Supplementary materials for the publication "Event inventories: Estimating the temporality of landscape scenic resources from user-contributed geodata."
datacite.FundingReference.funderName | Deutsche Forschungsgemeinschaft | |
Contributing person | Burghardt, Dirk (orcid: 0000-0003-2949-4887) | |
Documentation of the data | Methods: 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 Data Acquisition: Data query from public Application Programming Interfaces (APIs). Data Processing: The workflow to load and process the data provided is available in Jupyter Notebooks. | |
Countries to which the data refer | UNITED STATES OF AMERICA | |
Countries to which the data refer | GERMANY | |
References to related material | https://gitlab.hrz.tu-chemnitz.de/ad/ephemeral_events | |
Description of the data | 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 | |
Type of the data | Software | |
Type of the data | Other | |
Type of the data | Image | |
Type of the data | Dataset | |
Type of the data | Text | |
Total size of the dataset | 12182545 | |
Author | Dunkel, Alexander | |
Author | Burghardt, Dirk | |
Upload date | 2023-08-25T07:34:18Z | |
Publication date | 2023-08-25T07:34:18Z | |
Publication date | 2026-06-11T15:47:12Z | |
Data of data creation | 2023 | |
Publication date | 2023-08-25 | |
Abstract of the dataset | Supporting Information for the conference publication "Event inventories - Estimating the temporality of landscape scenic resources from user-contributed geodata." (2023 Visual Resource Stewardship Conference). 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 | |
Public reference to this page | https://opara.zih.tu-dresden.de/handle/123456789/2666 | |
Public reference to this page | https://doi.org/10.25532/OPARA-237 | |
dc.language | eng | |
Publisher | Technische Universität Dresden | |
Licence | Attribution-NonCommercial 4.0 International | |
URI of the licence text | http://creativecommons.org/licenses/by-nc/4.0/ | |
Specification of the discipline(s) | 3::34 | |
Title of the dataset | Supplementary materials for the publication "Event inventories: Estimating the temporality of landscape scenic resources from user-contributed geodata." | |
Research instruments | Carto-Lab Docker v0.14.0 (https://gitlab.vgiscience.de/lbsn/tools/jupyterlab) | |
Underlying research object | Data query from public Application Programming Interfaces (APIs). | |
Project abstract | "Geovisual analysis of VGI for understanding people’s behaviour in relation to multi-faceted context" Volunteered Geographic Information (VGI) in the form of actively and passively generated spatial content offers extensive potential for a wide range of applications. Realising this potential however requires methods which take account of the specific properties of such data, for example its heterogeneity, quality, subjectivity, spatial resolution and temporal relevance. The creation and production of such content through social media platforms is an expression of human behaviour, and as such influenced strongly by events and external context. In this project we will develop geovisual analysis methods which show how actors interact in LBSM, and how their interactions influence, and are influenced by, their physical and social environment and relations. | |
Project title | EvaVGI |
Files
Original bundle
Collections
