Collaborative data exploration interfaces - From participatory sensing to participatory sensemaking

Filonik, Daniel, Bednarz, Tomasz P., Rittenbruch, Markus, & Foth, Marcus (2015) Collaborative data exploration interfaces - From participatory sensing to participatory sensemaking. In Engelke, Ulrich, Bednarz, Tomasz P., Heinrich, Julian, Klein, Karsten, & Nguyen, Quang Vinh (Eds.) 2015 Big Data Visual Analytics, BDVA 2015, Institute of Electrical and Electronics Engineers Inc., Hobart, Australia, pp. 123-125.

View at publisher


As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.

Impact and interest:

0 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

67 since deposited on 02 Oct 2015
25 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 87981
Item Type: Conference Paper
Refereed: No
Additional URLs:
Keywords: co-located collaboration, participation, sensemaking, data visualisation, visual analysis
DOI: 10.1109/BDVA.2015.7314289
ISBN: 9781467373432
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Computer-Human Interaction (080602)
Australian and New Zealand Standard Research Classification > BUILT ENVIRONMENT AND DESIGN (120000) > DESIGN PRACTICE AND MANAGEMENT (120300) > Digital and Interaction Design (120304)
Divisions: Current > Schools > School of Design
Current > QUT Faculties and Divisions > Creative Industries Faculty
Current > Institutes > Institute for Future Environments
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 [Please consult the author]
Copyright © 2015 by the Institute of Electrical and Electronic Engineers, Inc. All rights reserved.
Deposited On: 02 Oct 2015 03:01
Last Modified: 25 Apr 2016 13:58

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page