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Record W2802897830 · doi:10.4095/288862

GeoConnections geospatial return on investment case study: PRISM-GIS and PRISM-911

2010· report· en· W2802897830 on OpenAlexaboutno aff
M A Stewart

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPrismGeospatial analysisInvestment (military)GeographyRemote sensingGeologyCartographyBusinessEnvironmental scienceOpticsPhysicsPolitical science

Abstract

fetched live from OpenAlex

In late 2009 GeoConnections commissioned a Geospatial Return on Investment Case Study to add to the body of knowledge of case studies based on the GITA ROI methodology for financial analysis of geospatial projects. The study focuses on the PRISM-GIS and PRISM-911 applications developed by the City of Quinte West in Southern Ontario. PRISM-GIS, launched in 2007, assists First Responders during emergency situations in the field and at the Central Command Centre and facilitates communication between the field and the Command Centre. PRISM-911, launched in 2008, provides emergency notification by telephone. Backward-looking five-year analysis of Quinte West PRISM: Total investment has been $130,757 (2006 $CA). Cumulative benefits are $405,972 (2006 $CA). Net Present Value is $275,215 (2006 $CA), with an annualized Return on Investment of 42.1%. Breakeven point was reached in 2008, two years into the project. The greatest tangible benefit is lowered risk to public health. Considerable benefits were also found from efficiencies in transferring manual notification to automated notification. Forward-looking 15-year analysis of Quinte West PRISM: Cumulative benefits are $3.5M. Net Present Value is $3.1M with an annualized Return on Investment of 54.33%. Payback period is under one year as a result of startup costs being externalized into the backward-looking study. This high rate of return and short payback period reflects the dramatic benefits realized through leveraging the initial work done by the City of Quinte West. Sensitivity analysis: A combined 19-year analysis of Quinte West PRISM showed Net Present Value of $3.109M. ROI is 31.66%. Sensitivity analysis was also performed on the combined 19-year business case showing only benefits to the City of Quinte West, by removing public benefits. Net Present Value to the city alone is $1.261M, with an ROI of 12.84%. Huron County is Quinte West's first external client for PRISM. Huron recently leased PRISM from the City of Quinte West, launching it in November 2009. Forward-looking 16-year analysis of Huron County PRISM: Cumulative benefits are $4,154,920 with a Net Present Value of $3,503,431 and an annualized Return on Investment of 33.61%. Payback period is one year. Huron County's Net Present Value is approximately $400,000 higher than the Quinte West combined study NPV, predominantly a result of greater public benefits from automated notification of Boil Water Advisories. A province-wide analysis illustrates potential costs and benefits if 50 municipalities, counties or regions adopt the system. Cumulative benefits are $163M over the 15-year analysis. Net Present Value is $132M with an annualized Return on Investment of 28.52%. Payback period is one year. Sensitivity analysis was performed to show the effect of slow ramp-up of 50 agency implementations of PRISM over the lifetime of the analysis. This forward-looking 15-year analysis showed Net Present Value of $79.3M. ROI for the ramped study is 26.03%. Cumulative benefits for the ramped study are $100M.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.492
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.279
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2010
Admission routes1
Has abstractyes

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