Special Track: Location Intelligence

With the proliferation of sensors, IoT, social media, and human mobility data, along with spatial imagery and remote sensing, geospatial big data presents an emerging frontier of research and innovation in the system sciences and across various sectors and industries. This mini-track invites papers that analyze and mine geospatial big data (along with non-spatial data) using cutting-edge scientific approaches to provide spatial insights to complex problems and systems in business, government, and society. Both theoretical and empirical papers are welcome in a variety of analytics contexts such as big data analytics, social media analytics, text and image analytics, web analytics, network analytics, and mobile analytics. Research papers will be solicited across a range of topics, including but not limited to:

• Geospatial Big Data and Commercial Services: Analyses that explores the advancements in geospatial big data for business functions, including in store behavior analysis, variety and price optimization, product placement design, improve performance, labor inputs optimization, and distribution and logistics optimization.
• Geospatial Big Data and Health Care: Analyses that addresses data advancements in clinical decision support systems, individual analytics applied for patient profiling, personalized medicine, and disease pattern identification.
• Geospatial Big Data and the Public Sector: Analyses that explores the use of geospatial big data for improving transportation, accessibility, social services, service delivery, and policy decision-making.
• Geospatial Big Data and Personal Location Data: Research related to indoor and outdoor individual location tracking.
• Geospatial Big Data and Location Intelligence: Analyses that introduce and enhance such emerging areas of space-time modeling, spatial analytics, locational decision-making, geography of the sharing economy, and social media analytics.

Minitrack Chair:

Joe Aversa
Ryerson University
javersa@ryerson.ca

This minitrack provides a research forum aiming to discuss the varied facets of Geographic Information Systems (GIS) for sustainable development and climate action. The present time is characterized by emerging technologies, such as artificial intelligence (AI), the Internet of Things (IoT), cloud computing services, and advanced data analytics, which can improve economic conditions and reduce societal harms. Industry trends increasingly focus on sustainable business practices, responsiveness to climate change, and related social and environmental issues. GIS (or location analytics) is one of the key technologies of the present time; IoTs generate an enormous amount of data, a big portion of which is spatial (or location) data that can be stored in the Cloud and analyzed in real time for better decision-making and prediction. Location data and spatial features embedded in such emerging technologies often facilitate and accelerate digital innovations, e.g., technological advancements in connected vehicles, connected homes, smart cities, and Industrial IoTs, which are bound to create not just extensive opportunities for economic gains, but also a positive externality of ecological sustainability.

This minitrack solicits and invites completed research papers from both academics and practitioners across the following topics, but not limited to:

• GIS and environmental sustainability
• GIS for climate action
• GIS for biodiversity
• GIS for addressing climate, water, energy, and agriculture as described by the United Nations
  SDGs
• GIS and sustainability in Industry 4.0
• Societal issues with big spatial data
• Mobile location-based applications and services
• Socio-technical aspects of GIS involved with sustainable development
• Benefits of GIS and location analytics
• Emerging areas of GIS and location analytics

Minitrack Co-Chairs:

Namchul Shin (Primary Contact)
Pace University
nshin@pace.edu

Daniel Farkas
Pace University
dfarkas@pace.edu

This minitrack aims to foster research and collaboration in the expansive, multi-disciplinary area of locational intelligence. Digital transformation is leading to application of locational data for organizational intelligence and decision making in the areas of business operations, marketing, management information systems, supply chain management and logistics, environment, natural resources, healthcare, retail, sharing economy, public safety, risk mitigation and disaster management, among others. Scholarly research papers are sought that apply a variety of theories and empirical techniques, quantitative, and qualitative, to understand how location, geography, and related data are increasingly important to incorporate into the system sciences. There is a need to develop new theories and modify existing ones for the systems sciences that incorporate spatial data, locational intelligence, and geographical concepts. Current concepts of data science, big data, trust, and privacy need attention in addressing locational intelligence research questions.

Minitrack Co-Chairs:

James Pick (Primary Contact)
University of Redlands
James_Pick@redlands.edu

Avijit Sarkar
University of Redlands
Avijit_Sarkar@redlands.edu

Following the Millennium Goals, the United Nations have adopted in 2015, 17 Sustainable Development Goals (SDGs), brought together under the umbrella of the 2030 Agenda. Based on 1,691 common targets, to be achieved by 2030, the SDGs address the major planetary challenges: eradicating all forms of poverty, in all countries; protecting the planet; and, ensuring prosperity for all (three pillars of sustainable development). SDGs have been designed essentially to be used at macro-scale level. Looking for ways to apply them locally at different geographic scales, in local government, departments and agencies, organizations and businesses, municipalities and cities, local communities… remain very challenging, despite the recent deployment, by the UN, of a series of simple actions, of a mobile application and even of a Chat Bot for the general public.

Implementing and monitoring the UN Sustainable Development Goals (SDGs) at the city scale is indeed not trivial. It requires dedicated research, specific methods, and tools. Even the SDG 11 “Sustainable cities and communities” does not provide “turnkey” or “one size fits” all solution. Smart cities approach, Smart technologies (sensors networks and IoT, urban Artificial Intelligence, geospatial intelligence technologies and data…) should be considered as a way of addressing implementation processes, indicators design and feeding and, SDSs\targets monitoring issues. This Special Issue aims to provide a platform for researchers and practitioners to present new research and developments in the following area. Areas of interest for this minitrack include, but are not limited to, the following topics:

• Using geospatial data and place–based technologies to build indicators for urban SDG monitoring,
• Developing urban SDG strategies based on smart city platform,
• Educating and engaging citizens and local communities in urban SDG strategies,
• Feeding urban SDG monitoring system with location technologies,
• Integrating SDG in smart city projects,
• SDG and urban digital transition,

The minitrack welcomes Original Research, Dialogues, Brief Research Report, Community Case Study, Conceptual Analysis, Research Statement and Perspectives.

Minitrack Co-Chairs:

Stéphane Roche (Primary Contact)
Laval University
stephane.roche@scg.ulaval.ca

Sehl Mellouli
Laval University
Sehl.Mellouli@fsa.ulaval.ca

This Minitrack aims to explore geospatial analytics topics (e.g., geospatial methods, geospatial tools, geo-visualization, artificial intelligence, big data, geo-medicine, public policies, cybersecurity, governance, among others). Authors’ submissions are encouraged to link research to sustainable and innovative approaches for education, training, competencies, workforce development, and curricular innovation. We welcome applied, conceptual, theoretical, technological, methodological, and empirical contributions employing various methods (e.g., empirical research, teaching cases, curriculum innovation, design-oriented research, case studies, and action research).

Minitrack Co-Chairs:

Asish Satpathy (Primary Contact)
Arizona State University
asatpat2@asu.edu

Michael Erskine
Middle Tennessee State
University michael.erskine@mtsu.edu

Andres Diaz Lopez
Arizona State University
adiazlop@asu.edu