Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges

G.A. García-Chapeton (Corresponding Author), F.O. Ostermann, R.A. de By, M.J. Kraak

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
60 Downloads (Pure)

Abstract

Collaboration across disciplines is recognized as one of the great
challenges for research in visual analysis of geographic information (GeoVisual Analytics, GVA). Considering the increasing availability of geodata and the complexity of analytical problems, the need to advance the support for collaborative work is becoming more pressing and prominent. This article contributes to this objective by reviewing the state‐of‐the‐art of the support for collaborative work in GVA systems and by identifying research challenges and proposing strategies to address them. We conducted a systematic review, resulting in the identification of 13 collaborative systems, 6 distinct collaborative
techniques, and 3 research challenges. We conclude that GVA is
moving toward more effective support of multidisciplinary and
cross‐domain collaborative analysis. However, to materialize
this potential, research is needed to improve the support for hybrid collaborative scenarios, cross‐device collaboration, and
support for time‐critical and long‐term analysis.
Original languageEnglish
Pages (from-to)640-663
Number of pages24
JournalTransactions in GIS
Volume22
Issue number3
DOIs
Publication statusPublished - 19 Aug 2018

Fingerprint

visual analysis
analysis
pressing

Keywords

  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-GOLD

Cite this

@article{f66a3321a5e04cca9ab29d4a9c5dcb7b,
title = "Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges",
abstract = "Collaboration across disciplines is recognized as one of the greatchallenges for research in visual analysis of geographic information (GeoVisual Analytics, GVA). Considering the increasing availability of geodata and the complexity of analytical problems, the need to advance the support for collaborative work is becoming more pressing and prominent. This article contributes to this objective by reviewing the state‐of‐the‐art of the support for collaborative work in GVA systems and by identifying research challenges and proposing strategies to address them. We conducted a systematic review, resulting in the identification of 13 collaborative systems, 6 distinct collaborativetechniques, and 3 research challenges. We conclude that GVA ismoving toward more effective support of multidisciplinary andcross‐domain collaborative analysis. However, to materializethis potential, research is needed to improve the support for hybrid collaborative scenarios, cross‐device collaboration, andsupport for time‐critical and long‐term analysis.",
keywords = "ITC-ISI-JOURNAL-ARTICLE, ITC-GOLD",
author = "G.A. Garc{\'i}a-Chapeton and F.O. Ostermann and {de By}, R.A. and M.J. Kraak",
year = "2018",
month = "8",
day = "19",
doi = "10.1111/tgis.12344",
language = "English",
volume = "22",
pages = "640--663",
journal = "Transactions in GIS",
issn = "1361-1682",
publisher = "Wiley-Blackwell",
number = "3",

}

Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges. / García-Chapeton, G.A. (Corresponding Author); Ostermann, F.O.; de By, R.A.; Kraak, M.J.

In: Transactions in GIS, Vol. 22, No. 3, 19.08.2018, p. 640-663.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges

AU - García-Chapeton, G.A.

AU - Ostermann, F.O.

AU - de By, R.A.

AU - Kraak, M.J.

PY - 2018/8/19

Y1 - 2018/8/19

N2 - Collaboration across disciplines is recognized as one of the greatchallenges for research in visual analysis of geographic information (GeoVisual Analytics, GVA). Considering the increasing availability of geodata and the complexity of analytical problems, the need to advance the support for collaborative work is becoming more pressing and prominent. This article contributes to this objective by reviewing the state‐of‐the‐art of the support for collaborative work in GVA systems and by identifying research challenges and proposing strategies to address them. We conducted a systematic review, resulting in the identification of 13 collaborative systems, 6 distinct collaborativetechniques, and 3 research challenges. We conclude that GVA ismoving toward more effective support of multidisciplinary andcross‐domain collaborative analysis. However, to materializethis potential, research is needed to improve the support for hybrid collaborative scenarios, cross‐device collaboration, andsupport for time‐critical and long‐term analysis.

AB - Collaboration across disciplines is recognized as one of the greatchallenges for research in visual analysis of geographic information (GeoVisual Analytics, GVA). Considering the increasing availability of geodata and the complexity of analytical problems, the need to advance the support for collaborative work is becoming more pressing and prominent. This article contributes to this objective by reviewing the state‐of‐the‐art of the support for collaborative work in GVA systems and by identifying research challenges and proposing strategies to address them. We conducted a systematic review, resulting in the identification of 13 collaborative systems, 6 distinct collaborativetechniques, and 3 research challenges. We conclude that GVA ismoving toward more effective support of multidisciplinary andcross‐domain collaborative analysis. However, to materializethis potential, research is needed to improve the support for hybrid collaborative scenarios, cross‐device collaboration, andsupport for time‐critical and long‐term analysis.

KW - ITC-ISI-JOURNAL-ARTICLE

KW - ITC-GOLD

UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2018/isi/garcia_ena.pdf

U2 - 10.1111/tgis.12344

DO - 10.1111/tgis.12344

M3 - Article

VL - 22

SP - 640

EP - 663

JO - Transactions in GIS

JF - Transactions in GIS

SN - 1361-1682

IS - 3

ER -