A semantic and language-based representation of an environmental scene

The modeling of a landscape environment is a cognitive activity that requires appropriate spatial representations. The research presented in this paper introduces a structural and semantic categorization of a landscape view based on panoramic photographs that act as a substitute of a given natural environment. Verbal descriptions of a landscape scene provide themodeling input of our approach. This structure-based model identifies the spatial, relational, and semantic constructs that emerge from these descriptions. Concepts in the environment are qualified according to a semantic classification, their proximity and direction to the observer, and the spatial relations that qualify them. The resulting model is represented in a way that constitutes a modeling support for the study of environmental scenes, and a contribution for further research oriented to the mapping of a verbal description onto a geographical information system-based representation

Getting Into Networks and Clusters: Evidence on the GNSS composite knowledge process in (and from) Midi-Pyrénées

This paper aims to contribute to the empirical identification of clusters by proposing methodological issues based on network analysis. We start with the detection of a composite knowledge process rather than a territorial one stricto sensu. Such a consideration allows us to avoid the overestimation of the role played by geographical proximity between agents, and grasp its ambivalence in knowledge relations. Networks and clusters correspond to the complex aggregation process of bi or n-lateral relations in which agents can play heterogeneous structural roles. Their empirical reconstitution requires thus to gather located relational data, whereas their structural properties analysis requires to compute a set of indexes developed in the field of the social network analysis. Our theoretical considerations are tested in the technological field of GNSS (Global Satellite Navigation Systems). We propose a sample of knowledge relations based on collaborative R&D projects and discuss how this sample is shaped and why we can assume its representativeness. The network we obtain allows us to show how the composite knowledge process gives rise to a structure with a peculiar combination of local and distant relations. Descriptive statistics and structural properties show the influence or the centrality of certain agents in the aggregate structure, and permit to discuss the complementarities between their heterogeneous knowledge profiles. Quantitative results are completed and confirmed by an interpretative discussion based on a run of semi-structured interviews. Concluding remarks provide theoretical feedbacks.Knowledge, Networks, Economic Geography, Cluster, GNSS

The Spatial Evolution of Innovation Networks: A Proximity Perspective

We propose an evolutionary perspective on the geography of network formation that is grounded in a dynamic proximity framework. In doing so, we root the proximity concept in an evolutionary approach to the geography of innovation networks. We discuss three topics. The first topic focuses on explaining the structure of networks. The second topic concentrates on explaining the effects of networks on the performance of actors. The third topic deals with the changing role of proximity dimensions in the formation and performance of innovation networks in the longer run.evolutionary economic geography, knowledge networks, innovation networks, dynamic proximity

Regional Learning Networks in Medium-Tech Technologies and European Integration

The paper aims at investigating the transfer of tacit knowledge both at the regional and at the interregional level and it focuses on the factors and forms of the processes of interactive learning between small and medium size in medium technology sectors. The analysis proceeds from the contributions of four strands of literature, focusing on economics of agglomeration, cognitive economics, industrial strategic alliances and governance in a knowledge economy. While industrial economics interprets technology spill-over at the local level as an automatic and chaotic process allowed by geographical proximity of the firms, regional economics identifies different specific types of flows and networks, which link together in an organized way the various firms and other private and public actors within a given regional innovation system. Cognitive economics may bring a significant contribution, as it considers the relevance for economics of human cognitive aspects and it discovers the key role in the creation of new ideas of selected factors, such as the stimulus by changes in the external environment, the process of “neurognosis†or negative reaction aiming to the protection of the internal integrity, the search process constrained by cognitive proximity, the success in pattern making and the achievement of consistency and compatability, the process of “exaptation†or reconversion leading to path-dependency, the creation of new connections and routines and institutions, which allows to save the limited cognitive capacity of individuals and organizations. This theoretical framework in the analysis of the processes of knowledge creation may be schematically represented through the model of “Territorial Knowledge Managementâ€, which aims at promoting the interactive learning processes within the regional innovation systems and focuses on a selected list of knowledge levers, such as: market orientation, accessibility, receptiveness, common identity, creativity and governance. On the base of these theoretical concepts and tools, the paper analyses various case studies of firms embedded in different industrial clusters in Europe, focusing on the forms of the process of interactive learning and innovation between the various regional actors. Finally, the paper attempts to derive from that analysis useful indications for the possible extension of knowledge and innovation networks at the interregional and international level and for decreasing the regional divide in a modern knowledge economy. The research has been undertaken within the framework of the project: “IKINET – International Knowledge and Innovation Network†(EU FP6, N° CIT2-CT-2004-506242). Keywords: knowledge creation, interactive learning processes, industrial clusters, innovation policies, European integration, medium technology sectors, small and medium size firms.

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

A Visibility and Spatial Constraint-Based Approach for Geopositioning

Over the past decade, automated systems dedicated to geopositioning have been the object of considerable development. Despite the success of these systems for many applications, they cannot be directly applied to qualitative descriptions of space. The research presented in this paper introduces a visibility and constraintbased approach whose objective is to locate an observer from the verbal description of his/her surroundings. The geopositioning process is formally supported by a constraint-satisfaction algorithm. Preliminary experiments are applied to the description of environmental scenes

A Visibility and Spatial Constraint-Based Approach for Geopositioning

Over the past decade, automated systems dedicated to geopositioning have been the object of considerable development. Despite the success of these systems for many applications, they cannot be directly applied to qualitative descriptions of space. The research presented in this paper introduces a visibility and constraintbased approach whose objective is to locate an observer from the verbal description of his/her surroundings. The geopositioning process is formally supported by a constraint-satisfaction algorithm. Preliminary experiments are applied to the description of environmental scenes

The Ambivalent Role of Mimetic Behaviors in Proximity Dynamics: Evidences on the French “Silicon Sentier”

This articles examines the peculiar role of mimetic behaviors in co-location processes. We start showing that geographical proximity between agents and/or firms is not a sufficient nor necessary condition for the collective performance of clusters. Other types of socio-economic proximities characterize clusters, and our purpose is to show that, among the several ways to analyze the complex links between proximities and clusters, the theoretical outlook on the role played by mimetic interactions in co-location processes are certainly one of the most promising. Mimetic behaviors of location (in economics and sociology) are introduced in order to demonstrate that co-location processes can be the result of sequentiality, uncertainty, legitimacy and non market interactions, rather than full rational and isolated decisions and pure strategic market interactions. According to the type of mimetic behavior at work in the clustering process, the nature of socio-economic proximity can differ and have a strong influence of the “evolutionary stability” of clusters. All these theoretical considerations are illustrated through the emblematic French case of “Silicon Sentier”, cluster which has gathered together three hundred firms of the French net-economy (the famous “dotcom”) during the Internet bubble swelling.cluster, mimetic interactions, proximity, stability, Silicon Sentier

Location-based and contextual mobile learning. A STELLAR Small-Scale Study

This study starts from several inputs that the partners have collected from previous and current running research projects and a workshop organised at the STELLAR Alpine Rendevous 2010. In the study, several steps have been taken, firstly a literature review and analysis of existing systems; secondly, mobile learning experts have been involved in a concept mapping study to identify the main challenges that can be solved via mobile learning; and thirdly, an identification of educational patterns based on these examples has been done. Out of this study the partners aim to develop an educational framework for contextual learning as a unifying approach in the field. Therefore one of our central research questions is: how can we investigate, theorise, model and support contextual learning