Task T2

Knowledge Graphs Production and Visualization

Task leader: Camille Bernard – LIG
Participants: J. Gensel, D. Ziebelin, P. Genoud, M. Villanova-Oliver, PA Davoine (LIG); H. Cherifi, E. Leclercq, C. Cruz (LIB); H. Dao, G. Giuliani (ISE); G. Falquet, N. Hamel (CUI); Daniela Milon Florès (LIG/ISE), PostDoc (LIG)                                                                            


This task first elaborates an ontological model for the representation of semantic environmental trajectories. Second, it builds from the indicators and their observations extracted from the infrastructure (T1), semantic environmental trajectories, in the shape of KGs. Third, various modes of visualization of the semantic environmental trajectories will be designed and developed.


A2.1 – Modelling semantic environmental trajectories: aims to define an ontological model for the representation of environmental trajectories. Based on the W3C RDF Data Cube standard, a vocabulary will be defined to link indicators observations over time, even in complex cases such as time-series break due to changes in the geographical support. These multidimensional observations, linked together in time, form semantic environmental trajectories at a conceptual level. The spatial dimension of trajectories will be described using the TSN ontology. Coupled with the TSN-Change ontology, it will be possible to informed about changes in the administrative divisions of the territory observed in the environmental trajectory.

A.2.2 – Generating semantic environmental trajectories: aims to populate the environmental trajectory conceptual model built in A2.1 with data identified in T1, transformed in RDF and described using the vocabulary defined. A program will be developed in order to create KGs representing the semantic environmental trajectories. On the basis of input parameters (an indicator, a period of observation, and a chosen territory) describing the trajectory to be built, the program retrieves the corresponding data from the T1 infrastructure to generate the semantic environmental trajectory in the shape of a KG. All the KGs will be published in a triplestore. Several open source triplestores will be tested during this activity in order to evaluate their scalability and performance for space-time queries in collaboration with the A3.1 activity.

A2.3 – Visualizing semantic environmental trajectories: aims to propose various visualization modes of the KGs built in A2.2. Because of their format and of the multidimensional information they hold, we will explore various visualization modes for the restitution and analysis of environmental trajectories: aspatial visualization of SETTS as RDF graphs, visualization of clusters of trajectories, visualization of environmental trajectories through interactive geographical maps to account for territorial dynamics, visualization through evolving spatiotemporal cubes. The Swiss Territorial Data Lab (STDL)/swisstopo 4D framework will be considered here as well as open-source existing tools such as Gephi[1], CubeViz[2] and D3.js library.[3]


Activity Caption Type Deadline
A2.1 D2.1 Environmental Trajectories Ontological Model Ontological model M12
A2.2 D2.2 Knowledge Graph of raw Environmental Trajectories KGs in a triplestore M24
A2.3 D2.3 Prototype for visualization of semantic environmental trajectories Software Prototype M39


[1] https://gephi.org/

[2] http://cubeviz.aksw.org/

[3] https://d3js.org/