NGIS Workshop News
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The New GIS workshop was organized by the NSF Spatiotemporal Innovation Center (STC) and hosted by Harvard University Center for Geographical Analyses on Oct 11, 2018. Sixteen directional talks were given by the invited speakers from the academia, NGOs and industry, sharing their thoughts and visions of future GIS in majorly three aspects, and followed by a NGIS survey report by STC Director: 1) Theory and Methodology, 2) Application and Technology, and 3) Computation and Cyberinfrastructure.
Theory and Methodology
Dr. Stephen Ervin (homepage), Assistant Dean for Information Technology at Harvard Design School, Director of Computer Resources, and lecturer in the Department of Landscape Architecture, at the Harvard Graduate School of Design, started off with his thoughts from a GeoDesign point of view. He argued that Geography, Design, People, and Computation are the four key components of GeoDesign. He envisions the Next Generation GIS is the within the 15 component systems of GeoDesign.
Dr. Keith Clarke (homepage) with coauthors published their reviews of the contemporary literature in their book: Advancing GIScience.Two types of forcing factors: ‘rising factors’ and the ones ‘not yet on the map’. He also mentioned Geospatial Privacy, which he sees as a critical issue but has little research and application. He envisions the new skill sets in the high education of Next Generation GIS.
Dr. May Yuan (homepage), University of Texas Dallas, presented her two key points for the next generation GIS: 1. Epistemology: nature of knowledge, justification, and rationality of belief >> understanding knowledge production and verification, 2. A spatiotemporal product of people, events and geospatial context. She also introduced her work on the event analysis and visualization of crime, social events, and world trade.
Dr. Joshua Lieberman (homepage), senior researcher at Harvard Center for Geographic Analysis, talked about six cardinal directions of future GIS: observational, representational, graphical, semantic, cognitive, and computational.
Application and Technology
Dr. Yun Zhang (homepage), Professor of Remote Sensing at the University of New Brunswick. 3D interaction and visualization. He introduced his achievements in 3D change detection & 3D online mapping. He envisions the future of 3D mapping is much more than gaming and movies.
Dr. Jason Ur (homepage), Faculty Director of Center for Geographic Analysis. Representing a consumer of GIS. He introduced his case study on teaching spatial archaeology and conducting fieldwork using mobile GIS and UAV data collection in the Kurdistan Region of Iraq. High Education: promote spatial thinking in every discipline. He also raised the question of how to rapid integration of raster dataset? Better, more accurate devices?
Dr. Peter Bol (homepage), Carswell Professor of East Asian Languages Civilization, and Vice Provost for Advances in Learning at Harvard University emphasizes paying attention to space and the technology related to space, especially in his study in Chinese culture. The importance of building and maintaining (sustainability) of the geospatial platforms, e.g. CGA product ‘WorldMap’.
Dr. Daniel Sui (homepage), vice chancellor for research and innovation at the University of Arkansas, talked about his observations over the past years as division director for the Social and Economic Sciences Division in the Directorate of Social, Behavioral and Economic Sciences at the National Science Foundation. His vision on new generation GIS is on the technological emergence and innovations of Quantum Computing, GeoAI, and so on.
Sudhir Raj Shrestha (Esri) talked about the ongoing machine learning functionalities at ESRI, the current status of spatial data science, distributed collaboration, connecting and evolving research to solutions, and the challenges, oppotunities and need for now and future.
Dr. Wenwen Li (homepage), Associate Professor at Arizona State University, presented her previous work on Polar Data Discovery platform, and her research vision of data discovery, curation, and analysis. Her current work is on Terrain AI.
Dr. Zhenlong Li (homepage), Assistant Professor of GIScience at the University of South Carolina, introduced his research in Hurricane Evacuation Behavior using Big Social Data. He examined the in and out evacuation based on statistical analysis and network based analysis during Hurricane Matthew.
Computation and Cyberinfrastructure
Siva Ravada, Senior Director of Development for the Oracle Spatial and Graph and Mapping technologies at Oracle, Visual analytics and dashboard capabilities in Oracle. How to do things meaningful with all available datasets? The intelligence of the data. He envisions ‘Data Management as a Service’. He emphasizes the data store independence for better data consistency and privacy. Data store needs to fit different data types independently, instead of letting the data to fit into a single multi-model database. He discussed the multi-model prevailing over time, and the current trend is after NoSQL is developed, people are coming back to SQL again. Based on this trend, he envisions the ‘Data Management as a Service’, with data, data management, and interface all independent.
Dr. Shaowen Wang (homepage) started with the question: How do we capture the spatiotemporal trend? He showed us an urban flow analytical visualization. He also discussed the importance of CyberGIS. 1) Application and Science Drivers: the massive data for scientific problem solving (high-resolution DEM, Lidar, Land Cover) 2) Computation and Data Challenges: How could you capture the detail and at the same time grasp the context? Example: continental flood map with high resolution. He mentioned the problem of computational complexity using an example of the spatial computational domain of nearest neighbor search. 3) Science and Technology Frontiers: the integration, interoperability, and reproducibility at scale. The importance and difficulty of maintaining and sustaining a geospatial platform. 4) Social Dimensions: collaborative problem solving and decision making. Example: Intelligent urban metabolism.
Dr. Shashi Shekar (homepage), McKnight Distinguished University Professor at University of Minnesota, talked about his perspectives on new GIS functionalities to harness the spatial data revolution, including CGI and IOT, object recognition, spatial big data, reduce false positives, and assess robustness to MAP dilemma. New research directions include: how to overcome weaknesses of spatial data science, GPS, remote sensing, GIS and spatial databases? For education, how should we adjust the curriculum to emphasize on convergence.
Dr. Axing Zhu (homepage), Professor at University of Wisconsin Madison, introduced his vision of Easy Geographic Computing, which has the four key characteristics: goal-driven, intelligent, easily accessible, and participatory.
Dr. Chaowei Yang (homepage), Director of NSF Spatiotemporal Innovation Center, reported the survey of New Generation GIS and envision of the next generation GIS. He systematically analyzed the NGIS industrial chain as five components including observations, data, computing, modeling, and service. He envisions six research directions: spatiotemporal computing, spatiotemporal intelligence, big spatiotemporal data, spatiotemporal platforms, Internet-based application, and domain application. He discussed the research and economic potentials for the six directions.
Q1. (Wendy Guan) Where does ‘geography’ fit in the big data and technology future?
A1. (Ben Lewis) GeoDesign. Need to find other ways to harness the unique contribution of geography.
(John Lieberman) Why is so hard for mainstream IT to adopt geographic aspects, e.g. lat and lon?
(Chaowei Yang) Are there going to be GIS in the next ten years given main stream IT is taking over almost everything? But mainstream IT is having more geospatial aspects in their research and development.
(May Yuan) 30 years debate between geography and computer science. IT has really advanced GIS, GPS and mapping. They recognize the importance of maps and they still develop useful tools. Is spatial really special?
(Josh Lieberman) They do that by avoiding spatial. Google Maps does not have spatial functions, instead they compute based on a graph, not a full function map. May spatial is just really hard.
(Wendy Guan) Scholars come to us for an easy access to a geographic knowledge. One hand we are picking up every possible new technologies, and then we are forgetting important geographic questions. Our system is not providing so much of geographic knowledge.
(May Yuan) Maybe develop procedure knowledge for GIS and embed them in GIS software. In GIS, we do not have many fundamental knowledge set, instead we have solutions and operations. What are the counterparts in GIS compared to fundamental science? Knowledge production…
(Wendy Guan) Solving types of problems not one problem…
Q2. (Zhenlong Li) There are other departments teaching GIS courses. Do we need to take a lead?
A1. (Josh) This is more of a political question in a interdisciplinary field…
Q3. (Yun Zhang) GIS is more dependent on computer science and technology. Knowledge Procedure. Can we provide more than tools, but more geographic knowledge?
A3. (Sudhir) At ESRI, we hire computer science graduates, but we have them work in an interdisciplinary atmosphere. We bring them into a real-world solution in collaboration with diverse group of people.