GeoConnections geospatial return on investment case study: Multi-Agency Situational Awareness System (MASAS)
Bibliographic record
Abstract
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 MASAS, Multi-agency Situational Awareness System, developed by New Brunswick Emergency Measures Organization. GeoConnections funded this project under a multi-agency situational awareness initiative with the intention of expanding MASAS to a national deployment. MASAS is intended to better enable emergency management practitioners in preparing for and mitigating the impacts of emergency incidents through timely sharing of geospatially-referenced information. The New Brunswick MASAS implementation provides situational awareness data aggregation, as well as connection to the national MASAS. New Brunswick MASAS was developed following an unusually large 2008 spring flood event, which resulted in damage claims in excess of $22M and required support from organizations outside the province. MASAS addresses the need to automate the information distribution and communication process during an emergency and to allow visual presentation of this information on maps. MASAS also provides for the use of shared tools by adopting open standards for application development. This study includes benefits to staff at: Prince Edward Island Emergency Operations Center, Royal Canadian Mounted Police, Communications New Brunswick, Regional Health Offices, New Brunswick Department of Transportation, City of Edmundston, Policing Services, and New Brunswick Emergency Operations Center. Forward-looking five-year analysis of New Brunswick MASAS: Cumulative benefits are $1.006M. Cumulative costs are $552K. Net Present Value (benefits minus costs in 2008 dollars) is $454K with an annualized Return on Investment (ratio of Net Present Value to cumulative costs) of 16.42%. Payback period is three years, showing a break-even point in 2011. This study uses a scaling factor based on average annual disaster claims over fifty years, taken to 2008 dollar values. The analysis reflects costs required for a Communications New Brunswick interface in order to realize public health benefits. Alternate scenario: As many of the benefits of the study come from time savings to public health staff working routine events such as boil water notification, an alternate scenario omitting benefits to health staff was created. Cumulative benefits are $668K. Cumulative costs are $481K. Net Present Value is $187K with an annualized Return on Investment of 7.76%. Payback period is four years, showing a break-even point in 2012. Conclusions: Estimated benefits begin to accrue midway through the five-year analysis, leaving only 2 ½ years for benefits to accrue. A longer study would permit the collection of more benefits over time, yet this technology is evolving so rapidly that a longer study was considered inappropriate. Many potential benefits come from routine activities rather than disaster-driven activities. Expanding to daily use would serve to reinforce staff familiarity with the tool set and increase their effectiveness during a disaster.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".