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Supplementary materials for the publication "Event inventories: Estimating the temporality of landscape scenic resources from user-contributed geodata."
Metadaten
| Weitere mitwirkende Personen, Institutionen oder Unternehmen | dfg - Funder | |
| Weitere mitwirkende Personen, Institutionen oder Unternehmen | Burghardt, Dirk (orcid: 0000-0003-2949-4887) - ProjectLeader | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Dunkel, Alexander | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Burghardt, Dirk (ORCID: 0000-0003-2949-4887) | |
| Beschreibung der weiteren Datenverarbeitung | The workflow to load and process the data provided is available in Jupyter Notebooks. | |
| Art der Erhebung der Daten | Other: Data query from public Application Programming Interfaces (APIs). | |
| Verwendete Forschungsinstrumente | Carto-Lab Docker v0.14.0 (https://gitlab.vgiscience.de/lbsn/tools/jupyterlab) | |
| Zugrundeliegende Forschungsobjekte | Other: Data query from public Application Programming Interfaces (APIs). | |
| Kurzbeschreibung | Supporting Information for the conference publication > Event inventories: Estimating the temporality of landscape scenic resources from user-contributed geodata. Updates may have been made since submission to Opara. The original git repository can be found here: https://gitlab.hrz.tu-chemnitz.de/ad/ephemeral_events | |
| Angewendete Methoden oder Verfahren | We use a workflow based on HyperLogLog (HLL) that was first demonstrated by Dunkel et al. [1], for studying user frequency of social media posts for various resolutions. HLL allowed us to reduce the data collection footprint to quantitative measurements early in the process. Consequently, the study illustrated here can be repeated without the need to store raw data, providing both performance and privacy benefits [1]. All quantities available through this data repository and reported in the paper are estimates, with guaranteed error bounds of ±2.30% [1]. [1]: Dunkel A, Löchner M, Burghardt D. Privacy-aware visualization of volunteered geographic information (VGI) to analyze spatial activity: a benchmark implementation. ISPRS Int J Geo-Information. 2020;9. doi:10.3390/ijgi9100607 | |
| Länder, auf die sich die Daten beziehen | GERMANY | de |
| Länder, auf die sich die Daten beziehen | UNITED STATES OF AMERICA | de |
| Sprache | eng | |
| Entstehungsjahr oder Entstehungszeitraum | 2023 | |
| Veröffentlichungsjahr | 2023 | |
| Herausgeber | Technische Universität Dresden | |
| Referenzen auf ergänzende Materialien | IsPartOf: 123456789/5929 (Handle) | |
| Inhalt der Forschungsdaten | Text, Image, Dataset, Software, Workflow: The repository contains: - Input Data: CSVs (abstracted, privacy-friendly HyperLogLog data) - Code: *.py - Jupyter Notebooks: *.ipynb (Code) - Jupyter Notebooks: *.md (code, comments) - Jupyter Notebooks: *.html (code, comments, output, for archive purposes) - Output: png (figures and graphics) - Output: svg (selected figures and graphics) - Output: pdf (svg, converted to pdf, for archive purposes) - Chore: Other files necessary to reproduce figures and output | |
| Inhaber der Nutzungsrechte | Technische Universität Dresden | |
| Nutzungsrechte des Datensatzes | CC-BY-NC-4.0 | |
| Angabe der Fachgebiete | Geological Science | de |
| Angabe der Fachgebiete | Environmental Science and Ecology | de |
| Titel des Datensatzes | Supplementary materials for the publication "Event inventories: Estimating the temporality of landscape scenic resources from user-contributed geodata." |
Dateien zu dieser Ressource
Die Datenpakete erscheinen in:
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Supporting Information: Event inventories - Estimating the temporality of landscape scenic resources from user-contributed geodata. [1]
This collection contains Supporting Information for the conference publication "Event inventories - Estimating the temporality of landscape scenic resources from user-contributed geodata." (2023 Visual Resource Stewardship Conference).