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

KBGIS-2: A knowledge-based geographic information system

The architecture and working of a recently implemented knowledge-based geographic information system (KBGIS-2) that was designed to satisfy several general criteria for the geographic information system are described. The system has four major functions that include query-answering, learning, and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial objects language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is currently performing all its designated tasks successfully, although currently implemented on inadequate hardware. Future reports will detail the performance characteristics of the system, and various new extensions are planned in order to enhance the power of KBGIS-2

Beyond the Knowledge-Based Theory of the Geographic Cluster

The knowledge-based theory of the geographic cluster represents a major attempt to re-conceptualize clusters, in essence arguing that the localization of firms in similar and related industries stimulates learning and innovation, giving a competitive advantage to clustered firms. This paper critically examines the knowledge-based theory the cluster, arguing that it has greatly overstated the advantages of co-location to firms and misidentified the mechanisms through which learning occurs in clusters. In particular, the theory is criticized on three points: the flexible, under-specified way that it defines its object of study; the focus on firms as an explanatory variable instead of more fundamental processes of resource accumulation; and the functionalist mode of theory that employs as an explanation. Ways to address of each of these issues are discussed. In a final section I suggest that the rather static notions of learning put forward in the knowledge-based theory of the cluster be replaced by a developmental theory of regional dynamics that focuses on both learning and structural transformation.geographic cluster, localization, relatedness, knowledge-based theory

Production of Knowledge and Geographically Mediated Spillovers from Universities: Spatial Econometric Perspective and Evidence from Austria

The paper sheds some light on the issue of geographically mediated knowledge spillovers from university research activities to regional knowledge production in the high tech sector in Austria. Knowledge spillovers occur because knowledge created by university is typically not contained within that institution, and thereby creates value for others. The conceptual framework for analysing geographic spillovers of university research on regional knowledge production is derived from Griliches (1979). It is assumed that knowledge production in the high tech sector essentially depends on two major sources of knowledge: the university research that represents the potential pool of knowledge spillovers and R&D performed by the high tech sector itself. Knowledge is measured in terms of patents, university research and R&D in terms of expenditures. We refine the standard %0D knowledge production function by modelling research spillovers as a spatially discounted external stock of knowledge. This enables us to capture local and interlocal spillovers. Using district-level data and employing spatial econometric tools evidence is found of university research spillovers that transcend the geographic scale of the political district in Austria. It is shown that geographic boundedness of the spillovers is linked to a decay effect. Reference Griliches Z. (1979): Issues in Assessing the Contribution of Research and Development to Productivity Growth, Bell Journal of Economics 10, 92-116

Leveraging Knowledge Across Geographic Boundaries

This paper examines knowledge flows within and across geographic boundaries of clusters and nations in the biotechnology industry. We hypothesize that these flows are characterized by various factors relating to the knowledge itself and by firm innovativeness and the presence of prior knowledge flows at the firm level. Surprisingly, our findings suggest that geographic proximity does not matter in some instances, while in others it has a decidedly nonlinear effect opposite to that hypothesized. The pattern of findings points to the greatest contrast in the comparison of between-cluster and between-country flows and presents an opportunity to reevaluate the role of geography and knowledge flows

Communities, Knowledge, and Innovation: Indian Immigrants in the US Semiconductor Industry

This paper investigates the influence of technological, geographic, and ethnic communities on the innovativeness of Indian inventors. We study Indian inventors in the semiconductor industry in the US and examine their patenting profiles between 1975 and 1999 to identify the influences on the quantity and quality of their innovations. We find that inventors who rely on knowledge from technological and geographic communities enhance their innovativeness. Knowledge from the ethnic Indian community is related to inventor innovativeness in the form of an inverted U. The negative effect of knowledge gained from the ethnic community on innovativeness is pronounced for experienced inventors.innovation, knowledge, semiconductor industry

GeoCLEF 2006: the CLEF 2006 Ccross-language geographic information retrieval track overview

After being a pilot track in 2005, GeoCLEF advanced to be a regular track within CLEF 2006. The purpose of GeoCLEF is to test and evaluate cross-language geographic information retrieval (GIR): retrieval for topics with a geographic specification. For GeoCLEF 2006, twenty-five search topics were defined by the organizing groups for searching English, German, Portuguese and Spanish document collections. Topics were translated into English, German, Portuguese, Spanish and Japanese. Several topics in 2006 were significantly more geographically challenging than in 2005. Seventeen groups submitted 149 runs (up from eleven groups and 117 runs in GeoCLEF 2005). The groups used a variety of approaches, including geographic bounding boxes, named entity extraction and external knowledge bases (geographic thesauri and ontologies and gazetteers)

SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting

Learning knowledge graph (KG) embeddings is an emerging technique for a variety of downstream tasks such as summarization, link prediction, information retrieval, and question answering. However, most existing KG embedding models neglect space and, therefore, do not perform well when applied to (geo)spatial data and tasks. For those models that consider space, most of them primarily rely on some notions of distance. These models suffer from higher computational complexity during training while still losing information beyond the relative distance between entities. In this work, we propose a location-aware KG embedding model called SE-KGE. It directly encodes spatial information such as point coordinates or bounding boxes of geographic entities into the KG embedding space. The resulting model is capable of handling different types of spatial reasoning. We also construct a geographic knowledge graph as well as a set of geographic query-answer pairs called DBGeo to evaluate the performance of SE-KGE in comparison to multiple baselines. Evaluation results show that SE-KGE outperforms these baselines on the DBGeo dataset for geographic logic query answering task. This demonstrates the effectiveness of our spatially-explicit model and the importance of considering the scale of different geographic entities. Finally, we introduce a novel downstream task called spatial semantic lifting which links an arbitrary location in the study area to entities in the KG via some relations. Evaluation on DBGeo shows that our model outperforms the baseline by a substantial margin.Comment: Accepted to Transactions in GI

Teaching Geographic Visualisation: Evaluating student understandings of visualising geographic knowledge

The project set out to “evaluate students’ understanding of visualisation techniques and the usefulness of different teaching approaches to help students understand the complex issues involved in visual representation.” In summary, this report covers the first two of the following three aims: 1 – to evaluate students’ understanding of visualisation techniques 2 – to evaluate the usefulness of different teaching approaches 3 – to assess the construction of assessment criteria for the visualisation assignment To achieve the objectives, Peanut were commissioned to evaluate “the delivery of a visualisation assignment on a second year undergraduate module about globalisation”, using participatory techniques and approaches