Map-based dashboard design with open government data for learning and analysis of industrial innovation environment

Chenyu Zuo, Linfang Ding, Xiaoyu Liu, Hui Zhang, Liqiu Meng

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Open government data has great potential to support various stakeholders for multiple purposes, such as participatory planning, smart city services, and strategic decision-making. However, many barriers stand in the way of efficient learning and analysis of the data. Suitable tools are needed to overcome these barriers. In this study, we designed and implemented a map-based dashboard called InDash to represent the spatial and semantic information of the industrial innovation environment at different levels of detail. We collected the open data from the statistical yearbook in 2015 Jiangsu, China, and selected 24 relevant factors from the categories of economy, inhabitance, infrastructure, and research & development to illustrate the design. To ensure the usefulness of InDash, we first analyzed and summarized the information needs and design requirements from the potential users. We then proposed the design requirements and designed the interface of InDash. Moreover, we evaluated the effectiveness of InDash using the think-aloud approach with 30 participants. The experiment results show that the users can efficiently learn and reason about the industrial innovation environment through InDash without intensive training.

Original languageEnglish
Pages (from-to)97-113
Number of pages17
JournalInternational Journal of Cartography
Volume9
Issue number1
DOIs
StatePublished - 2023

Keywords

  • Map-based dashboard
  • geovisualization
  • open government data
  • user-centered design

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