{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:37:15Z","timestamp":1742935035359,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031657931"},{"type":"electronic","value":"9783031657948"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T00:00:00Z","timestamp":1723680000000},"content-version":"vor","delay-in-days":227,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper first presents DANKE, a data and knowledge management platform that allows users to submit keyword queries to a centralized database. DANKE uses a knowledge graph to provide a semantic view of the centralized database in a vocabulary familiar to the users. The paper then describes DANKE-U, a specialized module that enables DANKE to handle unstructured data, including scientific and engineering documents. Lastly, the paper presents a real use case from the oil and gas industry, involving technical\/scientific documents.<\/jats:p>","DOI":"10.1007\/978-3-031-65794-8_9","type":"book-chapter","created":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T06:02:44Z","timestamp":1723615364000},"page":"134-146","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Technical\/Scientific Document Management Platform"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1723-9897","authenticated-orcid":false,"given":"Melissa","family":"Lemos","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9713-300X","authenticated-orcid":false,"given":"Grettel M.","family":"Garc\u00eda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0971-8572","authenticated-orcid":false,"given":"Yenier T.","family":"Izquierdo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cleber","family":"Oliveira","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jefferson Alves","family":"de Sousa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernardo Florindo Mortari","family":"Rezende","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruno","family":"Novelli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0765-9636","authenticated-orcid":false,"given":"Marco A.","family":"Casanova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,15]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.is.2015.07.005","volume":"55","author":"S Bergamaschi","year":"2016","unstructured":"Bergamaschi, S., Guerra, F., Interlandi, M., Trillo-Lado, R., Velegrakis, Y.: Combining user and database perspective for solving keyword queries over relational databases. Inf. Syst. 55, 1\u201319 (2016). https:\/\/doi.org\/10.1016\/j.is.2015.07.005","journal-title":"Inf. Syst."},{"issue":"3","key":"9_CR2","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1109\/TPAMI.2013.142","volume":"36","author":"J Costa Pereira","year":"2014","unstructured":"Costa Pereira, J., et al.: On the role of correlation and abstraction in cross-modal multimedia retrieval. Trans. Pattern Anal. Mach. Intell. 36(3), 521\u2013535 (2014). https:\/\/doi.org\/10.1109\/TPAMI.2013.142","journal-title":"Trans. Pattern Anal. Mach. Intell."},{"key":"9_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/C2011-0-06130-6","volume-title":"Principles of Data Integration","author":"A Doan","year":"2012","unstructured":"Doan, A., Halevy, A.Y., Ives, Z.G.: Principles of Data Integration, 1st edn. Morgan Kaufmann, San Francisco (2012). https:\/\/doi.org\/10.1016\/C2011-0-06130-6","edition":"1"},{"key":"9_CR4","doi-asserted-by":"publisher","unstructured":"Dong, X.L., Rekatsinas, T.: Data integration and machine learning: a natural synergy. In: Proceedings of the 2018 International Conference on Management of Data. p. 1645-1650. SIGMOD 2018, Association for Computing Machinery, New York, NY, USA (2018). https:\/\/doi.org\/10.1145\/3183713.3197387","DOI":"10.1145\/3183713.3197387"},{"key":"9_CR5","doi-asserted-by":"publisher","unstructured":"Dong, X.L., Srivastava, D.: Big data integration. In: 2013 IEEE 29th International Conference on Data Engineering (ICDE), pp. 1245\u20131248 (2013). https:\/\/doi.org\/10.1109\/ICDE.2013.6544914","DOI":"10.1109\/ICDE.2013.6544914"},{"issue":"4","key":"9_CR6","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1016\/j.compind.2013.01.002","volume":"64","author":"DB Esp\u00edndola","year":"2013","unstructured":"Esp\u00edndola, D.B., Fumagalli, L., Garetti, M., Pereira, C.E., Botelho, S.S., Ventura Henriques, R.: A model-based approach for data integration to improve maintenance management by mixed reality. Comput. Ind. 64(4), 376\u2013391 (2013). https:\/\/doi.org\/10.1016\/j.compind.2013.01.002","journal-title":"Comput. Ind."},{"key":"9_CR7","unstructured":"Garc\u00eda, 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)"},{"key":"9_CR8","doi-asserted-by":"publisher","unstructured":"Garc\u00eda, G.M., Izquierdo, Y.T., Menendez, E., Dartayre, F., Casanova, M.A.: RDF keyword-based query technology meets a real-world dataset. In: Proceedings of the International Conference on Extending Database Technology, pp. 656\u2013667. OpenProceedings.org (2017). https:\/\/doi.org\/10.5441\/002\/edbt.2017.86","DOI":"10.5441\/002\/edbt.2017.86"},{"issue":"1","key":"9_CR9","doi-asserted-by":"publisher","first-page":"1927469","DOI":"10.1080\/23311916.2021.1927469","volume":"8","author":"IM Hameed","year":"2021","unstructured":"Hameed, I.M., Abdulhussain, S.H., Mahmmod, B.M.: Content-based image retrieval: a review of recent trends. Cogent Eng. 8(1), 1927469 (2021). https:\/\/doi.org\/10.1080\/23311916.2021.1927469","journal-title":"Cogent Eng."},{"key":"9_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1007\/978-3-319-98812-2_22","volume-title":"Database and Expert Systems Applications","author":"YT Izquierdo","year":"2018","unstructured":"Izquierdo, Y.T., Garc\u00eda, G.M., Menendez, E.S., Casanova, M.A., Dartayre, F., Levy, C.H.: QUIOW: a keyword-based query processing tool for RDF datasets and relational databases. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R.R. (eds.) DEXA 2018. LNCS, vol. 11030, pp. 259\u2013269. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98812-2_22"},{"key":"9_CR11","doi-asserted-by":"publisher","first-page":"101814","DOI":"10.1016\/j.is.2021.101814","volume":"102","author":"YT Izquierdo","year":"2021","unstructured":"Izquierdo, Y.T., et al.: Keyword search over schema-less RDF datasets by SPARQL query compilation. Inf. Syst. 102, 101814 (2021). https:\/\/doi.org\/10.1016\/j.is.2021.101814","journal-title":"Inf. Syst."},{"key":"9_CR12","doi-asserted-by":"publisher","unstructured":"Izquierdo, Y.T., et al.: A platform for keyword search and its application for covid-19 pandemic data. J. Inf. Data Manage. 12(5) (2021). https:\/\/doi.org\/10.5753\/jidm.2021.1904, https:\/\/sol.sbc.org.br\/journals\/index.php\/jidm\/article\/view\/1904","DOI":"10.5753\/jidm.2021.1904"},{"key":"9_CR13","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1016\/j.neucom.2020.07.139","volume":"452","author":"X Li","year":"2021","unstructured":"Li, X., Yang, J., Ma, J.: Recent developments of content-based image retrieval (CBIR). Neurocomputing 452, 675\u2013689 (2021). https:\/\/doi.org\/10.1016\/j.neucom.2020.07.139","journal-title":"Neurocomputing"},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Nascimento, E.R., et al.: Text-to-SQL meets the real-world. In: (Accepted to the 26th International Conference on Enterprise Information System) (2024)","DOI":"10.5220\/0012555200003690"},{"key":"9_CR15","unstructured":"Nascimento, E.R., et al.: A family of natural language interfaces for databases based on chatGPT and langchain (short paper). In: Companion Proceedings of the 42nd International Conference on Conceptual Modeling: Posters and Demos co-located with ER 2023, Lisbon, Portugal, November 06-09, 2023. CEUR Workshop Proceedings, vol.\u00a03618 (2023). https:\/\/ceur-ws.org\/Vol-3618\/pd_paper_1.pdf"},{"key":"9_CR16","doi-asserted-by":"crossref","unstructured":"Nascimento, E.R., et al.: My database user is a large language model. In: (Accepted to the 26th International Conference on Enterprise Information System) (2024)","DOI":"10.5220\/0012697700003690"},{"key":"9_CR17","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.renene.2013.05.002","volume":"60","author":"TH Nguyen","year":"2013","unstructured":"Nguyen, T.H., Prinz, A., Friis\u0151, T., Nossum, R., Tyapin, I.: A framework for data integration of offshore wind farms. Renew. Energy 60, 150\u2013161 (2013). https:\/\/doi.org\/10.1016\/j.renene.2013.05.002","journal-title":"Renew. Energy"},{"key":"9_CR18","doi-asserted-by":"publisher","unstructured":"de\u00a0Oliveira, P., da\u00a0Silva, A., de\u00a0Moura, E.: Ranking candidate networks of relations to improve keyword search over relational databases. In: 2015 IEEE 31st International Conference on Data Engineering, pp. 399\u2013410 (2015). https:\/\/doi.org\/10.1109\/ICDE.2015.7113301","DOI":"10.1109\/ICDE.2015.7113301"},{"key":"9_CR19","doi-asserted-by":"publisher","first-page":"101460","DOI":"10.1016\/j.is.2019.101460","volume":"88","author":"MS Ramada","year":"2020","unstructured":"Ramada, M.S., Silva, J.C., Leit\u00e3o-J\u00fanior, P.S.: From keywords to relational database content: a semantic mapping method. Inf. Syst. 88, 101460 (2020). https:\/\/doi.org\/10.1016\/j.is.2019.101460","journal-title":"Inf. Syst."},{"key":"9_CR20","unstructured":"Stonebraker, M., Ilyas, I.F.: Data integration: the current status and the way forward. IEEE Data Eng. Bull. 41, 3\u20139 (2018). https:\/\/api.semanticscholar.org\/CorpusID:49407081"},{"key":"9_CR21","doi-asserted-by":"publisher","first-page":"84613","DOI":"10.1109\/ACCESS.2019.2923552","volume":"7","author":"I Tautkute","year":"2019","unstructured":"Tautkute, I., Trzci\u0144ski, T., Skorupa, A.P., Brocki, \u0141, Marasek, K.: Deepstyle: multimodal search engine for fashion and interior design. IEEE Access 7, 84613\u201384628 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2923552","journal-title":"IEEE Access"},{"key":"9_CR22","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.jmsy.2018.02.002","volume":"48","author":"PD Urbina Coronado","year":"2018","unstructured":"Urbina Coronado, P.D., Lynn, R., Louhichi, W., Parto, M., Wescoat, E., Kurfess, T.: Part data integration in the shop floor digital twin: mobile and cloud technologies to enable a manufacturing execution system. J. Manuf. Syst. 48, 25\u201333 (2018). https:\/\/doi.org\/10.1016\/j.jmsy.2018.02.002. special Issue on Smart Manufacturing","journal-title":"J. Manuf. Syst."},{"key":"9_CR23","doi-asserted-by":"publisher","unstructured":"Vo, N., Jiang, L., Sun, C., Murphy, K., Li, L.J., Fei-Fei, L., Hays, J.: Composing text and image for image retrieval-an empirical odyssey. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6439\u20136448 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00660","DOI":"10.1109\/CVPR.2019.00660"},{"key":"9_CR24","doi-asserted-by":"publisher","unstructured":"Yu, L., et al.: Commercemm: large-scale commerce multimodal representation learning with omni retrieval. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 4433\u20134442 (2022). https:\/\/doi.org\/10.1145\/3534678.3539151","DOI":"10.1145\/3534678.3539151"},{"issue":"3","key":"9_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3387164","volume":"16","author":"D Zeng","year":"2020","unstructured":"Zeng, D., Yu, Y., Oyama, K.: Deep triplet neural networks with cluster-cca for audio-visual cross-modal retrieval. ACM Trans. Multimedia Comput. Commun. Appl. 16(3), 1\u201323 (2020). https:\/\/doi.org\/10.1145\/3387164","journal-title":"ACM Trans. Multimedia Comput. Commun. Appl."}],"container-title":["Lecture Notes in Computer Science","Natural Scientific Language Processing and Research Knowledge Graphs"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-65794-8_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T06:04:20Z","timestamp":1723615460000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-65794-8_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031657931","9783031657948"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-65794-8_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"15 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NSLP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Natural Scientific Language Processing and Research Knowledge Graphs","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hersonissos, Crete","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 May 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 May 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nslp2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/nfdi4ds.github.io\/nslp2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}