serdif

The Semantic Environmental and Rare disease Data Integration Framework (SERDIF) seeks to enable the data linkage between health events and environmental data for health data researchers.

Latest working version: offline-version

Offline-version: Docker
Example user interface: https://serdif.fht.org/

Summary

SERDIF is combination of methods and tools based on the use of World Wide Web Consortium (W3C) standards to model graph data: the Resource Description Framework (RDF), the RDF query language SPARQL SPARQL and the databases to store RDF graphs.

The Knowledge Graph (KG) component is where environmental data and health data is linked together through location and time using RDF and SPARQL queries.
The Methodology is a series of steps that guides the researcher in linking particular events with environmental data using Semantic Web technologies.
The User Interface (UI) component is designed from a user-centric perspective to support health data researchers access, explore and export the linked health-environmental data with appropriate visualisations, and by facilitating the query formulation for non-Semantic Web experts.

The data linkage takes place at a query level where the geographic location (GeoSPARQL) and time window (xsd:dateTime are used as the common aspects to link the data for each event.

Evaluation

The usability and potential usefulness of the SERDIF framework has been evaluated following an interative user-centred design that included three phases. The KG and UI documentation for each of the phases is made available in phase-1/, phase-2/ and phase-3/.

Publications associated with each of the phases

phase-1: A. Navarro-Gallinad, F. Orlandi and D. O’Sullivan, Enhancing Rare Disease Research with Semantic Integration of Environmental and Health Data, in: The 10th International Joint Conference on Knowledge Graphs, IJCKG’21, Association for Computing Machinery, New York, NY, USA, 2021, pp. 19–27. ISBN 978-1-4503-9565-6.https://doi.org/10.1145/3502223.3502226
phase-2: A. Navarro-Gallinad, F. Orlandi, J. Scott, M. Little and D. O’Sullivan, Evaluating the usability of a semantic environmental health data framework: approach and study. Semantic Web Journal 11(1) (2022), Publisher: IOS Press. https://doi.org/10.3233/SW-223212
phase-3: drafting

Contact

This space is administered by:

Albert Navarro-Gallinad
PhD Student in Computer Science
ADAPT Centre for Digital Content in Trinity College Dublin Dublin, Ireland
anavarro@tcd.ie

GitHub: navarral

ORCID: 0000-0002-2336-753X