Evidence map›Paper›PMID 30940026›Full record

ArticleJournal of the Royal Society, Interface2019

Fly with the flock: immersive solutions for animal movement visualization and analytics.

Karsten Klein, Björn Sommer, Hieu T Nim, Andrea Flack, Kamran Safi, Máté Nagy, Stefan P Feyer, Ying Zhang, Kim Rehberg, Alexej Gluschkow and 4 more

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Beyond the horizon: immersive developments for animal ecology research.Visual computing for industry, biomedicine, and art · 2023
    Article
  5. Spatially resolved transcriptomics in immersive environments.Visual computing for industry, biomedicine, and art · 2022
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Karsten Klein1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.
Björn Sommer1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.
Hieu T Nim2 Faculty of Information Technology, Monash University , Melbourne , Australia.
Andrea Flack4 Max-Planck-Institute for Ornithology , Radolfzell , Germany.
Kamran Safi4 Max-Planck-Institute for Ornithology , Radolfzell , Germany.
Máté Nagy4 Max-Planck-Institute for Ornithology , Radolfzell , Germany.
Stefan P Feyer1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.
Ying Zhang1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.
Kim Rehberg1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.
Alexej Gluschkow1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.
Michael Quetting4 Max-Planck-Institute for Ornithology , Radolfzell , Germany.
Wolfgang Fiedler4 Max-Planck-Institute for Ornithology , Radolfzell , Germany.
Martin Wikelski4 Max-Planck-Institute for Ornithology , Radolfzell , Germany.
Falk Schreiber1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the movement of animals is important for a wide range of scientific interests including migration, disease spread, collective movement behaviour and analysing motion in relation to dynamic changes of the environment such as wind and thermal lifts. Particularly, the three-dimensional (3D) spatial-temporal nature of bird movement data, which is widely available with high temporal and spatial resolution at large volumes, presents a natural option to explore the potential of immersive analytics (IA). We investigate the requirements and benefits of a wide range of immersive environments for explorative visualization and analytics of 3D movement data, in particular regarding design considerations for such 3D immersive environments, and present prototypes for IA solutions. Tailored to biologists studying bird movement data, the immersive solutions enable geo-locational time-series data to be investigated interactively, thus enabling experts to visually explore interesting angles of a flock and its behaviour in the context of the environment. The 3D virtual world presents the audience with engaging and interactive content, allowing users to 'fly with the flock', with the potential to ascertain an intuitive overview of often complex datasets, and to provide the opportunity thereby to formulate and at least qualitatively assess hypotheses. This work also contributes to ongoing research efforts to promote better understanding of bird migration and the associated environmental factors at the global scale, thereby providing a visual vehicle for driving public awareness of environmental issues and bird migration patterns.

Indexed as

Behavior, AnimalComputer TerminalsVirtual RealityAnimalsEnvironmentHumansMovementanimal movement analysisaugmented realitycollective behaviourimmersive analyticsvirtual reality

Identifiers

PMID30940026
PMCPMC6505562

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.