Enhancing Spatial Data Analysis Public Policy: The Influence of Multimodal Interaction Research on the AIDEA Project

Impact summary

The research article "Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis with Dashboards" has made a significant contribution to the field of spatial data analysis, influencing the Spanish government's policy framework. The article was cited in the policy document "ANNEX I PROPOSAL FOR THE CONTENT OF THE CHALLENGE OF THE CPM OF THE AIDEA PROJECT," which is part of an initiative by the Innovative Platform for Integrated Analysis of Spatial Data of Andalusia. The document outlines strategies for enhancing public policy and private sector activities through the innovative use of spatial data and advanced analytical tools such as AI, machine learning, and deep learning.

Research and engagement activities leading to impact

Rationale: The ability to explore and analyze data through visualizations is critical for decision-making across various domains, including public policy. Traditional interaction methods, such as mouse and touch, may fall short in allowing users to express complex queries and efficiently analyze data. Our research aimed to address these limitations by developing a system that combines natural language and direct manipulation interactions to facilitate visual data analysis.

Research Work and Engagement Activities: The research, conducted in collaboration with York University (Canada) and CUET (Bangladesh), focused on developing and evaluating the Multimodal Interactions System for Visual Analysis (MIVA). MIVA allows users to interact with data visualizations using both natural language and direct manipulation, enhancing the ease and accuracy of complex data exploration. The system was tested on multiple dashboards, including a COVID-19 dashboard, and was empirically evaluated through a user study involving twenty participants. The findings demonstrated that MIVA improves the flow of visual analysis by enabling fluid, iterative exploration and data refinement. MIVA is publicly available at https://infovisualizer.github.io/Covid-19-Visualization/, and a video demonstration can be viewed at https://www.yorku.ca/enamulh/video/MIVA.mp4.

End-users Involved: The primary end-users of this research include policymakers, data analysts, and researchers who require advanced tools for spatial data analysis. The citation by the Spanish government highlights the research’s relevance to national and regional administrations involved in public policy planning and implementation.

Relevant Inputs: Collaborative input from international academic partners and access to diverse data sources, including COVID-19 case data, were critical in developing and testing the MIVA system. Publication in a top-tier journal (IEEE Access) ensured wide dissemination and recognition of the research within the academic and policy-making communities.

Research outputs associated with the impact

The key output of this research was the publication of the article "Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis with Dashboards" in 2021 in IEEE Access, a high-impact journal (SJR Q1). The paper has been recognized for its innovative approach to integrating multimodal interactions in visual data analysis. Additionally, the MIVA system is publicly accessible online, providing a practical tool for ongoing use and further research.

Researcher involvement

As the lead researcher, I was responsible for the conceptualization, design, and development of the MIVA system. My role included overseeing the empirical evaluation of the system and coordinating with collaborators from York University and CUET. My involvement ensured the research addressed practical challenges in data visualisation and produced outcomes relevant to both academic and policy-making contexts.

Outcomes of research leading to impact

The research has been implemented in practice by being cited in the Spanish government's policy document for the AIDEA project. This project aims to enhance the impact of spatial data in public policy and private sector activities by integrating innovative tools like AI and machine learning. The citation of our work in this context demonstrates its practical value in informing strategies for spatial data analysis and its application in various policy areas, including environment, health, agriculture, and transportation.

Beneficiaries of the impact

Primary Beneficiaries: The primary beneficiaries of this research are the Spanish government agencies involved in the AIDEA project, which aims to optimize the use of spatial data in public policy. Researchers and data analysts in the field of geospatial analysis also benefit from the methodologies developed in this study.

Secondary Beneficiaries: The broader community, including private sector entities involved in geospatial technologies and the public, benefits indirectly from improved public policy planning and implementation based on enhanced spatial data analysis.

Reach: The impact of this research extends across Spain, particularly in Andalusia, where it influences regional policy-making. The methodologies and insights may also inform similar initiatives in other regions and countries.

Details of the impact achieved

Significance: The citation of our research in the AIDEA project’s policy document highlights its importance in shaping strategies for integrating advanced analytical tools with spatial data. The research contributes to a comprehensive solution for spatial data analysis that is not yet available on the market, addressing critical needs in public policy and private sector innovation.

Evidence: The policy document "ANNEX I PROPOSAL FOR THE CONTENT OF THE CHALLENGE OF THE CPM OF THE AIDEA PROJECT" cites our research as one of the 27 scholarly outputs informing its strategies. This citation serves as concrete evidence of the research’s influence on national policy and its role in advancing the use of spatial data in public and private sectors. The public availability of the MIVA system further enhances its impact by allowing broader access to the tool for ongoing research and practical applications.

Impact date	2023
Category of impact	Public policy Impact
Impact level	International