Isaac Brewer

Bio: Isaac Brewer is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Geospatial analysis & Crisis management. The author has an hindex of 13, co-authored 19 publications receiving 1192 citations.

Geovisualization for knowledge construction and decision support

Abstract: Geovisualization is both a process for leveraging the data resources to meet scientific and societal needs and a research field that develops visual methods and tools to support a wide array of geospatial data applications. While researchers have made substantial advances in geovisualization over the past decade, many challenges remain. To support real-world knowledge construction and decision making, some of the most important challenges involve distributed geovisualization - that is, enabling geovisualization across software components, devices, people, and places.

Developing a conceptual framework for visually-enabled geocollaboration

Abstract: Most work with geospatial data, whether for scientific analysis, urban and environmental planning, or business decision making is carried out by groups. In contrast, geographic information technologies have been built and assessed only for use by individuals. In this paper we argue that, to support collaboration with geospatial information, specific attention must be given to tools that mediate understanding and support negotiation among participants. In addition, we contend that visual representations have a particularly important role to play as mediators of geocollaborative activities. With these contentions as a starting point, we present a framework for study of visually-enabled collaboration with geospatial information and for development, implementation, and assessment of geoinformation technologies that support that collaboration. The paper concludes with a brief description of two prototype geocollaborative environments that illustrate the use of the framework developed and provide the basis for ...

Designing a human-centered, multimodal GIS interface to support emergency management

Abstract: Geospatial information is critical to effective, collaborative decision-making during emergency management situations; however conventional GIS are not suited for multi-user access and high-level abstract queries. Currently, decision makers do not always have the real time information they need; GIS analysts produce maps at the request of individual decision makers, often leading to overlapping requests with slow delivery times. In order to overcome these limitations, a paradigm shift in interface design for GIS is needed. The research reported upon here attempts to overcome analyst-driven, menu-controlled, keyboard and mouse operated GIS by designing a multimodal, multi-user GIS interface that puts geospatial data directly in the hands of decision makers. A large screen display is used for data visualization, and collaborative, multi-user interactions in emergency management are supported through voice and gesture recognition. Speech and gesture recognition is coupled with a knowledge-based dialogue management system for storing and retrieving geospatial data. This paper describes the first prototype and the insights gained for human-centered multimodal GIS interface design.

Speech-gesture driven multimodal interfaces for crisis management

Abstract: Emergency response requires strategic assessment of risks, decisions, and communications that are time critical while requiring teams of individuals to have fast access to large volumes of complex information and technologies that enable tightly coordinated work. The access to this information by crisis management teams in emergency operations centers can be facilitated through various human-computer interfaces. Unfortunately, these interfaces are hard to use, require extensive training, and often impede rather than support teamwork. Dialogue-enabled devices, based on natural, multimodal interfaces, have the potential of making a variety of information technology tools accessible during crisis management. This paper establishes the importance of multimodal interfaces in various aspects of crisis management and explores many issues in realizing successful speech-gesture driven, dialogue-enabled interfaces for crisis management. This paper is organized in five parts. The first part discusses the needs of crisis management that can be potentially met by the development of appropriate interfaces. The second part discusses the issues related to the design and development of multimodal interfaces in the context of crisis management. The third part discusses the state of the art in both the theories and practices involving these human-computer interfaces. In particular, it describes the evolution and implementation details of two representative systems, Crisis Management (XISM) and Dialog Assisted Visual Environment for Geoinformation (DAVE/spl I.bar/G). The fourth part speculates on the short-term and long-term research directions that will help addressing the outstanding challenges in interfaces that support dialogue and collaboration. Finally, the fifth part concludes the paper.

Enabling collaborative geoinformation access and decision‐making through a natural, multimodal interface

Abstract: Current computing systems do not support human work effectively. They restrict human–computer interaction to one mode at a time and are designed with an assumption that use will be by individuals (rather than groups), directing (rather than interacting with) the system. To support the ways in which humans work and interact, a new paradigm for computing is required that is multimodal, rather than unimodal, collaborative, rather than personal, and dialogue‐enabled, rather than unidirectional. To address this challenge, we have developed an approach for designing natural, multimodal, multiuser dialogue‐enabled interfaces to geographic information systems that make use of large‐screen displays and integrated speech–gesture interaction. After outlining our goals and providing a brief overview of relevant literature, we introduce the Dialogue‐Assisted Visual Environment for Geoinformation (DAVE_G). DAVE_G is being developed using a human‐centred systems approach that contextualizes development and assessment in...

Architecture for controlling a computer using hand gestures

Abstract: Architecture for implementing a perceptual user interface. The architecture comprises alternative modalities for controlling computer application programs and manipulating on-screen objects through hand gestures or a combination of hand gestures and verbal commands. The perceptual user interface system includes a tracking component that detects object characteristics of at least one of a plurality of objects within a scene, and tracks the respective object. Detection of object characteristics is based at least in part upon image comparison of a plurality of images relative to a course mapping of the images. A seeding component iteratively seeds the tracking component with object hypotheses based upon the presence of the object characteristics and the image comparison. A filtering component selectively removes the tracked object from the object hypotheses and/or at least one object hypothesis from the set of object hypotheses based upon predetermined removal criteria.

Mastering the information age : solving problems with visual analytics

Abstract: Data Nodes, Edges Display Interactive Display Visual Analogues VisualItems in ItemRegistry User Figure 6.3: The Information Visualisation Reference Model, adapted from Heer et al.[57] 6.2 State of the Art 93 a visual analytics issue that should be better tackled by all the visualisation communities. Blending different kinds of visualisations in the same application is becoming Blending different kinds of visualisations is currently difficult more frequent. Scientific visualisation and geographic visualisation need information visualisation because they manage multi-valued data with complex topologies that can be visualised using their canonical geometry. In addition, they can also be explored with more abstract visual representations to avoid geometric artefacts. For example, census data can be visualised as a coloured map but also as a multi-dimensional dataset where the longitude and latitude are two attributes among others. Clustering this data by some similarity measure will then reveal places that can be far away in space but behave similarly in term of other attributes (e.g., level of education, level of income, size of houses etc.), similarity that would not be visible on a map. On top of these visualisation systems, a user interface allows control of the overall application. User interfaces are well understood but they can be very different in styles. 3D systems use specific types of interfaces that are very different to traditional desktop interfaces. Moreover, information visualisation systems tend to deeply embed the interaction with the visualisation, offering special kinds of controls either directly inside the visualisations (e.g., range sliders on the axes of parallel coordinates) or around it but with special kinds of widgets (e.g., range sliders for performing range-queries). Interoperability can thus be described at several levels. At the data management level, at the architecture model level and at the interface level. 6.2.2 Data Management All visual analytics applications start with data that can be either statically collected or dynamically produced. Depending on the nature of the data, visual analytics applications have used various ways of managing their storage. In order of sophistication, they are: Flat files using ad-hoc formats, Structured file formats such as XML, Specialised NoSQL systems, including Cloud Storage, Standard or extended transactional databases (SQL), Workflow or dataflow systems integrating storage, distribution and data processing. We will now consider these data storage methods, paying particular attention to Data Management for visual analytics can rely on different levels of sophistication the levels of service required by visual analytics, such as: Persistence (they all provide it by definition), Typing, Distribution, Atomic transactions, Notification, Interactive performance, Computation.

Vision-based hand-gesture applications

Abstract: Body posture and finger pointing are a natural modality for human-machine interaction, but first the system must know what it's seeing.

Understanding Risk - Informing Decisions in a Democratic Society

Abstract: This is the advice of a committee of leading American experts, chaired by Harvey Fineberg from the Harvard School of Public Health. It represents the fifth report in a series, commissioned by the US National Research Council, that considers how society can understand and cope with decisions about risks. The Committee's remit was to provide advice on risk characterisation, defined by the Research Council as the translation of `the information in a risk assessment ... into a form usable by a risk manager, individual decision maker, or the public'. In this book, the Committee has responded to the challenge clearly and authoritatively, beginning with a profound re-definition of `risk characterisation' that forms the basis for all that follows. In the view of the Committee, risk characterisation is a process. It is a process which starts before quantitative analysis of the risks, because it includes defining what risks to assess, and how most appropriately to assess them. It is an iterative process, in which assumptions are challenged and re-worked, and new information may be incorporated. It is a process in which qualitative judgements contribute to the fuller understanding of the problem; where quantitative scientific estimates, although important, contribute only a part. Most fundamentally, it is a process which, in a democratic society, needs to involve all those affected by the perceived problem and consequent decision. In the words of the Committee: `Experience shows that analyses, no matter how thorough, that do not address the decision-relevant questions, use reasonable assumptions, and meaningfully include the key affected parties can result in huge expenses and long delays and jeopardise the quality of understanding and the acceptability of the final decisions.' In other words, until or unless we expand our understanding of risk characterisation to include the process of defining the assessment itself, we are unlikely to make progress in gaining public acceptance for major decisions on health or environmental issues. For those without sufficient time to read the book, the ten-page summary provides a succinct overview of the Committee's advice, complete with bullet points and emboldened key phrases. However, the main body of the book (and particularly Appendix A, which discusses a number of case studies) is well worth scanning for its well-reasoned and well-structured discussion of the issues and the suggested way forward. Nor is the Committee lost in an `academic ivory tower'. It recognises that involvement of all those with vested interests cannot ensure a rapid or consensus solution or preclude some groups `dropping out' and choosing the route of litigation. It also recognises that allowing a `voice' for a wide range of interest groups can be time consuming and difficult to manage. However, the Committee argues: `While we are sensitive to concerns about cost and delay, we note that huge costs and delays have sometimes resulted when a risk situation was inadequately diagnosed, a problem misformulated, key interested and affected parties did not participate, or analysis proceeded unintegrated with deliberation. We believe that following [our] principles can reduce delays and costs as much as or more than it increases them.' So what are the Committee's principles? Getting the science right - any quantitative science that is undertaken must be of the highest standards. Getting the right science - this ensures that all the relevant risks are considered. Getting the right participation - this ensures that all those affected have a `voice' in the process. Getting the participation right - this ensures that the process is responsive to the needs of all the participants. Developing an accurate, balanced and informative synthesis - this should include a balanced understanding of the uncertainties in current knowledge, encompassing ignorance and indeterminacy as well as more quantifiable uncertainties. Again, in the words of the Committee: `These criteria are related. To be decision-relevant, risk characterisation must be accurate, balanced and informative. This requires getting the science right and getting the right science. Participation helps ask the right questions of the science, check the plausibility of assumptions, and ensure that any synthesis is both balanced and informative.' In order to set up an appropriate risk characterisation process, the Committee recommends that those responsible for it should `begin by developing a provisional diagnosis of the decision situation' in order to identify potential participants, allocate resources and structure the process. However, in doing so, they should `treat the diagnosis as tentative and remain open to change, always keeping in mind that their goal is a process that leads to a useful and credible risk characterization'. The Committee also stresses the need for those responsible for the process to `develop the capability to cope with attempts by some interested and affected parties to delay decision, and to develop a range of strategies for reaching closure'. This is likely to require the development of new skills and may require organisational changes `to improve communication across sub-units and to allow for the flexibility and judgement necessary to match the process to decision'. This balanced, reasoned and authoritative book is, in my opinion, a `must for all those involved in informing societal decision on risks.