GeoChangeViz: Visualizing

Abstract

time. Geographical divisions (GD) being administrative, parcel or census divisions frequently change over time. When such changes are not well documented, they introduce biases in the understanding of the evolution of such a given area. To cope with this problem, we have designed a Knowledge Graph (KG) that allows for the description of many GDs in the world and the changes they undergone over time. In this demo, we present a Web application called GeoChange-Viz that connects to this KG and provides spatial planners with an innovative tool for geovisualizing and understanding territorial changes over Spatiotemporal Knowledge Graph, Knowledge Graph visualization, Linked Geospatial Data ∗Corresponding author. †These authors contributed equally. https://lig-membres.imag.fr/villanov/ (M. Villanova); https://lig-membres.imag.fr/gensel/ (J. Gensel) 0000-0003-2246-6568 (C. Bernard); 0000-0002-0693-8556 (M. Viry); 0000-0002-7242-6102 (M. Villanova); htp:/ceur-ws.org CEUR Workshop Proceedings (CEUR-WS.org) ISN1613-073

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CEUR ceur-ws.org

1. Introduction

All over the world, diferent kinds of Geographical divisions (GD) (being administrative, electoral, census or parcel divisions) are defined by (local) authorities. Following administrative or political reforms and decrees, the boundaries, name or identifier of these GD change over time. For instance, in the United States, census units are frequently redefined to maintain an equivalent number of inhabitants per unit. When such changes are not well documented, they are major obstacles to the understanding of a study area. As a result, decision-makers and spatial planners need tools to monitor these territorial changes and avoid many errors when analyzing data series collected on divisions that have changed. In this demo, we present the GeoChange-Viz Web application designed to assist spatial planners in the monitoring of changes their study areas have undergone. GeoChange-Viz is based on a Knowledge Graph (KG) we have designed [ 1 ], called GeoChange KG1. This GeoChange KG describes GD and their evolution over time. It https://lig-membres.imag.fr/bernardc/ (C. Bernard); https://mthh.github.io/portfolio/ (M. Viry); CEUR Workshop Proceedings provides rich descriptions of GD changes, using terms such as Split, Merge, Name or Identifier change, etc. Moreover, the GeoChange KG is enriched with data from the Open Data Web. The GeoChange-Viz application exploits the structure of this KG to show, by means of innovative graphical components, GD changes along the lifelines of Territorial Units (TU) (i.e., each division of the geographical space in the GD).

2. The GeoChange Knowledge Graph

In [ 2 ], we have presented the TSN2 (Territorial Statistical Nomenclature) ontology whose terms are generic enough to allow for the description of any multi-levels GD that can be found around in the world. This ontology goes hand in hand with the TSN-Change ontology3 which consists of a generic vocabulary for the description of changes in GD (using terms such as name/identifier/boundaries change, merging or splitting of TUs, etc.). In this vocabulary, distinctions are made between changes where the identifiers of the geographical areas persist after change or not (e.g, fusion vs integration). This ensure a clear understanding of the changes and avoid misinterpreting data when a TU does not change its identifier over the versions of a GD, even though it has undergone major geographical changes. The TSN and TSN-Change ontologies are based on (standards) ontologies and frameworks such as GeoSPARQL [ 3 ], OWLTime [ 4 ], PAV [ 5 ], DCTerms4, BFO [ 6 ]. In [ 7 ], we have presented a framework named Theseus to populate the TSN and TSN-Change ontologies. It is based on an algorithm defined for the detection and semantic annotation of territorial changes. Using the Theseus framework, the GeoChange KG can be populated with the description of various GD and versions. So far, the graph contains the description of diverse GD (covering respectively the evolution, over a given period, of GD in Switzerland, Australia, European Union and France). This graph, dedicated to the description of changes in GD, follows a specific structure that is named ”Multi-levels change graph”. This structure is inspired by [ 8 ] while adding the notion of ”multi-level”, since changes that occur at one given level of the GD (e.g., state level) propagate to changes impacting lower divisions (e.g., districts). The scenario of the demo presented here is based on a French GD called AdminExpress 5, in versions 2015 and 2016, which is composed of 3 French administrative levels: regions, departments and municipalities6. The Figure 1 is an extract of the GeoChange KG showing a change event that has occurred at level 2 (municipalities, see label L2 of the nodes in Figure 1) in this GD, between years 2015 and 2016: the integration of a municipality (circled green node with label V2015_L2_38021) into another (circled green node with label V2015_L2_38225) municipality, results in the new municipality with code V2016_L2_38225. In the following section, we show how the GeoChange-Viz application can be used to geo-visualize this graph, and make it available to an audience with no technical background in KG. 2http://purl.org/net/tsn# 3http://purl.org/net/tsnchange# 4https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ 5Source https://geoservices.ign.fr/adminexpress 6Please, note that in the demo video, only an extract of this GD (covering the French region AURA) is loaded from the GeoChange KG, under the name GeoflAURA.

3. The GeoChange-Viz Web Application

The GeoChange-Viz application connects to the GeoChange KG and guides users, step by step, in their understanding of territorial changes. In a similar approach to the SexTant application [ 9 ], GeoChange-Viz focuses on the visualisation of the temporal dimension of linked geospatial data. In [ 10 ], the authors present a generic model for delivering time-evolving 3D city models for Web visualization. They describe transitions between two versions of a geographic feature. They propose to link documents to these transitions which help to give elements of proofs regarding how geographic features evolve in time. Our approach is also to describe the changes (or transitions) between two versions of a GD, by semantizing these changes and searching the Web for documents that can explain their causes. Indeed, each year, Urban Planning Authoritative Services (UPAS) must identify where, when, how much, why and how territorial changes took place, in order to maintain their expertise on their study area and to transfer their statistical data into the latest version of the GD. In particular, knowing how the TUs change over time (i.e., the nature of the change event) helps them in determining the appropriated statistical data processing for this transfer. In this demo, we will progressively show how such an UPAS can answer these where, when, how much, why and how questions from the application.

Where? When? How much? Within GeoChange-Viz, several UIs have been designed to understand territorial changes step by step. In particular, the UI named Synchronised maps helps the user to quickly identify where the changes have taken place, using a set of colors highlighting the changes on the map according to their nature (on the contrary, unchanged units are kept grey) (see Figure 2). The two synchronized maps are dated (giving information on the When): the map on the right shows the TUs before the change event and, on the left, the TUs after the change event. Below the map, a bar graph quantifies the number of TUs impacted. Also, the Change Catalog tab lists and quantifies the change events, according to their nature (providing information on the How much).

Why? How? By selecting a TU on the map, the user accesses its description, enriched with external descriptions (e.g., links to LOD Wikipedia, Geonames and Wikidata representations of the TU) that, most of the time, confirm the territorial change and explain it. Similarly, when the information is available on the Web, the GeoChange KG connects to legislation (providing information on the Why). Also, a UI component named Change Bridge gives the user access to a visualization of a bunch of the GeoChange KG with semantic labels describing the nature of the change event (providing information on the How). For instance, as shown in the Figure 2, the user has selected a municipality on the right map and, in the Change Bridge component, s-he learns that this TU has merged with another. As one of the merging TUs keeps its identifier after the change event, the change event is described as an Integration in the GeoChange KG. This precision is important as it may alert users and avoid misinterpretation of statistical data that refer to a TU using its unchanged identifier while its boundaries and, consequently, probably its number of inhabitants, have changed.

4. Conclusion

In this demo, we have shown how the use of semantic Web technologies with UI can help spatial planners in understanding how GD evolve over time. KGs are here first used to represent GDs and the changes they are subject to, and then enriched by contextual information that brings explanations for the observed evolution. Our future work will consist in carrying out a study on the use of the application in order to reinforce the key functionalities of the application. Demo link: https://videos.univ-grenoble-alpes.fr/video/26646-demo-GeoChange-Viz-iswc-2023mp4 Password: 2023-geochange-iswc

Acknowledgments

This work is supported by LINKSIUM, SATT Grenoble Alpes.

References

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