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Record W4295665722 · doi:10.5194/ica-abs-5-11-2022

Future National Atlases – Strategies for Tearing Down the User’s Firewall

2022· article· en· W4295665722 on OpenAlexaboutno aff
René Sieber, Lorenz Hurni

Bibliographic record

VenueAbstracts of the ICA · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFirewall (physics)TearingComputer scienceComputer securityBusinessEngineeringFinance

Abstract

fetched live from OpenAlex

National atlases have a long tradition; first copies were published in the 19th century (e.g., National Atlas de Finlande in 1899), and they consisted initially only of a series of topographic maps. In the mid 1950ies, the IGU/ICA commission under the lead of Prof. Salitchev propagated a rigid scheme for the map content, consisting of the five categories: Physical environment, Population, Economy, Culture, and Administrative structure (Ormeling 2022). Large format printed atlases were produced, the aim being to demonstrate the power and the beauty of the country. Still today, some national atlases follow basically this structure, sometimes slightly adapted or extended with new categories like Traffic and Ecology. Common to all of these national atlases are well curated atlas maps with a strict display order, and manly addressing the people of the own country, sometimes also used for nation building. With the emergence of electronic national atlases in the 1990es (e.g., Atlas of Canada, Atlas of Spain, Atlas of Sweden), the concept of interactivity was established in atlas GUIs and maps. The benefit of such an interactive design was achieved by changing the map layers, and through the combination of map layers. Around the year 2000, 3D visualizations became possible (e.g., Atlas of Switzerland). These features in digital atlases allowed users to create never-before-seen maps, and exploration of the map content with the help of free navigation, as well as compilation, analysis and comparison of maps and map elements (Hurni and Sieber 2018, Sieber et al. 2019). At the same time, the focus of national atlases shifted from the (propagandistic) nation's viewpoint to a more individual socio-cultural perspective, which is determined by the interests and needs of atlas users. However, with the transition from physical copies (book, CD-ROM, DVD) to publication on the Internet, the visibility of digital national atlases has decreased dramatically. Their use also stagnated because national atlases were not used as an everyday tool, as national and regional geo-browsers -some of which are competitors of an atlas -are today. The plan to install national atlases as an SDI frontend (Kbben 2017) has failed in large part, only the Atlas of the Ukraine is still following this strategy (Putrenko 2022). In addition, there are many internal challenges, inter alia static GUI design, an overload of atlas features, and repetitive visualization (Sieber and Losang 2020). Now, what could be the solution to solve this dilemma? How can we make national atlases more visible, more attractive and more integrated into daily life? We can try to solve this essential challenge with two propositions, one of them is basically a top-down approach, the other one a bottom-up approach. The goal of both approaches is to "tear down the firewall between the visualized data and the user", as Ian Muehlenhaus (2022) recently postulated. In the Top-down Approach, we rely on a customized application, specialized in terms of content, tools and topicality. The maps of such an atlas should cover mostly current events and changes. Thus, people are getting interested and hopefully stay tuned. The thematic focus could be on didactics or geo-sciences, for example, presented in a popular way. This enables the visualization of actual data and current issues. The Bottom-up Approach is apparently more user-driven. It aims to open the national atlas concept to a wide audience, trying to integrate them in the atlas building process. Only the basic technology and instalments like base maps, import/export functionality are provided by the atlas makers. The users themselves define the maps by contributing to the map content, or by assigning the atlas authors to produce maps they are interested in. This approach could be very demanding, since a moderator and/or a quality control is needed. Two further points have to be considered: the way and form of distribution and the fields or key roles of action. Regarding the distribution, a web-based publication is a must, but it can be combined with a printed version (either as a single book or as a series of booklets/ magazines). The most important thing here is: the content of both publication forms must be tailor-made, meaning that the digital version is not only an excerpt of the printed version and vice-versa.

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)0.043
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.068
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.004
Science and technology studies0.0100.005
Scholarly communication0.0270.078
Open science0.0090.027
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0870.031

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 head0.024
GPT teacher head0.288
Teacher spread0.265 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

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Citations2
Published2022
Admission routes1
Has abstractyes

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Same venueAbstracts of the ICASame topicGeographic Information Systems StudiesFrench-language works237,207