Increasing Access to and Use of Geospatial Data by Municipal Government and Citizens: The Process of "Geomatization" in Rural Quebec
Notice bibliographique
Résumé
INTRODUCTION There is a strong history of the application of geographic information systems (GIS) at the local level within government (Budic 1994, Goelman 2005, Harris 1965) and community organizations (Carver, Evans, Kingston, and Turton 2000; Drummond and French 2008; Ghose 2001; Sieber 2000). Many of the tasks of municipal planning, such as land-use management, zoning, location analysis, and impact assessment, can be supported through the use of GIS and geospatial data more broadly. Despite the potential value of GIS and geospatial data, the adoption of this technology at the municipal and community levels can face many challenges, including organizational, fit-to-task, technical, and user-interface constraints (Budic 1999; Onsrud and Pinto 1991; Vonk, Geertman, and Schot 2005). Recent developments in online mapping software have produced a range of alternate approaches that can be used to provide for the GIS-like communication and visualization of geospatial data that may be more suited to local government and community organizations compared to conventional desktop GIS (Dragicevic and Balram 2004; Goelman 2005; Johnson and Sieber 2011a; Rouse, Bergeron, and Harris 2007). The Geospatial Web 2.0 (Geoweb) is an online collection of frameworks and services that can be used to gather, display, analyze, and share geospatial data (Scharl and Tochterman 2007). Compared to traditional desktop GIS, the Geoweb provides an approach that is claimed to be more democratized, user-friendly, and accessible to a broader range of users, particularly nonexperts (Hudson-Smith, Crooks, Gibin, Milton, and Batty 2009; Rinner, Kefiler, and Andrulis 2008). This is partly because of the use of a familiar Web browser to access Geoweb sites and the general simplicity of the Geoweb compared to full-featured desktop GIS (Gorman 2007). The Geoweb is typically considered to have a bidirectional, or participatory, aspect to it, with users contributing content that is then shared with other users (Haklay, Singleton, and Parker 2008; Johnson and Sieber 2011a; Rouse et al. 2007). Geoweb frameworks or application programming interfaces (APIs) such as the Google Maps API or OpenLayers API provide a repository of source codes and tools that allow anyone with sufficient programming skills to develop and customize their own Geoweb platform. Key characteristics of the Geoweb include openness of data and tools, a focus on ease of use and lightweight delivery that is enforced by Web access, and the ability for users to contribute (Haklay et al. 2008). Johnson and Sieber (2011a) define two broad types of the Geoweb; informational and participatory. Informational Geoweb sites serve as lightweight accessible platforms through which data and information are delivered online in a map form. These informational Geoweb sites are in many cases provided by governments as access portals for developers, groups, and individual citizens to access data. Notable examples of these informational sites include the U.S. government data. gov, the Canadian government data.gc.ca, and municipal government sites, such as San Francisco's dataSF.org. Compared to the informational Geoweb, the participatory Geoweb looks to develop a two-way conversation based on map data displayed within the tool. This two-way conversation can be between Geoweb tool developer and tool user, or between users. There are several prominent examples of participatory Geoweb tools, including ArgooMap (Rinner and Bird 2009, Sidlar and Rinner 2009), a platform that was used to spatially situate conversations surrounding a university campus redesign, and crisis maps (De Longueville, Annoni, Schade, Ostlaender, and Whitmore 2010; Goodchild and Glennon, 2010; Liu and Palen 2010), where users and developers communicate up-to-date information on an unfolding crisis. This paper describes the development of a municipal government-centric Geoweb platform used to integrate federal and provincial geospatial data with existing municipal data. …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,004 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».