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This repository contains the DET components developed within the SALTED project.

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Data Enrichment Toolchain by Universidad de Cantabria

Introduction

📝 Description

This repository contains the DET (Data Enrichment Toolchain) components developed by Universidad de Cantabria (UC) within the SALTED project. This includes collectors, a mapper, a curator, and several linkers and enrichers.

▶️ Workflow

The DET starts by collecting data from heterogeneous sources, and goes all the way to publishing the harmonised enriched data in an NGSI-LD Context Broker. Below is a workflow briefly explaining what each component does:

  • The Data Collectors (collector, sms and kcity folders) harvest data from heterogeneous sources by way of several protocols, such as HTTP or MQTT.
  • The Data Mapper (mapper folder) transforms heterogeneous formats into NGSI-LD, and more specifically Smart Data Models.
  • The Data Curator (curator folder) assesses the quality of the data and tags the NGSI-LD entities accordingly.
  • The Data Linkers and Enrichers (enricher folder) add value to existing data by adding new entities, properties or relationships.

✨ Other components

The Data Curator is based on the Data Quality Assessment module developed by UC.

📧 Contact

All code located in this repository has been developed by Universidad de Cantabria (contact).

Installation

The most simple and effective way of installing the UC DET is by using the provided docker-compose.yml file. Before installing it, however, you may want to adapt the configuration to your particular needs. You can do that by modifying the config.conf file. Next you can run the command:

docker compose up -d --build

All components will be up and running. You can interact with them, check the docker logs, or set up an NGSI-LD Context Broker to use their full potential.

Acknowledgement

This work was supported by the European Commission CEF Programme by means of the project SALTED ‘‘Situation-Aware Linked heTerogeneous Enriched Data’’ under the Action Number 2020-EU-IA-0274.

License

This material is licensed under the GNU Lesser General Public License v3.0 whose full text may be found at the LICENSE file.

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  • Python 98.0%
  • Shell 1.4%
  • Dockerfile 0.6%