Kate Beard

Use of Graph Theory to Support Map Generalization

In the generalization of a concept, we seek to preserve the essential characteristics and behavior of objects. In map generalization, the appropriate selection and application of procedures (such as merging, exaggeration, and selection) require information at the geometric, attribute, and topological levels. This article highlights the potential of graph theoretic representations in providing the topological information necessary for the efficient and effective application of specific generalization procedures. Besides ease of algebraic manipulation, the principal benefit of a graph theoretic approach is the ability to detect and thus preserve topological characteristics of map objects such as isolation, adjacency, and connectivity. While it is true that topologically based systems have been developed for consistency checking and error detection during editing, this article emphasizes the benefits from a map-generalization perspective. Examples are given with respect to specific generalization procedures ...

Multidimensional ranking for data in digital spatial libraries

Abstract Digital spatial libraries currently under development are generating large repositories of data which will continue to grow. As these repositories grow, the situation will inevitably arise in which a digital library user may be confronted with several hundred spatial data sets in response to a particular query. The question then arises as to how the results from this search can be most easily assimilated by the user. Text based materials have benefited from substantial research and experience on ranking of search results. Ranking of spatial data sets has not received the same attention since there has been little motivation for such activity until recently. In this paper we propose a multidimensional ranking scheme based on the three dimensions of space, time, and theme. The multidimensional rank is presented graphically to inform users about how well data sets from a digital spatial library meet their spatial, temporal, and thematic targets.

A framework for visualization and exploration of events

The expanding deployment of sensor systems that capture location, time, and multiple thematic variables is increasing the need for exploratory spatio-temporal data analysis tools. Geographic information systems (GIS) and time series analysis tools support exploration of spatial and temporal patterns respectively and independently, but tools for the exploration of both dimensions within a single system are relatively rare. The contribution of this research is a framework for the visualization and exploration of spatial, temporal, and thematic dimensions of sensor-based data. The unit of analysis is an event, a spatio-temporal data type extracted from sensor data. The conceptual framework suggests an approach for design layout that can be flexibly modified to explore spatial and temporal trends, temporal relationships among events, periodic temporal patterns, the timing of irregularly repeating events, event-event relationships in terms of thematic attributes, and event patterns at different spatial and temporal granularities. Flexible assignment of spatial, temporal, and thematic categories to a set of graphical interface elements that can be easily rearranged provides exploratory power as well as a generalizable design layout structure. The framework is illustrated with events extracted from Gulf of Maine Ocean Observing System data but the approach has broad application to other domains and applications in which time, space, and attributes need to be considered in conjunction.

Understanding error in spatial databases

Abstract This paper provides a three-part classification of error that establishes a relationship between sources of error, forms of error and final product error in spatial databases. It aims to inform users of both the types of error that may be inherent in data they acquire for their applications, and errors which may occur as the result of their own actions in managing and analysing data within a Geographic Information System (GIS). The framework for spatial database error presented also helps focus attention on areas where future research is needed to make spatial error more tractable for users.

Zipper: A Localized Approach to Edgematching

There is often an analytical need to combine maps digitized from separately compiled map sheets into a sheetless product. If the maps are strictly compatible, the borders will overlay exactly and features will cross the borders smoothly. Digitized products, particularly those entered manually, fall short of this goal. Due to imperfect geodetic references and other flaws of compilation, many existing maps fail to match their neighbors exactly. These circumstances call for a process we call “zipping”—the ability to merge map sheets so that edges disappear and features cross the boundary smoothly. Advanced overlay software that provides a fuzzy tolerance to remove slivers can be used to perform this process, but the results are not fully satisfactory. This paper introduces an algorithm call Zipper that limits its calculations to the edges of the maps instead of invoking a general-purpose processor. It creates a clean topographical product with minimal manual intervention. This public-domain processor has bee...

High-Level Event Detection in Spatially Distributed Time Series

This paper presents an approach for the detection of high-level events from spatially distributed time series. The objective is to detect spatially evolving high-level events as aggregate patterns of primitive events. The approach starts with a segmentation of time series into primitive events as building blocks for high-level events. A high-level event ontology is then used to specify the composition of high-level events of interest in terms of initiating, body forming, and terminating primitive events. We illustrate the approach first with simulated time series data to identify traffic congestion events and then with real data to identify storm events from sensor time series collected as part of an ocean observing system deployed in the Gulf of Maine. Detected storm events are compared against NCDC reported storm events as an evaluation of the approach.

A semantic web based gazetteer model for VGI

The recent and expanding phenomena of volunteered geographic information (VGI) have potential for building locally rich geographic knowledgebases. Volunteer contributions include a broad range of geographically associated content that has the potential to contribute to collective digital place knowledge, but contributions are scattered over the web with little to no common structure or formal metadata. This paper explores some organizing principles and a potential structure for integrating VGI. Characteristics of VGI suggest organization around features rather than layers, support for multiple representations that capture different contributor perspectives, and integration around the concept of place. A semantic web based gazetteer model that manages features, multiple representations of features, and varying levels of association of features to places is suggested as an integration framework. Semantics of the gazetteer and inference on these semantics provide support for integrating diverse VGI content around hierarchies of officially named places as starting points. Preliminary work illustrates the approach with samples of VGI data from Maine.

Roles of Meta-Information in Uncertainty Management

Meta-information is information that describes information. (1994) defined it as information that makes data useful. The importance of meta-information becomes most apparent in situations where the data user is not the data collector and is not likely to be familiar with the characteristics and idiosyncrasies of the data. As more geospatial information becomes available on-line for use by ecologists, meta-information becomes essential to understand and minimize the uncertainty in using the data. Many ecologists collect their own data, but their analysis may require integration with data collected by other scientists. In a context in which it is becoming ever-more common to share and integrate heterogeneous digital data sets, there are several questions for ecologists: • How effectively can ecologists use other scientists’ data? • How effectively can ecologists integrate their data with other scientists’ data? • How can ecologists better understand the uncertainty in their own data analysis? • How can they communicate the uncertainty in their data and analysis to others? • How can they understand the uncertainty in another scientist’s analysis?

The EventViewer: A tool for visualizing and exploring events extracted from Ocean Observing System data

This paper presents capabilities of the EventViewer, a graphical user interface for visualizing and exploring patterns in events. The EventViewer supports queries on events stored in an events database and exploration of various temporal and spatial patterns in events. Interactions in the EventViewer interface allow users to select events from the database, assign spatial, temporal and thematic categories to graphic display elements called bands, stacks, and panels which causes events to be displayed according to their associations with the user selected categories. The spatial, temporal and thematic categories can be rearranged among the bands, stacks and panels thus changing the view of events and causing different patterns to become apparent. The EventViewer support exploration of periodic patterns, spatial and temporal trends, and event-event relationships. The EventViewer functionality is illustrated with oceanographic events extracted from the Gulf of Maine Ocean Observing system sensor data. Events are extracted from multiple time series variables collected at a number of locations and depths in the Gulf of Maine.

Visual Evaluation of GIS Algorithms Using a Reference Grid

Geographic Information Systems (GIS) algorithms are used to simplify, edge match, and overlay large data sets. Some of these GIS processes can cause considerable positional changes to spatial data which are sometimes difficult to assess. This study presents a visualization technique for the evaluation of GIS algorithms and their positional effects on spatial data. The technique is applicable to vector representations and can be used with any GIS operation that changes vector geometry. The technique employs a uniform reference grid to exploit the visual skills of human operators in the evaluation of positional changes in spatial databases after applying GIS transformations. Changes in grid cell length, area, and shape, along with a set of displacement vectors, can be analyzed to evaluate positional changes in spatial data and to compare the behaviors of different algorithms. The technique can assist GIS users in the documentation of positional changes and in the comparison and selection of algorithms for v...