A Platform for Keyword Search and its Application for COVID-19 Pandemic Data
DOI:
https://doi.org/10.5753/jidm.2021.1904Keywords:
COVID-19 data, Platform, Keyword search, SQLAbstract
Keyword search is typically associated with information retrieval systems. However, recently, keyword search has been expanded to relational databases and RDF datasets, as an attractive alternative to traditional database access. This paper introduces DANKE, a platform for keyword search over databases, and discusses how third-party applications can be equipped with DANKE to take advantage of a data retrieval mechanism that does not require users to have specific technical skills for searching, retrieving and exploring data. The paper ends with the description of an application, called CovidKeyS, which uses DANKE to implement keyword search over three COVID-19 data scenarios.
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References
Bast, H., Björn, B., and Haussmann, E. Semantic search on text and knowledge bases. Foundations and Trends in Information Retrieval 10 (2-3): 119–271, 2016.
Bergamaschi, S., Guerra, F., Interlandi, M., Trillo-Lado, R., and Velegrakis, Y. Combining user and database perspective for solving keyword queries over relational databases. Information Systems vol. 55, pp. 1–19, 2016.
Dong, E., Du, H., and Gardner, L. An interactive web-based dashboard to track covid-19 in real time. The Lancet infectious diseases 20 (5): 533–534, 2020.
Dosso, D. and Silvello, G. Search text to retrieve graphs: A scalable rdf keyword-based search system. IEEE Access vol. 8, pp. 14089–14111, 2020.
Garcia, G. M. A Keyword-based Query Processing Method for Datasets with Schemas. Ph.D. thesis, Thesis presented to the Graduate Program in Informatics, PUC-Rio, 2020.
García, G. M., Izquierdo, Y. T., Menendez, E., Dartayre, F., and Casanova, M. A. Rdf keyword-based query technology meets a real-world dataset. In Proceedings of the International Conference on Extending Database Technology. OpenProceedings.org, pp. 656–667, 2017.
Gkirtzou, K., Karozos, K., Vassalos, V., and Dalamagas, T. Keywords-to-sparql translation for rdf data search and exploration. In International Conference on Theory and Practice of Digital Libraries. Springer, pp. 111–123, 2015.
Han, S., Zou, L., Yu, J. X., and Zhao, D. Keyword search on rdf graphs-a query graph assembly approach. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (CIKM). ACM, pp. 227–236, 2017.
Izquierdo, Y. T., Casanova, M. A., García, G., Dartayre, F., and Levy, C. H. Keyword search over federated rdf datasets. In ER Forum 2017 and ER Demo track co-located with the 36th Int. Conf. on Conceptual Modeling. CEUR-WS.org, pp. 86–99, 2017.
Izquierdo, Y. T., García, G. M., Lemos, M., Novello, A., Novelli, B., Damasceno, C., Leme, L. A. P., and Casanova, M. A. Keyword search over covid-19 data. In 35th Edition of the Brazilian Symposium on Databases. Journal of the Brazilian Computer Society (JBCS), pp. 205–210, 2020.
Izquierdo, Y. T., García, G. M., Menendez, E. S., Casanova, M. A., Dartayre, F., and Levy, C. H. Quiow: a keyword-based query processing tool for rdf datasets and relational databases. In International Conference on Database and Expert Systems Applications (DEXA). Springer, pp. 259–269, 2018.
Luo, Y., Qin, X., Tang, N., and Li, G. Deepeye: Towards automatic data visualization. 2018 IEEE 34th International Conference on Data Engineering (ICDE) vol. DOI: 10.1109/ICDE.2018.00019, pp. 101–112, 2018.
Mello, L. E., Suman, A., Medeiros, C. B., Prado, C. A., Rizzatti, E. G., Nunes, F. L. S., Barnabé, G. F., Ferreira, J. E., Sá, J., Reis, L. F. L., Rizzo, L. V., Sarno, L., de Lamonica, R., Maciel, R. M. B., Cesar-Jr, R. M., and Carvalho, R. Opening Brazilian COVID-19 patient data to support world research on pandemics. DOI: 10.5281/zenodo.3966427, 2020.
Menendez, E. S., Casanova, M. A., Leme, L. A. P., and Boughanem, M. Novel node importance measures to improve keyword search over rdf graphs. In International Conference on Database and Expert Systems Applications. Springer, pp. 143–158, 2019.
Oliveira, P., Silva, A., and Moura, E. Ranking candidate networks of relations to improve keyword search over relational databases. In 31st International Conference on Data Engineering. IEEE, DOI: 10.1109/ICDE.2015.7113301, pp. 399–410, 2015.
Ramada, M. S., Silva, J. C., and Leitão-Júnior, P. S. From keywords to relational database content: A semantic mapping method. Information Systems vol. 88, pp. 101460, 2020.
Roser, M., Ritchie, H., Ortiz-Ospina, E., and Hasell, J. Coronavirus pandemic (covid-19). Our World in Data, 2020.
Tran, T., Wang, H., Rudolph, S., and Cimiano, P. Top-k exploration of query candidates for efficient keyword search on graph-shaped (rdf) data. In 25th International Conference on Data Engineering (ICDE). IEEE, pp. 405–416, 2009.
Vinay, M. S. and Haritsa, J. R. Operator implementation of result set dependent kws scoring functions. Information Systems vol. 88, pp. 11, 2020.
Zhou, Q., Wang, C., Xiong, M., Wang, H., and Yu, Y. Spark: adapting keyword query to semantic search. In Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC’07/ASWC’07). Springer, pp. 694–707, 2007.