ISTMINER: Interactive Spatiotemporal Co-occurrence Pattern Extraction: A Biodiversity case study
| dc.contributor.author | Sharafeldeen, Dina | |
| dc.contributor.author | Bakli, Mohamed | |
| dc.contributor.author | Algergawy, Alsayed | |
| dc.contributor.author | König-Ries, Birgitta | |
| dc.date.accessioned | 2021-12-14T10:57:28Z | |
| dc.date.available | 2021-12-14T10:57:28Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | In recent years, the exponential growth of spatiotemporal data has led to an increasing need for new interactive methods for accessing and analyzing this data. In the biodiversity domain, species co-occurrence models are critical to gain a mechanistic understanding of the processes underlying biodiversity and supporting its maintenance. This paper introduces a new framework that allows users to explore species occurrences datasets at different spatial and temporal periods to extract co-occurrence patterns. As a real-world case study, we conducted several experiments on a subset of the Global Biodiversity Information Facility (GBIF) occurrences dataset to extract species co-occurrence patterns interactively. For better understanding, these co-occurrence patterns are visualized in a map view and as a graph. Also, the user can export these patterns in CSV format for further use. For many queries, runtimes are in a range that allows for interaction already. Further optimizations are on our research agenda. | en |
| dc.identifier.doi | 10.18420/informatik2021-043 | |
| dc.identifier.isbn | 978-3-88579-708-1 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/37708 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | INFORMATIK 2021 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-314 | |
| dc.subject | Spatiotemporal data mining | |
| dc.subject | Co-occurrence patterns | |
| dc.subject | Biodiversity data mining | |
| dc.title | ISTMINER: Interactive Spatiotemporal Co-occurrence Pattern Extraction: A Biodiversity case study | en |
| gi.citation.endPage | 579 | |
| gi.citation.startPage | 565 | |
| gi.conference.date | 27. September - 1. Oktober 2021 | |
| gi.conference.location | Berlin | |
| gi.conference.sessiontitle | Workshop: Computer Science for Biodiversity (CS4BIODiversity) |
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