Health information systems: proposal of a provenance data management method in the instantiation of the W3C PROV-DM model
DOI:
https://doi.org/10.47909/anis.978-9916-9760-3-6.10Keywords:
Health Information Systems, Data Provenance, Provenance Data Management, W3C PROV-DM, MethodAbstract
Health Information Systems (HIS) are being implemented in all aspects of health, from administration to clinical decision support systems. The generation and storage of large volumes of data in their decentralized repositories make these processes challenging when it comes to managing this data. The data provenance approaches in this regard help to answer questions such as: why? How? Where? When? by whom? And for what? The data were produced in the HIS, contributing to several benefits, especially in terms of traceability of the data of origin so that they can be managed within these systems. In this context, the present work is bibliographical research of qualitative nature based on the Provenance Data Model (PROV-DM) recommended by the World Wide Web Consortium (W3C), where we propose a method for management of provenance data in HIS. Considering the theme of this study, the research question presented here is: how to develop a method for the management of provenance data in HIS in the instantiation of the W3C PROV-DM model? An expected result is the development of a prototype to validate the method proposed here in a real health scenario, showing, in fact, the benefit of using the method.
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Belhajjame, K., B'Far, R., Cheney, J., Coppens, S., Cresswell, S., Gil, Y., Groth, P., Klyne, G., Lebo, T., McCusker, J., Miles, S., Myers, J., & Sahoo, S. (2013, April 30). PROV-DM: The PROV Data Model. W3C Recommendation. https://www.w3.org/TR/prov-dm/
Chiasson, M. W., & Davidson, E. (2004). Pushing the contextual envelope: developing and diffusing is theory for health information systems research. Information And Organization, 14(3), 155-188. http://dx.doi.org/10.1016/j.infoandorg.2004.02.001
Davidson, S. B., & Freire, J. (2008) Provenance and scientific workflows: challenges and opportunities. In ACM Sigmod International Conference On Management Of Data, Vancouver. https://vgc.poly.edu/~juliana/pub/freire-tutorial-sigmod2008.pdf
Ferreira, J. E. de S. M., Oliveira, L. R. de, Marques, W. S., Lima, T. S. de, Barbosa, E. da S., Castro, R. R., & Guimarães, J. M. X. (2020). Sistemas de Informação em Saúde no apoio à gestão da Atenção Primária à Saúde: revisão integrativa. Revista Eletrônica de Comunicação, Informação e Inovação em Saúde, 14(4), 970-982. http://dx.doi.org/10.29397/reciis.v14i4.1923
Freire, J., Koop, D., Santos, E., & Silva, C. T. (2008). Provenance for computational tasks: a survey. Journal Computing in Science and Engineering, 10(3), 11-21. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.147.3801&rep=rep1&type=pdf
Freund, G. P., Sembay, M. J., & Macedo, D. D. J. (2019). Proveniência de Dados e Segurança da Informação: relações interdisciplinares no domínio da ciência da informação. Revista Ibero-Americana de Ciência da Informação, 12(3), 807-825. https://doi.org/10.26512/rici.v12.n3.2019.21203
Garcia, P. T., & Reis, R. S. (2016). Gestão Pública em Saúde: sistemas de informação de apoio à gestão em saúde. UFMA.
Groth, P., & Moreau, L. (2013). PROV-Overview: an overview of the prov family of documents. https://www.w3.org/TR/prov-overview/
Moreau, L., Groth, P., Cheney, J., Lebo, T., & Miles, S. (2015). The rationale of PROV. Journal of Web Semantics, 35, 235-257. https://doi.org/10.1016/j.websem.2015.04.001
Sembay, M. J., Macedo, D. J., & Dutra, M. L. A. (2020a) Method for collecting provenance data: a case study in a Brazilian hemotherapy center. In Lecture Notes of the Institute for Computer Sciences, Social InformaTIC and Telecommunications Engineering. 1. ed. (pp. 89-102). Springer International Publishing. Doi 10.1007/978-3-030-50072-6_8
Sembay, M. J., Macedo, D. J., & Dutra, M. L. (2020b). A proposed approach for provenance data gathering. In Mobile Networks & Applications, (pp. 1-13). https://doi.org/10.1007/s11036-020-01648-7
Simmhan, Y., Plale, B., & Gannon, D. (2006). A framework for collecting provenance in data-centric scientific workflows. Proceedings International Conference On Web Services, ICWS’06, Chicago, EUA, Doi 10.1109/ICWS.2006.5
Tan, W. C. (2008). Provenance in databases: past, current, and future. IEEE Data Eng. Bull, 30(4), 3-12, 2008.
W3C (2013). PROV-DM: The PROV Data Model. W3C. http://www.w3.org/TR/prov-dm/
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