Integration of metadata across different GI platforms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Geographic information (GI) is produced and used by wide range of scientific spheres. There is an obvious tendency to integrate data and information from various branches of scientific research and also across different languages. This paper is, among others, a brief overview and evaluation of existing standards for integration of metadata. Main focus is on the standard ISO 19115. This standard is the basics for metadata integration in INSPIRE (The Infrastructure for Spatial Information in Europe). Possibilities of metadata extensions and community profiles are also included. Spatial data are usually distributed over several existing systems (geographical information systems, database management systems or file systems). A lot of work has been related to metadata integration till now. However, we can find only a few examples of appropriate metadata integration in present GI platforms. Thus, related step and main focus of this research is to analyze the main GI platforms that are used across the world. The following platforms were analyzed: Bentley, ESRI, Intergraph and some other metadata software providers, like MICKA, GeoNetwork and METIS. First of all, we have to analyze all supported standards (including their versions, exchange formats, etc.) in the analyzed GI platform. Afterwards, there has to be an analysis of main characteristics of the platform (i.e. software, data structure, import and export of metadata, editing, querying, supported catalogue service, system control, users control, language support, portrayal and future work on this GI platform). Finally, it is necessary to define a way how to integrate metadata independently on the GI platform. This research has been supported by funding from project No. MSM0021622418 called Dynamic geovisualization in risk management and project No. T206030407 called Management of geographic information and knowledge.
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.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it