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Reality mining of animal social systems

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Reality mining of animal social systems. / Krause, Jens; Krause, Stefan; Arlinghaus, Robert; Psorakis, Ioannis; Roberts, Stephen; Rutz, Christian.

In: Trends in Ecology and Evolution, Vol. 28, No. 9, 2013, p. 541–551.

Research output: Contribution to journalReview articlepeer-review

Harvard

Krause, J, Krause, S, Arlinghaus, R, Psorakis, I, Roberts, S & Rutz, C 2013, 'Reality mining of animal social systems', Trends in Ecology and Evolution, vol. 28, no. 9, pp. 541–551.

APA

Krause, J., Krause, S., Arlinghaus, R., Psorakis, I., Roberts, S., & Rutz, C. (2013). Reality mining of animal social systems. Trends in Ecology and Evolution, 28(9), 541–551.

Vancouver

Krause J, Krause S, Arlinghaus R, Psorakis I, Roberts S, Rutz C. Reality mining of animal social systems. Trends in Ecology and Evolution. 2013;28(9):541–551.

Author

Krause, Jens ; Krause, Stefan ; Arlinghaus, Robert ; Psorakis, Ioannis ; Roberts, Stephen ; Rutz, Christian. / Reality mining of animal social systems. In: Trends in Ecology and Evolution. 2013 ; Vol. 28, No. 9. pp. 541–551.

Bibtex - Download

@article{570e21d0527e42758926c4b479c55ee4,
title = "Reality mining of animal social systems",
abstract = "The increasing miniaturisation of animal-tracking technology has made it possible to gather exceptionally detailed machine-sensed data on the social dynamics of almost entire populations of individuals, in both terrestrial and aquatic study systems. Here, we review important issues concerning the collection of such data, and their processing and analysis, to identify the most promising approaches in the emerging field of {\textquoteleft}reality mining{\textquoteright}. Automated technologies can provide data sensing at time intervals small enough to close the gap between social patterns and their underlying processes, providing insights into how social structures arise and change dynamically over different timescales. Especially in conjunction with experimental manipulations, reality mining promises significant advances in basic and applied research on animal social systems.",
author = "Jens Krause and Stefan Krause and Robert Arlinghaus and Ioannis Psorakis and Stephen Roberts and Christian Rutz",
note = "The authors acknowledge funding from the BBSRC (David Phillips Fellowship, grant BB/G023913/1 to C.R.), the German Federal Ministry for Education and Research (project Besatzfisch, www.besatz-fisch.de) in the Program of Social-Ecological Research (grant 01UU0907 to R.A.), and the BehaviourType project granted by the Gottfried-Wilhelm-Leibniz Association's Pact for Innovation and Research (to J.K. and R.A.).",
year = "2013",
language = "English",
volume = "28",
pages = "541–551",
journal = "Trends in Ecology and Evolution",
issn = "0169-5347",
publisher = "ELSEVIER SCIENCE LONDON",
number = "9",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Reality mining of animal social systems

AU - Krause, Jens

AU - Krause, Stefan

AU - Arlinghaus, Robert

AU - Psorakis, Ioannis

AU - Roberts, Stephen

AU - Rutz, Christian

N1 - The authors acknowledge funding from the BBSRC (David Phillips Fellowship, grant BB/G023913/1 to C.R.), the German Federal Ministry for Education and Research (project Besatzfisch, www.besatz-fisch.de) in the Program of Social-Ecological Research (grant 01UU0907 to R.A.), and the BehaviourType project granted by the Gottfried-Wilhelm-Leibniz Association's Pact for Innovation and Research (to J.K. and R.A.).

PY - 2013

Y1 - 2013

N2 - The increasing miniaturisation of animal-tracking technology has made it possible to gather exceptionally detailed machine-sensed data on the social dynamics of almost entire populations of individuals, in both terrestrial and aquatic study systems. Here, we review important issues concerning the collection of such data, and their processing and analysis, to identify the most promising approaches in the emerging field of ‘reality mining’. Automated technologies can provide data sensing at time intervals small enough to close the gap between social patterns and their underlying processes, providing insights into how social structures arise and change dynamically over different timescales. Especially in conjunction with experimental manipulations, reality mining promises significant advances in basic and applied research on animal social systems.

AB - The increasing miniaturisation of animal-tracking technology has made it possible to gather exceptionally detailed machine-sensed data on the social dynamics of almost entire populations of individuals, in both terrestrial and aquatic study systems. Here, we review important issues concerning the collection of such data, and their processing and analysis, to identify the most promising approaches in the emerging field of ‘reality mining’. Automated technologies can provide data sensing at time intervals small enough to close the gap between social patterns and their underlying processes, providing insights into how social structures arise and change dynamically over different timescales. Especially in conjunction with experimental manipulations, reality mining promises significant advances in basic and applied research on animal social systems.

M3 - Review article

VL - 28

SP - 541

EP - 551

JO - Trends in Ecology and Evolution

JF - Trends in Ecology and Evolution

SN - 0169-5347

IS - 9

ER -

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