=Paper=
{{Paper
|id=Vol-3890/paper-45
|storemode=property
|title=FAIR Software as a Service: Combining tools to implement FAIR for clinical data platforms
|pdfUrl=https://ceur-ws.org/Vol-3890/paper-45.pdf
|volume=Vol-3890
}}
==FAIR Software as a Service: Combining tools to implement FAIR for clinical data platforms==
https://ceur-ws.org/Vol-3890/paper-45.pdf
FAIR Software as a Service: Combining tools to implement FAIR
for clinical data platforms
Rick Overkleefta,b, Sander van Booma,b, Eric Prud’Hommeauxc, Kees Burgerd, Jip Fransenb,
Teus Kappene, Luiz Bonino da Silva Santosb,f, Rajaram Kaliyaperumalb and Marco Roosb
a
4MedBox Nederland B.V, Kanaalpark 157, Leiden, 2321 JW, The Netherlands
b
Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands
c
Janeiro Digital, 2 rue nouvelle de Wailly, Clermont-Ferrand, 63000, France
d
Health-RI, Utrecht, The Netherlands
e
Universitair Medisch Centrum Utrecht, Utrecht, The Netherlands
f
Technical University Twente, Enschede, The Netherlands
Abstract
Many DCCs have operational expertise in deploying software services, but lack expertise in
deploying and exploiting FAIR services that use Semantic Web technology for machine
actionability. Although local deployment is lightweight and non-invasive for institutional
infrastructure, engineers are not yet familiar with the underlying web technologies of FAIR
services. This poses a risk for delivering the FAIR foundation of a federated health data
infrastructure that is ready for federated analytics, AI, and machine learning.
This project is making deployment by institutional DCCs of FAIR services cost-effective,
scalable, and sustainable by delivering ‘FAIR Software as a Service’ (FAIR-SaaS).
Keywords 1
FAIR, implementation, architecture, FAIR Data Point, SaaS
1. Introduction
Semantic Web (SW) technology is a common implementation choice for software services that help
meet the machine actionability requirement of the FAIR principles. An example is the DCAT-based
FAIR Data Point (FDP) [1]. Although local deployment is lightweight for SW experts and non-
invasive for institutional infrastructure, adoption is hampered if engineers are not yet familiar with the
underlying technologies of FAIR services. IT departments and Data Competency Centres (DCCs)
usually have operational expertise in deploying software services as such, but lack expertise in using
Semantic Web technology. This poses a risk for delivering the FAIR foundation of a federated health
data infrastructure that is ready for federated analytics, AI, and machine learning.
We present our first results of a project that aims to make deployment of FAIR services by
institutional DCCs cost-effective, scalable, and sustainable by delivering ‘FAIR Software as a
Service’ (FAIR-SaaS). FAIR-SaaS is centrally hosted software that is preconfigured and updated by
FAIR specialists for institutional DCCs. The project starts with (i) common FAIR Data Point (FDP)2
configurations that DCCs can deploy to describe their resources for machines, (ii) grlc-inspired
configurations facilitating DCCs to generate common APIs from FAIR metadata.
SWAT4HCLS 2024: The 15th International Conference on Semantic Web Applications and Tools for Health Care and Life Science,
February 26–29, 2024, Leiden, Netherlands
Rick Overkleeft, Sander van Boom, Eric Prud’Hommeaux, Kees Burger, Jip Fransen, Teus Kappen, Luiz Bonino, Rajaram Kaliyaperumal,
Marco Roos, 02-01, 2024, Leiden, The Netherlands
EMAIL: rick@4medbox.eu (A. 1); svanboom@4lifesupport.eu (A. 2); m.roos@lumc.nl (A. 9)
ORCID: 0009-0004-3529-1159 (A. 1); 0009-0004-1020-475X (A. 2); 0000-0003-1775-9921 (A. 3); 0000-0002-5437-779X (A. 4); 0000-
0003-1895-0998 (A. 6); 0000-0002-1164-1351 (A. 7); 0000-0002-1215-167X (A. 8); 0000-0002-8691-772X (A. 9)
©️ 2024 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
2
FAIR Data Point conform the FAIR Data Point specifications is a service that provides access to machine actionable metadata describing a
resource, including pointers to data sets in one or more formats. The metadata is described in terms of the Data Catalogue Vocabulary (DCAT)
CEUR
and extensions thereof. See https://specs.fairdatapoint.org/
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
An early target is to simplify the processes for DCCs to contribute FDPs for data and compute
capacity to the Dutch national health infrastructure, and comply with multiple existing and future
common APIs. FAIR SaaS are straightforward to update for FAIR experts (e.g. grlc SaaS requires
simple queries on FAIR metadata) who can guarantee convergence to international standards. The
hypothesis is that FAIR SaaS provided by SURF, the Dutch national hosting organisation, which
requires a minimal number of Semantic Web experts for maintenance, has a significant impact on the
applicability, scalability, and sustainability of a health data infrastructure, demonstrating how a
critical mass of FAIR (meta)data can be achieved for enhancing health care and life sciences.
2. From concept to development
A use-case has been defined with local health data project leaders from the LUMC, UMC Utrecht and
Erasmus MC, to develop the overall architecture and concept of the service:
As a cardiologist I would like to see
information on physical fitness (weight,
stamina, blood pressure, etc.) for patients
planned for thorax surgery across two
hospitals, such that I can screen patients
based on their physical fitness for surgery
and take decisions on timing of surgery and
capacity planning. Patients that are not
selected must undergo a fitness program.
The use-case was used to create the business
architecture that has been defined in Figure
1, which resulted in the application Figure 1 FAIR-SaaS Business architecture, a conceptual
architecture defined in Figure 2. From a overview of the need by the experts.
FAIR mindset, we have defined that these
services do not need to be created by us but
should be re-used where available and
adjusted if necessary.
To lower the amount of knowledge about
Semantic Web technology needed by IT
personnel we concluded that the first services
will be delivered in a docker container and that
we need to set up a Virtual Machine (VM) Figure 2 FAIR-SaaS Application architecture, a conceptual
image with these dockers pre-installed. The overview of the software services that are needed to address the
VM is optional if docker knowledge is present need of the experts.
at the specific IT department. We are currently
combining existing tools to develop these features.
3. Acknowledgements
We acknowledge SURF and NWO for support and funding, Health RI, the European Joint Programme
Rare Diseases and EOSC-Life for developments leading to this project (H2020 N°82557, 824087).
4. References
[1] Luiz Olavo Bonino da Silva Santos, Kees Burger, Rajaram Kaliyaperumal, Mark D. Wilkinson; FAIR Data Point: A
FAIR-Oriented Approach for Metadata Publication. Data Intelligence 2023; 5 (1): 163–183. doi:
https://doi.org/10.1162/dint_a_00160