Usability Trumps Features: User needs and the redesign of a web-based GIS to support community environmental monitoring
Bibliographic record
Abstract
Web-distributed tools that complement community-based environmental monitoring (CBEM) initiatives can improve processing of and access to information, supporting environmental education and better informing decision-making. To this end a web-based geographic information system known as “Juturna” was developed to support CBEM in the vicinity of Toronto, Canada. This web-GIS facilitates input, analysis, and reporting of community data. However, use of the system steadily declined in activity since this initiative started in 2004. Lay users reported that the system was complicated and confusing, and so discouraged use. Also, it employed expensive proprietary software, which was a disincentive for the local Conservation Authority and collaborating NGO to adopt the system. To revitalize use of the website and provide support to the CBEM program, we undertook to redesign the web-GIS using open source software. To understand why the original web-GIS was not well used and to inform redesign of the system, we implemented a user-centered design methodology. Methods included user testing, rapid prototyping and stakeholder interviews. The process was invaluable in prioritizing user tasks, defining characteristics of users of the website, and identifying those components of the web-GIS most confounding to them. Findings were used to inform re-development of the web-GIS through an iterative process that led to the creation of two prototypes that were evaluated by the user audience and so informed the design of a new (more accessible) website.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".