This document discusses multidimensional data and co-creation in the context of supporting decision making on environmental permits and inspections. It outlines several data sources like IMJV, CBB, and GPBV that contain information on air emissions, water emissions, waste, and companies. These data sources are in different formats like XML, relational databases, and SPARQL endpoints. The document also mentions standards used and describes the current and future architectures to integrate these multidimensional data sources to support use cases for civil servants, citizens, and companies.

1. paul@proxml.be
L(O)SD at dep. Environment,
Flemish Gov.

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Context

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Context

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 Supporting decision making on environmental permits and
inspections
 As a civil servant I want to know the already reported emissions in a
neighborhood to evaluate new emission permit requests for that same area
and plan emission inspection based on previous reporting to enhance
efficiency. ===== Data Integration
 As a citizen I would like to know which emissions are happening in our/a
neighborhood.
 As a company I want to compare my emission values with similar companies.
Objective

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 IMJV (integral environmental year report)
 Air Emissions
 Water Emissions
 Waste
 …
 CBB (Flemish company registry)
 GPBV, Integrated Pollution Prevention and Control (IPPC)
 KBO (Belgian company registry)
 NIS/NACE (codelists)
 CRAB (Flemish adresses registry)
 Supporting controlled vocabularies
Data

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 IMJV (integral environmental year report) – XML in archiving system
 Air Emissions
 Water Emissions
 Waste
 …
 CBB (company registry) – RDBMS (PostgreSQL)
 GPBV (Integrated Pollution Prevention and Control (IPPC)) – XML archive
 KBO – External SPARQL endpoint
 NIS/NACE – External SPARQL endpoint
 CRAB – External SPARQL endpoint
 Supporting controlled vocabularies – CSV, tables
Data sources

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Standards used

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Architecture

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Architecture

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Future Architecture

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Observation

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Application

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Analytics

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Q&A