Knowledge Graph for Open Government Data - Case of ESGREEN

🌲 A RDF knowledge graph for green spaces infrastructure (trees, parkland, green areas) data of a city that are relevant for Open City Project.

To make BIODIVERSITY data Interoperable (the I in FAIR).

• Research Project Proposal

Potential SPARQL Research questions

• 1. city center most abundant organisms.
• 2. outside city center.
• 3. areas with least and most diverse species diversity (Shannon Index).
• 4. Diversity Index: we can measure how evenly diversity exists in your tree inventory.

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Inputs

A total of 18 datasets originally from Madrid Green Data Space are used to generate the Ontology. These datasets consist of measures (e.g., number of trees) and dimensions describing the measures (e.g., regions)

• Raw Datasets
• Clean Dataset

Other external datasets:

We will map each specie with global identifier within biodiversity database (e.g. wikidata API or Global Biodiversity Information Facility. This will allow us to get further information about species such kingdom, genus name, family name and global identifier. See data-argumentation.py

• Unique Tree data
  • Geographical location
  • Scientific or species name
  • Genus name
  • Family name
  • Global Identifier

Open Tree of Life or Encyclopedia of Life are some other free and open biodiversity data.

Data Model

Concepts and properties are annotated with the Semanticscience Integrated Ontology.

The figure below gives an overview of upper level concepts and properties used in our data model.

You can browse different ESGREEN modules by visiting the links below:

• Arbolado Parques Historico y Singulares
• Arbolado Zonas Verdes Distritos Calles
• Estado Parques Historico y Singulares
• Estado Zonas Verdes Distritos Calles
• Masas Parques Historico Singulares Forestales
• Masas Zonas Verdes Distritos Calles

We have used this API to generate documentation related to ESGREEN modules.

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License

Copyright (C) 2021

MIT License

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