GeoConnections geospatial return on investment case study: BCeMap (MASAS)
Notice bibliographique
Résumé
In late 2009 GeoConnections commissioned a series of Geospatial Return on Investment Case Studies to add to the body of knowledge of case studies based on the GITA ROI methodology for financial analysis of geospatial projects. This study focuses on BCeMap, developed by Emergency Management BC (EMBC) and GeoBC to enhance the Emergency Management Information Service (EMIS) being implemented by EMBC. The BC Emergency Map Viewer (BCeMap) as part of the Multi-Agency Situational Awareness System (MASAS) is intended to enable emergency management practitioners in preparing for and mitigating the impacts of emergency incidents through timely sharing of geospatially referenced information. BceMap focuses on situational awareness data aggregation and connection to the national MASAS. BCeMap provides a single resource to aggregate relevant incident data for emergency management and public safety personnel within BC and across Canada (via the MASAS integration) rather than use of several disparate systems where overlap, higher level effects and trends could be overlooked. In addition to the inherent efficiencies of seeing multiple data types in one common view, BCeMap has the potential to improve agency collaboration and improve public safety. BCeMap was developed as a pilot project for the 2010 Olympic and Paralympic Games, using $198,000 in GeoConnections funding and matching in-kind resources. The pilot demonstrated capabilities for southwest British Columbia in the area where the games were held. EMBC is currently working to secure funding to move BCeMap to a full production mode and to extend its data capabilities to include the entire province. There is also an effort to extend awareness and training regarding the tool set throughout the stakeholder community. Areas of where greatest tangible benefits were projected for this study include: - Improved staff efficiency for routine operations - Improved efficiency for event response - Greater efficiency in protection of critical infrastructure - Greater efficiency in preservation of business continuity Areas where additional significant benefits were projected include: better retention of volunteers, improved effectiveness of volunteers, enhanced revenue from critical infrastructure owners, improved logistics regarding available transport during events, cost avoidance from redundant field data collection in areas with frequent fires, time saved maintaining critical infrastructure contact information, and time saved seeking information by district health staff. Forward-looking five-year analysis of BCeMap: Cumulative benefits are $2.4M. Net Present Value is $1.8M, with an annualized Return on Investment of 60%. Payback period is two years. This high rate of return and short payback period points to the dramatic benefits that can be realized through use of real-time data feeds, development of standards to support interoperability, and implementation of interagency data sharing for situational awareness.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».