Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3406522.3446007acmconferencesArticle/Chapter ViewAbstractPublication PagesirConference Proceedingsconference-collections
extended-abstract

Toward a Conceptual Model for Users' Online Open Government Data Interaction

Published: 14 March 2021 Publication History

Abstract

The rapid development of open government data and the increasing attention on data use/reuse have stimulated many studies on data-related issues. The extant studies show that even though OGD portals have been rapidly developed in this age of data, there are still various challenges when users interact with data. Therefore, this dissertation attempts to identify the contextualized user challenges, understand user behaviors when interacting with OGD, and ultimately, propose solutions that can assist users in using OGD. Furthermore, aiming to ameliorate the issues that data is hard to find and to be understood, a mixed-method design will be employed, including a transaction log analysis, a content analysis, and semistructured interviews. Also, the research sites accessed are two local-level OGD portals: OpenDataPhilly and Western Pennsylvania Regional Data Center. Local-level portals are closely connected with local communities and neighborhoods, which have a direct impact on a citizen's daily life. The results of this dissertation are expected to contribute to the fields of Human Information/Data Interaction, Human Computer Interaction and OGD Use.

References

[1]
Kholod Alsufiani, Simon Attfield, and Leishi Zhang. 2017. Towards an instrument for measuring sensemaking and an assessment of its theoretical features. In Proceedings of the 31st British Computer Society Human Computer Interaction Conference. BCS Learning & Development Ltd., 86.
[2]
Earl Babbie. 2001. The practice of social research (9th ed.). Wadsworth/Thomson Learning, Belmont, CA, USA.
[3]
Peter Conradie and Sunil Choenni. 2014. On the barriers for local government releasing open data. Government Information Quarterly 31 (2014), S10--S17.
[4]
Jonathan Crusoe, Anthony Simonofski, Antoine Clarinval, and Elisabeth Gebka. 2019. The impact of impediments on open government data use: Insights from users. In 2019 13th International Conference on Research Challenges in Information Science (RCIS). IEEE, 1--12.
[5]
Brenda Dervin. 1999. Chaos, order and sense-making: A proposed theory for information design. Information design (1999), 35--57.
[6]
Susan Dumais, Robin Jeffries, Daniel M Russell, Diane Tang, and Jaime Teevan. 2014. Understanding user behavior through log data and analysis. In Ways of Knowing in HCI. Springer, 349--372.
[7]
Bernard J Jansen. 2006. Search log analysis: What it is, what's been done, how to do it. Library & information science research 28, 3 (2006), 407--432.
[8]
Marijn Janssen, Yannis Charalabidis, and Anneke Zuiderwijk. 2012. Benefits, adoption barriers and myths of open data and open government. Information systems management 29, 4 (2012), 258--268.
[9]
Gary Klein, Brian Moon, and Robert R Hoffman. 2006. Making sense of sensemaking 1: Alternative perspectives. IEEE intelligent systems 4 (2006), 70--73.
[10]
Laura M Koesten, Emilia Kacprzak, Jenifer FA Tennison, and Elena Simperl. 2017. The Trials and Tribulations of Working with Structured Data: -a Study on Information Seeking Behaviour. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 1277--1289.
[11]
Danny Lammerhirt, Oscar Montiel, and Mor Rubinstein. 2017. The State of Open Government Data in 2017. (2017).
[12]
Jingjing Liu, Michael J Cole, Chang Liu, Ralf Bierig, Jacek Gwizdka, Nicholas J Belkin, Jun Zhang, and Xiangmin Zhang. 2010. Search behaviors in different task types. In Proceedings of the 10th annual joint conference on Digital libraries. 69--78.
[13]
OECD. 2020. Open Government Data. Retrieved Oct 29, 2020 from https://www. oecd.org/gov/digital-government/open-government-data.htm
[14]
Peter Pirolli and Stuart Card. 2005. The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In Proceedings of international conference on intelligence analysis, Vol. 5. McLean, VA, USA, 2--4.
[15]
Elaine G Toms, Heather O'Brien, Tayze Mackenzie, Chris Jordan, Luanne Freund, Sandra Toze, Emilie Dawe, and Alexandra Macnutt. 2007. Task effects on interactive search: The query factor. In International Workshop of the Initiative for the Evaluation of XML Retrieval. Springer, 359--372.
[16]
Karl E Weick. 1995. Sensemaking in organizations. Vol. 3. Sage.
[17]
Anneke Zuiderwijk, Marijn Janssen, Sunil Choenni, Ronald Meijer, R Sheikh Alibaks, and R Sheikh_Alibaks. 2012. Socio-technical impediments of open data. Electronic Journal of e-Government 10, 2 (2012), 156--172.

Index Terms

  1. Toward a Conceptual Model for Users' Online Open Government Data Interaction

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    CHIIR '21: Proceedings of the 2021 Conference on Human Information Interaction and Retrieval
    March 2021
    384 pages
    ISBN:9781450380553
    DOI:10.1145/3406522
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 14 March 2021

    Check for updates

    Author Tags

    1. human data interaction
    2. open data
    3. open government data
    4. task-based user data behaviors
    5. user ogd interaction

    Qualifiers

    • Extended-abstract

    Conference

    CHIIR '21
    Sponsor:

    Acceptance Rates

    Overall Acceptance Rate 55 of 163 submissions, 34%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 127
      Total Downloads
    • Downloads (Last 12 months)6
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 15 Feb 2025

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media