1,011 research outputs found
A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web
Over the past decade, rapid advances in web technologies, coupled with
innovative models of spatial data collection and consumption, have generated a
robust growth in geo-referenced information, resulting in spatial information
overload. Increasing 'geographic intelligence' in traditional text-based
information retrieval has become a prominent approach to respond to this issue
and to fulfill users' spatial information needs. Numerous efforts in the
Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the
Linking Open Data initiative have converged in a constellation of open
knowledge bases, freely available online. In this article, we survey these open
knowledge bases, focusing on their geospatial dimension. Particular attention
is devoted to the crucial issue of the quality of geo-knowledge bases, as well
as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic
Network, is outlined as our contribution to this area. Research directions in
information integration and Geographic Information Retrieval (GIR) are then
reviewed, with a critical discussion of their current limitations and future
prospects
Managing contextual information in semantically-driven temporal information systems
Context-aware (CA) systems have demonstrated the provision of a robust solution for personalized information delivery in the current content-rich and dynamic information age we live in. They allow software agents to autonomously interact with users by modeling the userâs environment (e.g. profile, location, relevant public information etc.) as dynamically-evolving and interoperable contexts. There is a flurry of research activities in a wide spectrum at context-aware research areas such as managing the userâs profile, context acquisition from external environments, context storage, context representation and interpretation, context service delivery and matching of context attributes to usersâ queries etc. We propose SDCAS, a Semantic-Driven Context Aware System that facilitates public services recommendation to users at temporal location. This paper focuses on information management and service recommendation using semantic technologies, taking into account the challenges of relationship complexity in temporal and contextual information
Dwelling on ontology - semantic reasoning over topographic maps
The thesis builds upon the hypothesis that the spatial arrangement of topographic
features, such as buildings, roads and other land cover parcels, indicates how land is
used. The aim is to make this kind of high-level semantic information explicit within
topographic data. There is an increasing need to share and use data for a wider range of
purposes, and to make data more definitive, intelligent and accessible. Unfortunately,
we still encounter a gap between low-level data representations and high-level concepts
that typify human qualitative spatial reasoning. The thesis adopts an ontological
approach to bridge this gap and to derive functional information by using standard
reasoning mechanisms offered by logic-based knowledge representation formalisms. It
formulates a framework for the processes involved in interpreting land use information
from topographic maps. Land use is a high-level abstract concept, but it is also an
observable fact intimately tied to geography. By decomposing this relationship, the
thesis correlates a one-to-one mapping between high-level conceptualisations
established from human knowledge and real world entities represented in the data.
Based on a middle-out approach, it develops a conceptual model that incrementally
links different levels of detail, and thereby derives coarser, more meaningful
descriptions from more detailed ones. The thesis verifies its proposed ideas by
implementing an ontology describing the land use âresidential areaâ in the ontology
editor Protégé. By asserting knowledge about high-level concepts such as types of
dwellings, urban blocks and residential districts as well as individuals that link directly
to topographic features stored in the database, the reasoner successfully infers instances
of the defined classes. Despite current technological limitations, ontologies are a
promising way forward in the manner we handle and integrate geographic data,
especially with respect to how humans conceptualise geographic space
Recommended from our members
The National Transport Data Framework
Report by Professor Peter Landshoff (Cambridge University) and
Professor John Polak (Imperial College London) on a project for
the Department for Transport.
emails: [email protected] [email protected] NTDF is designed to be a resource for data owners to deposit descriptions
into a central catalogue, so that people can search for data and find data
and understand their characteristics. The value of this is to individuals, to
commercial organizations, and to public bodies. For example, services that
provide better information to travellers will help to make their journey
less stressful and persuade them to make more use of public transport.
Transport operators need very diverse information to help them
plan developments to their services: demographic, geographical, economic etc.
And policy makers need a similar range of information to help them decide
how to divide their budget and afterwards to evaluate how valuable it has
been.This work was supported by the Department for Transport (DfT)
Conservation GIS: Ontology and spatial reasoning for commonsense knowledge.
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.Geographic information available from multiple sources are moving beyond their local
context and widening the semantic difference. The major challenge emerged with ubiquity of
geographic information, evolving geospatial technology and location-aware service is to deal
with the semantic interoperability. Although the use of ontology aims at capturing shared
conceptualization of geospatial information, human perception of world view is not
adequately addressed in geospatial ontology. This study proposes âConservation GIS
Ontologyâ that comprises spatial knowledge of non-expert conservationists in the context of
Chitwan National Park, Nepal.
The discussion is presented in four parts: exploration of commonsense spatial knowledge
about conservation; development of conceptual ontology to conceptualize domain
knowledge; formal representation of conceptualization in Web Ontology Language (OWL);
and quality assessment of the ontology development tasks. Elicitation of commonsense
spatial knowledge is performed with the notion of cognitive view of semantic. Emphasis is
given to investigate the observation of wildlife movement and habitat change scenarios.
Conceptualization is carried out by providing the foundation of the top-level ontology-
âDOLCEâ and geospatial ontologies. ProtĂ©gĂ© 4.1 ontology editor is employed for ontology
engineering tasks. Quality assessment is accomplished based on the intrinsic approach of
ontology evaluation.(...
Assessing the quality of geospatial linked data â experiences from Ordnance Survey Ireland (OSi)
Ordnance Survey Ireland (OSi) is Irelandâs national mapping agency
that is responsible for the digitisation of the islandâs infrastructure in terms of
mapping. Generating data from various sensors (e.g. spatial sensors), OSi build
its knowledge in the Prime2 framework, a subset of which is transformed into
geo-Linked Data. In this paper we discuss how the quality of the generated
sematic data fares against datasets in the LOD cloud. We set up Luzzu, a scalable
Linked Data quality assessment framework, in the OSi pipeline to continuously
assess produced data in order to tackle any quality problems prior to publishing
Interacting with ontologies and linked data through controlled natural languages and dialogues
This paper describes a suite of tools developed at the University of Leeds which aim to make it easier for domain experts to be involved in the creation and use of ontologies. The paper summarises the main features of the tools and gives a short summary of our evaluations and experiences using the tools with domain experts
- âŠ