Integrating Plant Protection Product Data using Semantic ... · SEMIC 2013 June 21, Dublin . Who we...

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Integrating Plant Protection

Product Data using Semantic

Technologies

Giorgos Georgiannakis

SEMIC 2013

June 21, Dublin

Who we are

Why Semantic Technologies

• Data rich organisation

• Facilitate sharing of data

• Nature of data

• Openness

• Formats

• Exchange

• Applications

Objective

• Make up-to-date public data available

• Apply standard open data formats

• Share access to the data (humans and machines)

• Provide relevant links to the data

• Facilitate relevant linking to the data

• Develop applications based on the data

The case for plant protection products in EU

A simple yet difficult

to answer question:

“Which products

are authorised for

a crop / pest?’’

DATA CONSUMER

?

Lack of a single point of access

GR

DG Plant Produce

HU

Agrinex

NL

CTGB

PL

BIP

SE

KEMI

AT

AGES

BE

Fytoweb

DE

BVL

Data fragmentation Heterogeneous data formats

Lack of common identifiers

ISA Activity

Domain ontology

(DG Health and

Consumers) Data Cleansing

Common

Taxonomies

Member States

Data / Systems

Common Data Models RDF Repository

SPARQL Faceted browsing

Services

DG Health and Consumers Activities

• Open Data

• Linked Data

• Architecture and infrastructure

• Linking and publishing data from external sources

• MS Authorities

• International authorities

Make up-to-date pubic data available

• Legal obligation

• Data inventory (lack of interoperability)

• Heterogeneous data

• Data exchange and sharing national datasets

• Open Data Portal http://open-data.europa.eu/

Setting an Architecture with Standard Open Data Formats

UI – publication

SPARQL User Interface

Linked Data Tools – Data Dictionary Maker

• Web app

• Create information models

• Describe content of datasets

• Use restricted value lists

• Publish this model on the web for data collection

Linked Data Tools - RDFa Maker

• Transform a CSV dataset into a mini-RDFa, static

website

• Generates an index (URI) to the dataset

• Publish on a local webserver

• Each row of the CSV file must contain:

• Id (unique and permanent identifier)

• Label

• Description

• Datasets are available as human or machine-readable

Linked Data Hub

The process for publication and linkage

• Original data

• Modeling concepts

• Transformation

• Linkage

• Publication

• Applications

• Content Maintenance and evolution

Messages

• Difficulties to link data from multiple sources

• Value of

• Ontologies

• Taxonomies

• Vocabularies

• Technologies are available and mature

• Build for evolution

• Model

• Data

• Practical solutions vs. huge projects

Thank you!