Designing Effective Legends and Layouts with a Focus on Nigerian Topographic Maps
Bibliographic record
Abstract
Most mapping research efforts currently focus on the content of maps and the platform used. By examining layout (the spatial arrangement of various map elements) and legends (an example of marginal map information) in topographic maps, this study complements other studies on map content and use. A map's legend, sometimes known as a "key," enables the reader to decipher the meanings of the marks and forms that make up the map's content. The layout style and legend used in many topographic map series in Africa were adopted from colonial maps - for example, Nigeria's topographic maps are reminiscent of British colonial maps - and thus post-independence topographic maps reflect the legacies of colonial mapping. This article describes the design of a layout and legend created, using a digital workflow based on the existing analogue legend, for the Nigerian 1:50,000 topographic map series. Classes of vegetation and transportation features depicted on both the old legend and the proposed new legend were compared to illustrate the enhancements achieved in the latter. Une grande partie des recherches menées actuellement en cartographie portent sur le contenu des cartes et les plate-formes utilisées. En examinant la disposition (l'arrangement spatial de divers éléments sur une carte) et les légendes (un exemple d'information cartographique marginale) des cartes topographiques, la présente étude se veut un complément d'autres études sur le contenu et l'emploi des cartes. La légende de la carte, parfois appelée la « clé », permet à son lecteur de déchiffrer la signification des marques et des formes qui composent le contenu de la carte. Le style de disposition et la légende utilisés pour de nombreuses séries de cartes topographiques des pays africains proviennent des cartes coloniales - par exemple, les cartes topographiques du Nigéria rappellent celles des colonies britanniques - et donc, les cartes topographiques postindépendance reflètent cet héritage venant de la cartographie coloniale. Dans l'article, on décrit la conception de la disposition et de la légende, à l'aide d'un flux numérique et en tenant compte de la légende analogue existante, pour les séries de cartes topographiques de 1:50 000 du Nigéria. La végétation et les transports, deux éléments représentés à la fois sur l'ancienne légende et la nouvelle légende proposée, ont été comparés pour montrer les améliorations qu'apporte la nouvelle légende.
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 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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".