Abstract
Data spaces are one of the key technology pillars of the European Strategy for Data, which intends to establish a single market inside the European Union (EU) for the efficient and secure sharing and interchange of data across industries. A data space that could combine and correlate cross-sector knowledge from the healthcare and environmental sectors could play a crucial role in determining the future of healthcare. Given that climate change is the single greatest health threat facing humanity and that health professionals worldwide are already responding to the health harms caused by this develo** crisis, such a solution would enable the identification and correlation of environmental influences on human health as well as the extraction of novel biomarkers. However, the difficulties in creating such infrastructure necessitate cutting-edge, multidisciplinary research in numerous fields. This manuscript contributes into providing a visionary approach toward a single-entry point ecosystem to access, share, and trade cross-sector data assets originating from the environmental and healthcare domains through a Cross-sector Data Space (CDS), thereby effectively promoting European technological autonomy in data sharing. This CDS will consider a variety of analytics as ready-to-use solutions to facilitate analysis, prediction, and monitoring of the causality, correlation, reasoning, and practical visualization of real-time environmental settings, as well as to identify the effects of climate change to human health.
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References
Bruzzone, G., et al.: As Open as Possible, as Closed as Needed: Challenges of the EU Strategy for Data. Les Nouvelles-Journal of the LESI 56(1), 41–49 (2021)
Mavrogiorgou, A., et al.: FAME: federated decentralized trusted data marketplace for embedded finance. In: International Conference on Smart Applications, Communications and Networking (SmartNets), pp.1–6 (2023)
Braud, A., et al.: The road to European digital sovereignty with Gaia-X and IDSA. IEEE Netw. 35(2), 4–5 (2021)
Curry, E.: Future research directions for dataspaces, data ecosystems, and intelligent systems. Real-time Linked Dataspaces, pp. 297–304 (2020)
Mitra, S., et al.: Impact of heavy metals on the environment and human health: Novel therapeutic insights to counter the toxicity. J. King Saud Uni. Sci. 34(3), 101865 (2022)
Solmaz, G., et al.: Enabling data spaces: existing developments and challenges. In: Proceedings of the 1st International Workshop on Data Economy, pp. 42–48 (2022)
Kiourtis, A., et al.: Identity management standards: a literature review. Comput. Inform. 3(1), 35–46 (2023)
Wise, J.: Climate change: window to act is closing rapidly. BMJ 380, 674 (2023)
Noll, M.: Exponential life-threatening rise of the global temperature (2023)
Malla, F.A., et al.: Understanding climate change: scientific opinion and public perspective. Climate Change: The Social and Scientific Construct, pp.1–20 (2022)
Climate Change, https://www.who.int/health-topics/climate-change#tab=tab_1. Accessed 29 Sept 2023
Naiyer, S., Abbas, S.S.: Effect of greenhouse gases on human health. In: Sonwani, S., Saxena, P. (eds.) Greenhouse Gases: Sources, Sinks and Mitigation, pp. 85–106. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-4482-5_5
Is Europe reducing its greenhouse gas emissions?, https://www.eea.europa.eu/themes/climate/eu-greenhouse-gas-inventory/is-europe-reducing-its-greenhouse, last accessed 2023/09/29
Progress made in cutting emissions. https://climate.ec.europa.eu/eu-action/climate-strategies-targets/progress-made-cutting-emissions_en. Accessed 29 Sept 2023
2050 long-term strategy. https://climate.ec.europa.eu/eu-action/climate-strategies-targets/2050-long-term-strategy_en. Accessed 29 Sept 2023
Design Principles for Data Spaces, H2020 OPEN-DEI Position Paper. https://design-principles-for-data-spaces.org/. Accessed 29 Sept 2023
Copernicus and Galileo: boosting their integration and synergies around the world. https://www.copernicus.eu/en/news/news/observer-copernicus-and-galileo-boosting-their-integration-and-synergies-around-world. Accessed 29 Sept 2023
Korançe, F.: The growing relation between environment and public health. SciMedicine J. 3(2), 100–115 (2021)
Ramis Ferrer, B., et al.: Comparing ontologies and databases: a critical review of lifecycle engineering models in manufacturing. Knowl. Inf. Syst. 63(6), 1271–1304 (2021). https://doi.org/10.1007/s10115-021-01558-4
Rosenberg, J. et al.: Leveraging ElasticSearch to improve data discoverability in science gateways. In: Practice & Experience in Advanced Research Computing, pp. 1–5 (2019)
Novakovsky, G., et al.: Obtaining genetics insights from deep learning via explainable artificial intelligence. Nat. Rev. Genet. 24(2), 125–137 (2023)
Bokulich, A., Parker, W.: Data models, representation and adequacy-for-purpose. Eur. J. Philos. Sci. 11(1), 1–26 (2021)
Data Scientist: The Dirtiest Job of the 21st Century, https://towardsdatascience.com/data-scientist-the-dirtiest-job-of-the-21st-century-7f0c8215e845, last accessed 2023/09/29
Spiekermann, M.: Data marketplaces: trends and monetisation of data goods. Intereconomics 54(4), 208–216 (2019)
Data sharing challenges. https://www.datarepublic.com/resources/resources-guides/the-most-common-challenges-of-data-sharing. Accessed 29 Sept 2023
Angela, G.: Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits of Data Re-use Across Societies. OECD Publishing, Tokyo (2019)
Lu, J.L.: Correlation of climate change indicators with health and environmental data in the Philippines. Acta Medica Philippina 56(1) (2021)
Anderegg, W.R., et al.: Climate-driven risks to the climate mitigation potential of forests. Science 368(6497), eaaz7005 (2020)
Došilović, F.K., et al.: Explainable artificial intelligence: a survey. In: 41st International Convention on Information & Communication Technology, pp. 210–215 (2018)
Copernicus. https://www.copernicus.eu/en. Accessed 29 Sept 2023
Nasa Earth Observatory. https://earthobservatory.nasa.gov/. Accessed 29 Sept 2023
Copernicus: Data and Information Access Services. https://www.copernicus.eu/en/access-data/dias. Accessed 29 Sept 2023
A European Green Deal. https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal_en. Accessed 29 Sept 2023
OpenRefine. https://openrefine.org/. Accessed 29 Sept 2023
Faroukhi, A.Z., et al.: An adaptable big data value chain framework for end-to-end big data monetization. Big Data Cogn. Comput. 4(4), 34 (2020)
Barcelos, A.M.F.: Researching beliefs about SLA: a critical review. Beliefs about SLA: New research approaches, 7–33 (2003)
Knowage. https://www.knowage-suite.com/site/. Accessed 29 Sept 2023
Zhang, J., et al.: DRNet: a deep neural network with multi-layer residual blocks improves image denoising. IEEE Access 9, 79936–79946 (2020)
Mavrogiorgou, A., et al.: A comparative study of ML algorithms for scenario-agnostic predictions in healthcare. In: IEEE Symposium on Computers and Communications (ISCC), pp. 1–7 (2022)
Kaveh, A., et al.: Efficient training of two ANNs using four meta-heuristic algorithms for predicting the FRP strength. In Structures 52, 256–272 (2023)
Mosca, E., et al.: SHAP-based explanation methods: a review for NLP interpretability. In: Proceedings of the International Conference on Computational Linguistics, pp. 4593–4603 (2022)
Zhang, H.: Structural equation modeling. In: Models and Methods for Management Science, pp. 363–381 (2022)
Gomez, R., et al.: Confirmatory factor analysis and exploratory structural equation modeling of the factor structure of the questionnaire of Cognitive and Affective Empathy (QCAE). PLoS ONE 17(2), e0261914 (2022)
Saad, M., Zhang, Y., Tian, J., Jia, J.: A graph database for life cycle inventory using Neo4j. J. Clean. Prod. 393, 136344 (2023)
Hadaj, P., Strzałka, D., Nowak, M., Łatka, M., Dymora, P.: The use of PLANS and NetworkX in modeling power grid system failures. Sci. Rep. 12(1), 17445 (2022)
Kleftakis, S., et al.: Digital twin in healthcare through the eyes of the Vitruvian man. In: Innovation in Medicine and Healthcare: Proceedings of 10th KES-InMed, pp. 75–85 (2022)
Kyriazis, D., et al.: The CrowdHEALTH project and the hollistic health records: collective wisdom driving public health policies. Acta Informatica Medica 27(5), 369 (2019)
Koumaditis, K., Themistocleous, M., Vassilacopoulos, G.: ‘PINCLOUD: Integrated E-Health Services Over the Cloud’ SUCRE 2014
Kiourtis, A., et al.: Electronic health records at people’s hands across Europe: the InteropEHRate Protocols. In: pHealth 2022, pp. 145–150 (2022)
Mavrogiorgou, A., Kiourtis, A., Touloupou, M., Kapassa, E., Kyriazis, D., Themistocleous, M.: The road to the future of healthcare: transmitting interoperable healthcare data through a 5G based communication platform. In: Themistocleous, M., Rupino da Cunha, P. (eds.) EMCIS 2018. LNBIP, vol. 341, pp. 383–401. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-11395-7_30
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The SmartCHANGE project has received funding from the Horizon Europe R&I programme under the GA No. 101080965.
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Kiourtis, A., Mavrogiorgou, A., Kyriazis, D. (2024). Α Cross-Sector Data Space for Correlating Environmental Risks with Human Health. In: Papadaki, M., Themistocleous, M., Al Marri, K., Al Zarouni, M. (eds) Information Systems. EMCIS 2023. Lecture Notes in Business Information Processing, vol 501. Springer, Cham. https://doi.org/10.1007/978-3-031-56478-9_17
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