To Ontologise or Not to Ontologise: An Information Model for a Geospatial Knowledge Infrastructure

Computers & GeosciencesComputers & Geosciences, Volume 45, August 2012, Pages 98–108

Kristin Stock, Tim Stojanovic, Femke Reitsma, Yang Ou, Mohamed Bishr, Jens Ortmann, and Anne Robertson

“A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created.

“This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge.

The COMPASS user interface.

The COMPASS user interface.

“The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.”

Using GIScience Methods to Establish Spatial Information for Prehispanic Sites in the Malpaso Valley, Zacatecas, Mexico

Masters thesis, Texas State University-San Marcos, August 2012

Ryan Thomas Schuermann

“This research uses Geographical Information Science methods to establish spatial information pertaining to archaeological sites within the middle Malpaso Valley, Zacatecas, Mexico. Analysis of residual and Root Mean Square Error of geo-rectification produces both localized and overall geodetic accuracy assessments of a historic 1974 survey map. Ground control points acquired using Global Positioning System provide a basis for establishing confidence in the geo-rectified map. This research is a technological continuation of previous work in the Malpaso Valley, and aims to produce a useful map for spatial analysis and data management in future research.”

Example of ASL ambiguity between warped map and GPS recordings

Example of ASL ambiguity between warped map and
GPS recordings

Detection and Spatial Analysis of Selective Logging with Geometrically Corrected Landsat Images

International Journal of Remote SensingInternational Journal of Remote Sensing, Volume 33, Issue 24, 2012

Salma Anwar and Alfred Stein

“The Brazilian Amazonian rain forests are under imminent threat of serious degradation and ultimately deforestation. Human activities such as selective logging are an important cause. Selectively logged locations are difficult to detect from medium-resolution Landsat images, due to their relatively small sizes and subtle spatial patterns. Spectral linear unmixing provides an effective tool for the purpose. The orientation of geometrically corrected images, however, artificially introduces zero-reflectance background pixels. These change the variance–covariance structure of the image bands and hinder the identification of pure endmembers. In this study, we compare image cropping and image rotation as two alternative approaches. Selectively logged forests were detected in northern Rondônia state, north-western Mato Grosso state and south-eastern Amazonas state in Brazil by applying spectral unmixing. The study shows that image rotation is a better approach as it preserves the image extent and thus provides information on forest degradation over a wider region. Spatial statistical analysis of the detected locations shows strong clustering within the study area. We conclude that the endmembers used in this study represent basic components of a degraded forest environment. As spectral unmixing of remote-sensing images avoids collection of field data, it may broadly be applied towards other Amazonian regions as well.”

URISA Announces GIS Management Initiative

URISAURISA has announced an important new initiative to develop a GIS Management Institute.  Greg Babinski, URISA President, made the announcement during a presentation at the 2012 Esri User Conference in San Diego.  The GIS Management Institute (GMI) will develop resources and services that focus on promoting the advancement of professional best practices and standards for the management of GIS operations.

The GIS Management Institute will build upon resources that URISA has already developed, including the GIS Capability Maturity Model, the Geospatial Management Competency Model, the Exemplary Systems in Government (ESIG) Awards, the URISA Leadership Academy, and others.  A key component of the GIS Management Institute will be the development of the GIS Management Body of Knowledge (GMBOK).

The GIS Management Body of Knowledge will be the central unifying element of the Institute.  It will be used to refine the GIS Capability Maturity Model (GISCMM) and the Geospatial Management Competency Model (GMCM).  The GMBOK will be a collection of peer-reviewed best practices and standards that can inform geospatial managers and operations in order to improve the effectiveness of their use of geospatial technology.

The GMI will develop programs based on the GMBOK to accredit the capability and maturity of GIS operations against the GISCMM.  It will also develop a program to accredit GIS management educational programs against the GMBOK and GMCM.  URISA has agreed to work in cooperation with the GIS Certification Institute (GISCI) to advance the future certification of GIS managers.

Mr. Babinski explained the motivation behind the development of the GIS Management Institute: “The management of enterprise GIS operations requires knowledge, skills, and abilities that clearly set it apart from other management domains.  GIS operations today are highly complex, critical for effective agency services, and have been proven to deliver tremendous financial benefits.” He further noted that, “Central to the GMI, is the theory that as GIS operational maturity improves, ROI (return on investment) from GIS increases.”

The GIS Management Institute will be a program managed by URISA.  URISA has nearly 50 years of study, experience, and intellectual capital related to GIS management.  URISA developed and launched GISCI.  URISA developed and manages GISCorps, the ESIG awards, the URISA Leadership Academy, and a portfolio of 20 URISA workshops.

[Source: URISA press release]