Abstract
Network kernel density visualization (NKDV) is an important tool for many application domains, including criminology and transportation science. However, all existing software tools, e.g., SANET (a plug-in for QGIS and ArcGIS) and spNetwork (an R package), adopt the naïve implementation of NKDV, which does not scale to large-scale location datasets and high-resolution sizes. To overcome this issue, we develop the first python library, called PyNKDV, which adopts our complexity-reduced solution and its parallel implementation to significantly improve the efficiency for generating NKDV. Moreover, PyNKDV is also user friendly (with four lines of python code) and can support commonly used geospatial analytic systems (e.g., QGIS and ArcGIS). In this demonstration, we will use three large-scale location datasets (up to 7.71 million data points), provide different python scripts (in the Jupyter Notebook), and install existing software tools (i.e., SANET and spNetwork) for participants to (1) explore different functionalities of our PyNKDV library and (2) compare its practical efficiency with existing software tools.
Original language | English |
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Title of host publication | SIGMOD '23 |
Subtitle of host publication | Proceedings of the 2023 International Conference on Management of Data |
Editors | Sudipto Das, Ippokratis Pandis |
Publisher | Association for Computing Machinery (ACM) |
Pages | 99-102 |
Number of pages | 4 |
ISBN (Print) | 9781450395076 |
DOIs | |
Publication status | Published - 18 Jun 2023 |
Event | ACM SIGMOD International Conference on Management of Data, SIGMOD 2023 - Hyatt Regency Bellevue Hotel, Seattle, United States Duration: 18 Jun 2023 → 23 Jun 2023 https://2023.sigmod.org/ https://dl.acm.org/doi/proceedings/10.1145/3555041 |
Publication series
Name | Proceedings of the ACM SIGMOD International Conference on Management of Data |
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ISSN (Print) | 0730-8078 |
Conference
Conference | ACM SIGMOD International Conference on Management of Data, SIGMOD 2023 |
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Country/Territory | United States |
City | Seattle |
Period | 18/06/23 → 23/06/23 |
Internet address |
Scopus Subject Areas
- Software
- Information Systems
User-Defined Keywords
- NKDV
- geospatial analytic systems
- python library