Earth system science deals with complex systems that pose many significant representation challenges. Ontologies as knowledge repositories have been developed to support the primary goal of sharing knowledge in a manner that aids understanding. DARPA is currently developing an extension to OWL called SWRL (semantic Web rule language), which lets to express some aspects of rules and process behaviors. The semantic Web facilitates researchers' collaboration and model components automated discovery and use. Spatial data plays a key role in modeling the earth system as the input to models and as a measure against which results are validated.
Volunteered Geographic Information (VGI) has emerged as a large, up-to-date, and easily accessible data source. VGI can allow authoritative mapping agencies to undertake continuous improvement of their own data, adding a currency dimension previously unattainable due to high associated costs. VGI also benefits scientific and social research by facilitating quick and low-cost research data capture by the public. VGI, however, through its diversity of authorship, presents a quality assurance risk to the use of this data. This research presents a formulaic model that addresses VGI quality issues, by quantifying trust in VGI. Our 'VGTrust' model assesses information about a data author, and the spatial and temporal trust associated with the data they create, to produce an overall VGTrust rating metric. This metric is both easy to understand and interpret. A facilitated case study, 'Building Our Footprints' is presented which tests the feasibility of VGTrust model in a real-world data capture exercise run by Land Information New Zealand, New Zealand's mapping organisation. By overcoming the trust issues in VGI, this research will allow the integration of VGI and authoritative data and potentially expand the application of VGI, thereby leveraging the power of the crowd for productive and innovative re-use.
Visual exposure modelling establishes the extent to which a nominated feature may be seen from a specified location. The advent of high-resolution light detection and ranging (LiDAR)-sourced elevation models has enabled visual exposure modelling to be applied in urban regions, for example, to calculate the field of view occupied by a landmark building when observed from a nearby street. Currently, visual exposure models access a single surface elevation model to establish the lines of sight (LoSs) between the observer and the landmark feature. This is a cause for concern in vegetated areas where trees are represented as solid protrusions in the surface model totally blocking the LoSs. Additionally, the observer's elevation, as read from the surface model, would be incorrectly set to the tree top height in those regions. The research presented here overcomes these issues by introducing a new visual exposure model, which accesses a bare earth terrain model, to establish the observer's true elevation even when passing through vegetated regions, a surface model for the city profile and an additional vegetation map. Where there is a difference between terrain and surface elevations, the vegetation map is consulted. In vegetated areas the LoS is permitted to continue its journey, either passing under the canopy with clear views or partially through it depending on foliage density, otherwise the LoS is terminated. This approach enables landmark visual exposure to be modelled more realistically, with consideration given to urban trees. The model's improvements are demonstrated through a number of real-world trials and compared to current visual exposure methods.
Advances in technology have created opportunities for collaborative multi-institution programme delivery which are increasingly attractive within a constrained financial environment. This paper details the development of a cross-institution collaboratively delivered masters and postgraduate diploma programme in Geographical Information Science in New Zealand. We explore the benefits of such an approach as well as the lessons learnt from its implementation. The recommendations presented will be of interest to teaching faculty considering specialized collaborative programmes as well as more senior staff who are keen to combine institutional resources to meet new and emerging demands for skills.
Abstract Current approaches to the discovery of scientific resources (publications, data sets and web services) are dominated by keyword search. These approaches do not allow scientists to search on the deeper semantics of scientific resources, or to discover resources on the basis of the scientific approaches taken. This article evaluates a user interface that allows users to discover scientific resources through structured knowledge in the form of ontologies describing the domain and the scientific knowledge inherent within the scientific resource, and also through informal user tags. These combined capabilities provide scientists with new and powerful options for resource discovery. A qualitative user evaluation explored how scientists felt about the approach for resource discovery in the context of their scientific work. The study showed that marine scientists were enthusiastic about the capabilities of such an approach and appreciated the ability to browse the visual structure of the knowledge and query on scientific method but, overall, preferred the use of tags over ontologies. The exploratory nature of the user study was used to identify future directions for such improvements.
Abstract Ontology‐based information publishing, retrieval, reuse, and integration have become popular research topics to address the challenges involved in exchanging data between heterogeneous sources. However, in most cases ontologies are still developed in a centralized top‐down manner by a few knowledge engineers. Consequently, the role that developers play in conceptualizing a domain such as the geosciences is disproportional compared with the role of domain experts and especially potential end‐users. These and other drawbacks have stimulated the creation of new methodologies focusing around collaboration. Based on a review of existing approaches, this article presents a two‐step methodology and implementation to foster collaborative ontology engineering in the geosciences. Our approach consists of the development of a minimalistic core ontology acting as a catalyst and the creation of a virtual collaborative development cycle. Both methodology and prototypical implementation have been tested in the context of the EU ‐funded ForeStClim project which addresses environmental protection with respect to forests and climate change.
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