Ming-Hsiang Tsou

Integrated Mobile GIS and Wireless Internet Map Servers for Environmental Monitoring and Management

With the progress of mobile GIS technology there is a great potential for adopting wireless communications and Internet mapping services for regional environmental management programs and natural habitat conservation. This paper provides an overview of a NASA-funded research project that focuses on the development of mobile GIS tools and wireless Internet Map Server (IMS) services to facilitate environmental monitoring and management tasks. By developing and testing wireless web-based map/image servers, mobile GIS applications, and global positional systems (GPS), this research created an integrated software/hardware infrastructure for a prototype mobile GIS application. The mobile GIS prototype allows multiple resource managers and park rangers to access large-size, remotely sensed images and GIS layers from a portable web server mounted in a vehicle. Users can conduct real-time spatial data updates and/or submit changes back to the web server over the wireless local area network (WLAN). This paper discusses in general the major components of mobile GIS, their current technological limitations, and potential problems during implementation. Key research agenda for mobile GIS are identified with suggestions for future research and development.

A Dynamic Architecture for Distributing Geographic Information Services

Traditional GISystems are no longer appropriate for modern distributed, heterogeneous network environments due to their closed architecture, and their lack of interoperability, reusability, and flexibility. Distributed GIServices can provide broader capabilities and functions for data management, browsing, and exchange. This paper introduces a dynamic architecture for distributing GIServices. The term dynamic indicates that the architecture is constructed temporarily by connecting or migrating geodata objects and GIS components across a network. The intention of the paper is to overview components and protocols necessary for a workable implementation of dynamically linked GIServices. The paper introduces a metadata scheme for both geodata objects and software components, and proposes an implementation framework based on existing languages, computing architectures and web services. In the framework, GIS nodes form the basic processing unit. All GIServices can be accomplished through collaboration between GIS nodes. The design of the presented framework emphasizes scalability, reusability, and dynamic integration. Current distributed computing environments cannot fully support dynamic architectures for technical and other reasons. Throughout the discussion, we distinguish what currently can be implemented from what cannot. We summarize costs and benefits of adopting a dynamic GIServices paradigm in a final section.

Developing a grid-enabled spatial Web portal for Internet GIServices and geospatial cyberinfrastructure

Geospatial cyberinfrastructure integrates distributed geographic information processing (DGIP) technology, high-performance computing resources, interoperable Web services, and sharable geographic knowledge to facilitate the advancement of geographic information science (GIScience) research, geospatial technology, and geographic education. This article addresses three major development issues of geospatial cyberinfrastructure: the performance of grid-enabled DGIP services, the integration of Internet GIService resources, and the technical challenges of spatial Web portal implementation. A four-tier grid-enabled Internet GIService framework was designed for geospatial cyberinfrastructure. The advantages of the grid-enabled framework were demonstrated by a spatial Web portal. The spatial Web portal was implemented based on current available Internet technologies and utilizes multiple computing resources and high-performance systems, including local PC clusters and the TeraGrid. By comparing their performance testing results, we found that grid computing (TeraGrid) is more powerful and flexible than local PC clusters. However, job queuing time and relatively poor performance of cross-site computation are the major obstacles of grid computing for geospatial cyberinfrastructure. Detailed analysis of different computational settings and performance testing contributes to a deeper understanding of the improvements of DGIP services and geospatial cyberinfrastructure. This research demonstrates that resource/service integration and performance improvement can be accomplished by deploying the new four-tier grid-enabled Internet GIService framework. This article also identifies four research priorities for developing geospatial cyberinfrastructure: the design of GIS middleware, high-performance geovisualization methods, semantic GIService, and the integration of multiple GIS grid applications.

The Complex Relationship of Realspace Events and Messages in Cyberspace: Case Study of Influenza and Pertussis Using Tweets

Background Surveillance plays a vital role in disease detection, but traditional methods of collecting patient data, reporting to health officials, and compiling reports are costly and time consuming. In recent years, syndromic surveillance tools have expanded and researchers are able to exploit the vast amount of data available in real time on the Internet at minimal cost. Many data sources for infoveillance exist, but this study focuses on status updates (tweets) from the Twitter microblogging website. Objective The aim of this study was to explore the interaction between cyberspace message activity, measured by keyword-specific tweets, and real world occurrences of influenza and pertussis. Tweets were aggregated by week and compared to weekly influenza-like illness (ILI) and weekly pertussis incidence. The potential effect of tweet type was analyzed by categorizing tweets into 4 categories: nonretweets, retweets, tweets with a URL Web address, and tweets without a URL Web address. Methods Tweets were collected within a 17-mile radius of 11 US cities chosen on the basis of population size and the availability of disease data. Influenza analysis involved all 11 cities. Pertussis analysis was based on the 2 cities nearest to the Washington State pertussis outbreak (Seattle, WA and Portland, OR). Tweet collection resulted in 161,821 flu, 6174 influenza, 160 pertussis, and 1167 whooping cough tweets. The correlation coefficients between tweets or subgroups of tweets and disease occurrence were calculated and trends were presented graphically. Results Correlations between weekly aggregated tweets and disease occurrence varied greatly, but were relatively strong in some areas. In general, correlation coefficients were stronger in the flu analysis compared to the pertussis analysis. Within each analysis, flu tweets were more strongly correlated with ILI rates than influenza tweets, and whooping cough tweets correlated more strongly with pertussis incidence than pertussis tweets. Nonretweets correlated more with disease occurrence than retweets, and tweets without a URL Web address correlated better with actual incidence than those with a URL Web address primarily for the flu tweets. Conclusions This study demonstrates that not only does keyword choice play an important role in how well tweets correlate with disease occurrence, but that the subgroup of tweets used for analysis is also important. This exploratory work shows potential in the use of tweets for infoveillance, but continued efforts are needed to further refine research methods in this field.

Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election

We introduce a new research framework for analyzing the spatial distribution of web pages and social media (Twitter) messages with related contents, called Visualizing Information Space in Ontological Networks (VISION). This innovative method can facilitate the tracking of ideas and social events disseminated in cyberspace from a spatial-temporal perspective. Thousands of web pages and millions of tweets associated with the same keywords were converted into visualization maps using commercial web search engines (Yahoo application programming interface (API) and Bing API), a social media search engine (Twitter APIs), Internet Protocol (IP) geolocation methods, and Geographic Information Systems (GIS) functions (e.g., kernel density and raster-based map algebra methods). We found that comparing multiple web information landscapes with different keywords or different dates can reveal important spatial patterns and “geospatial fingerprints” for selected keywords. We used the 2012 US Presidential Election candidates as our case study to validate this method. We noticed that the weekly changes of the geographic probability of hosting “Barack Obama” or “Mitt Romney” web pages are highly related to certain major campaign events. Both attention levels and the content of the tweets were deeply impacted by Hurricane Sandy. This new approach may provide a new research direction for studying human thought, human behaviors, and social activities quantitatively.

The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance

Background Existing influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza. Objective There were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego. Methods Tweets containing the keyword “flu” were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was “valid”, or from a user who was likely ill with the flu. Results Correlations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier. Conclusions Compared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data.

Visualization of social media: seeing a mirage or a message?

Cyberspace (Gibson 1984) is a digital wonderland for people to meet with their friends, to share their ideas, and to create their dreams. Social media are built upon cyberspace to enable hybrid mul...

Editorial: human dynamics in the mobile and big data era

Human dynamics is a term that has been used and investigated by researchers in various fields from very different perspectives. Barabasi’s (2005) publication of ‘The origin of bursts and heavy tail...

Research challenges and opportunities in mapping social media and Big Data

Social media and Big Data have transformed our world into interconnected cyberspace and realspace. Cartographers can now trace, monitor, and map the spread of social movements, disease outbreaks, nature hazards, and popular events by digitally collecting social media and Big Data with locational contents, such as global positioning system tags and user location profiles. The dynamic characteristics of social media and Big Data provide a great research opportunity for cartographers to map and analyze human behaviors, communications, and movements. However, there are many challenges and pitfalls in cartographic research associated with spatiotemporal analysis of social media contents and Big Data. This short paper will address important research challenges and major opportunities for cartographers to process and visualize Big Data and social media.

An Operational Metadata Framework for Searching, Indexing, and Retrieving Distributed Geographic Information Services on the Internet

A comprehensive metadata scheme for distributed geographic information services should include multiple types of information services, including geodata objects, software components, and web map services. This paper examines the existing metadata standards and their implementation frameworks and presents an operational, object-oriented, hierarchical metadata architecture as an alternative solution for searching, indexing, and retrieving distributed GIServices on the Internet. An operational metadata framework can facilitate the establishment of self-manageable, self-describable GIS web services, which can be freely combined and used on the Internet. Hierarchical metadata repositories can provide a meaningful metadata archive structure and can improve metadata search mechanisms, where geospatial datasets and services are grouped and organized by their unique features or functions. By collaborating with operational metadata contents and hierarchical metadata repositories, the new metadata framework will help users and systems to access on-line geodata objects, software components, and web map services efficiently and effectively.