dag Endresen)

13:30 – 14:00

Why, how, and when could and should Open Science be implemented in our educations? (Vigdis Vandvik)

14:00 – 14:15

Coffee break

14:15 – 16:00

How are we dealing with data in biology educations today? (Case studies – examples from participants)

Way forward: Group discussions; summary in plenary


In a FAIR open science world…

Group members / email:


…students will need new skills

For discussion:

  • What are critical FAIR open science skills students should acquire?
  • Which of these do we already cover, and which are missing in the education we offer today?
  • How can these skills be acquired? Existing/new methods, examples, cases…
  • When during the studies should this happen?
  • What are the main opportunities? Challenges?


…students should learn using real data

For discussion:

  • Examples of real data used in education today?
  • When, how, and for what learning outcome can students use real data?
  • Pros and cons of using real data in education

…student’s data should be shared

For discussion:

  • Examples of student contributions of real data to science? Examples from different levels, types, learning situations, learning outcomes (beyond thesis work…). Published examples, if you have 🙂 ?
  • Additional opportunities, ideas of how students could contribute data?
  • For what learning outcome

…we should share educational resources

For discussion:

  • which educational resources should we devellop now, and for what?

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