HEALTH GeoJunction: place-time-concept browsing of health publications

<p>Abstract</p> <p>Background</p> <p>The volume of health science publications is escalating rapidly. Thus, keeping up with developments is becoming harder as is the task of finding important cross-domain connections. When geographic location is a relevant component of research reported in publications, these tasks are more difficult because standard search and indexing facilities have limited or no ability to identify geographic foci in documents. This paper introduces <it><smcaps>HEALTH</smcaps> GeoJunction</it>, a web application that supports researchers in the task of quickly finding scientific publications that are relevant geographically and temporally as well as thematically.</p> <p>Results</p> <p><it><smcaps>HEALTH</smcaps> GeoJunction </it>is a geovisual analytics-enabled web application providing: (a) web services using computational reasoning methods to extract place-time-concept information from bibliographic data for documents and (b) visually-enabled place-time-concept query, filtering, and contextualizing tools that apply to both the documents and their extracted content. This paper focuses specifically on strategies for visually-enabled, iterative, facet-like, place-time-concept filtering that allows analysts to quickly drill down to scientific findings of interest in PubMed abstracts and to explore relations among abstracts and extracted concepts in place and time. The approach enables analysts to: find publications without knowing all relevant query parameters, recognize unanticipated geographic relations within and among documents in multiple health domains, identify the thematic emphasis of research targeting particular places, notice changes in concepts over time, and notice changes in places where concepts are emphasized.</p> <p>Conclusions</p> <p>PubMed is a database of over 19 million biomedical abstracts and citations maintained by the National Center for Biotechnology Information; achieving quick filtering is an important contribution due to the database size. Including geography in filters is important due to rapidly escalating attention to geographic factors in public health. The implementation of mechanisms for iterative place-time-concept filtering makes it possible to narrow searches efficiently and quickly from thousands of documents to a small subset that meet place-time-concept constraints. Support for a <it>more-like-this </it>query creates the potential to identify unexpected connections across diverse areas of research. Multi-view visualization methods support understanding of the place, time, and concept components of document collections and enable comparison of filtered query results to the full set of publications.</p

A Collaborative Process for Developing Map Symbol Standards

AbstractGeographic information is commonly disseminated and consumed via visual representations of features and their environmental context on maps. Map design inherently involves generalizing reality, and one method by which mapmakers do so is through the use of symbols to represent features. Here we focus on the challenges associated with supporting mapmakers who need to work together to reach consensus on standardizing their map symbols. Based on a needs assessment study with mapmakers at the U.S. Department of Homeland Security, we designed a new, mixed-method symbol standardization process that takes place through a web-based, asynchronous platform. A study to test this new standardization process with mapmakers at DHS revealed that our process allowed participants to identify many issues related to symbol design, meaning, and categorization. The approach elicited sustained, iterative engagement and critical thinking from participants, and results from a post-study survey indicate that participants found it to be useful and usable. Results from our study and user feedback allow us to suggest multiple ways in which our approach and platform can be improved for future applications

GeoCAM: A geovisual analytics workspace to contextualize and interpret statements about movement

This article focuses on integrating computational and visual methods in a system that supports analysts to identify extract map and relate linguistic accounts of movement. We address two objectives: (1) build the conceptual theoretical and empirical framework needed to represent and interpret human-generated directions; and (2) design and implement a geovisual analytics workspace for direction document analysis. We have built a set of geo-enabled computational methods to identify documents containing movement statements and a visual analytics environment that uses natural language processing methods iteratively with geographic database support to extract interpret and map geographic movement references in context. Additionally analysts can provide feedback to improve computational results. To demonstrate the value of this integrative approach we have realized a proof-of-concept implementation focusing on identifying and processing documents that contain human-generated route directions. Using our visual analytic interface an analyst can explore the results provide feedback to improve those results pose queries against a database of route directions and interactively represent the route on a map

An Open GeoSpatial Standards-Enabled Google Earth Application to Support Crisis Management

Google Earth (GE) and related open geospatial technologies have changed both the accessibility of and audience for geospatial information dramatically. Through data rich applications with easy to use interfaces, these technologies bring personalized geospatial information directly to the non-specialist. When coupled with open geospatial data standards, such as Web Map Services (WMS), Web Features Services (WFS), and GeoRSS, the resulting web-based technologies have the potential to assimilate heterogeneous data from distributed sources rapidly enough to support time-critical activities such as crisis response. Although the ability to view and interact with data in these environments is important, this functionality alone is not sufficient for the demands of crisis response activity. For example, GE’s standard version currently lacks geoanalysis capabilities such as geographic buffering and topology functions. In this paper, we present development of the “Google Earth Dashboard ” (GED), a web-based interface powered by open geospatial standards and designed for supplementing and enhancing the geospatial capabilities of GE. The GED allows users to create custom maps through WMS layer addition to GE and perform traditional GIS analysis functions. Utility of the GED is presented in a use-case scenario where GIS operations implemented to work with GE are applied to support crisis management activities. The GED represents an important first step towards combining the ubiquity of GE and geospatial standards into an easy-to-use, data rich, geo-analytically powerful environment that can support crisis management activity

Supporting Humanitarian Relief Logistics Operations through Online Geocollaborative Knowledge Management Brian M. Tomaszewski, Alan M. MacEachren, Scott Pezanowski, Xiaoyan Liu, and Ian Turton

Over the past two years, horrific disasters such as the Asian Tsunami, Hurricane Katrina, and the Pakistan Earthquake have demonstrated the critical need for effective technological infrastructure that is scientifically grounded in geo-visual group interaction theory [1] and humanitarian knowledge management procedures [2] to quickly and effectively facilitate planning for predictable events and post-event response. In this demonstration, we address specific issues that negatively impact the effectiveness of geocollaborative process in disaster relief. These include lack of common group operating picture, lack of command structure understanding and blatant miscommunication and misunderstanding about where relief supplies needed to be delivered, who will deliver them, when they need to be delivered, and the relevancy of deliveries to stricken areas. Our approach improves on existing systems by using methods and technologies that meet the challenges of coordinating the efforts of diverse and spatially distributed private, public, and governmental agencies throughout the world responding to disasters. This is accomplished by applying new forms of distributed geospatial data, technology, and collaboration functionality. We present our progress on the development of the Geocollaborative Web Portal (GWP), an asynchronous, open source geospatial information framework designed to support international group interaction and knowledge management in the context of humanitarian relief logistics

SensePlace3: a geovisual framework to analyze place–time–attribute information in social media

<p>SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted <i>about</i>, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources.</p

GeoCorpora: building a corpus to test and train microblog geoparsers

<p>In this article, we present the GeoCorpora corpus building framework and software tools as well as a geo-annotated Twitter corpus built with these tools to foster research and development in the areas of microblog/Twitter geoparsing and geographic information retrieval. The developed framework employs crowdsourcing and geovisual analytics to support the construction of large corpora of text in which the mentioned location entities are identified and geolocated to toponyms in existing geographical gazetteers. We describe how the approach has been applied to build a corpus of geo-annotated tweets that will be made freely available to the research community alongside this article to support the evaluation, comparison and training of geoparsers. Additionally, we report lessons learned related to corpus construction for geoparsing as well as insights about the notions of place and natural spatial language that we derive from application of the framework to building this corpus.</p

SensePlace2: GeoTwitter analytics support for situational awareness

Geographically-grounded situational awareness (SA) is critical to crisis management and is essential in many other decision making domains that range from infectious disease monitoring, through regional planning, to political campaigning. Social media are becoming an important information input to support situational assessment (to produce awareness) in all domains. Here, we present a geovisual analytics approach to supporting SA for crisis events using one source of social media, Twitter. Specifically, we focus on leveraging explicit and implicit geographic information for tweets, on developing place-time-theme indexing schemes that support overview+detail methods and that scale analytical capabilities to relatively large tweet volumes, and on providing visual interface methods to enable understanding of place, time, and theme components of evolving situations. Our approach is user-centered, using scenario-based design methods that include formal scenarios to guide design and validate implementation as well as a systematic claims analysis to justify design choices and provide a framework for future testing. The work is informed by a structured survey of practitioners and the end product of Phase-I development is demonstrated / validated through implementation in SensePlace2, a map-based, web application initially focused on tweets but extensible to other media