Abstract
The need to store and manipulate large volume of (unstructured) data has led to the development of several NoSQL databases for better scalability. Graph databases are a particular kind of NoSQL databases that have proven their efficiency to store and query highly interconnected data, and have become a promising solution for multiple applications. While the mapping of conceptual schemas to relational databases is a well-studied field of research, there are only few solutions that target conceptual modeling for NoSQL databases and even less focusing on graph databases. This is specially true when dealing with the mapping of business rules and constraints in the conceptual schema. In this article we describe a mapping from UML/OCL conceptual schemas to Blueprints, an abstraction layer on top of a variety of graph databases, and Gremlin, a graph traversal language, via an intermediate Graph metamodel. Tool support is fully available.
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Notes
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Implementation list is available at https://github.com/tinkerpop/blueprints.
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References
Anand, M.K., Bowers, S., Ludäscher, B.: Techniques for efficiently querying scientific workflow provenance graphs. In: EDBT, vol. 10, pp. 287–298 (2010)
Benelallam, A., Gómez, A., Sunyé, G., Tisi, M., Launay, D.: Neo4EMF, a scalable persistence layer for EMF models. In: Cabot, J., Rubin, J. (eds.) ECMFA 2014. LNCS, vol. 8569, pp. 230–241. Springer, Heidelberg (2014). doi:10.1007/978-3-319-09195-2_15
Bettini, L.: Implementing Domain-Specific Languages with Xtext and Xtend. Packt Publishing Ltd., Birmingham (2013)
Brambilla, M., Cabot, J.: Constraint tuning and management for web applications. In: Proceedings of the 6th ICWE Conference, pp. 345–352. ACM (2006)
Bugiotti, F., Cabibbo, L., Atzeni, P., Torlone, R.: Database design for NoSQL systems. In: Yu, E., Dobbie, G., Jarke, M., Purao, S. (eds.) ER 2014. LNCS, vol. 8824, pp. 223–231. Springer, Heidelberg (2014). doi:10.1007/978-3-319-12206-9_18
Cabot, J., Teniente, E.: Incremental integrity checking of UML/OCL conceptual schemas. JSS 82(9), 1459–1478 (2009)
Chiang, R.H.L., Barron, T.M., Storey, V.C.: Reverse engineering of relational databases: extraction of an EER model from a relational database. Data Knowl. Eng. 12(2), 107–142 (1994)
Daniel, G., Sunyé, G., Cabot, J.: Mogwaï: a framework to handle complex queries on large models. In: Proceedings of the 10th RCIS Conference. IEEE (2016, to appear). http://tinyurl.com/zx6cfam
Demuth, B., Hussmann, H.: Using UML/OCL constraints for relational database design. In: France, R., Rumpe, B. (eds.) UML 1999. LNCS, vol. 1723, pp. 598–613. Springer, Heidelberg (1999). doi:10.1007/3-540-46852-8_42
Demuth, B., Hussmann, H., Loecher, S.: OCL as a specification language for business rules in database applications. In: Gogolla, M., Kobryn, C. (eds.) UML 2001. LNCS, vol. 2185, pp. 104–117. Springer, Heidelberg (2001). doi:10.1007/3-540-45441-1_9
Fan, W.: Graph pattern matching revised for social network analysis. In: Proceedings of the 15th ICDT, pp. 8–21. ACM (2012)
Hausenblas, M., Nadeau, J.: Apache drill: interactive ad-hoc analysis at scale. Big Data 1(2), 100–104 (2013)
Cánovas Izquierdo, J.L., Cabot, J.: Discovering implicit schemas in JSON Data. In: Daniel, F., Dolog, P., Li, Q. (eds.) ICWE 2013. LNCS, vol. 7977, pp. 68–83. Springer, Heidelberg (2013). doi:10.1007/978-3-642-39200-9_8
Jouault, F., Allilaire, F., Bézivin, J., Kurtev, I.: ATL: a model transformation tool. SCP 72(1–2), 31–39 (2008)
Jouault, F., Kurtev, I.: On the architectural alignment of ATL and QVT. In: Proceedings of the 21st SAC Conference, pp. 1188–1195. ACM (2006)
Lal, M.: Neo4j Graph Data Modeling. Packt Publishing Ltd., Birmingham (2015)
Leonard, A.: Pro Hibernate and MongoDB. Apress, Berkeley (2013)
Li, Y., Gu, P., Zhang, C.: Transforming UML class diagrams into HBase based on meta-model. In: Proceedings of the 4th ISEEE Conference, vol. 2, pp. 720–724. IEEE (2014)
Marcos, E., Vela, B., Cavero, J.M.: A methodological approach for object-relational database design using UML. SoSyM 2(1), 59–72 (2003)
Mior, M.J., Salem, K., Aboulnaga, A., Liu, R., NoSE: schema design for NoSQL applications. In: 32nd ICDE Conference. IEEE (2016, accepted). http://tinyurl.com/hqoxddx
Okman, L., Gal-Oz, N., Gonen, Y., Gudes, E., Abramov, J.: Security issues in NoSQL databases. In: Proceedings of the 10th TrustCom Conference, pp. 541–547. IEEE (2011)
OMG: MDA Specifications (2016). http://www.omg.org/mda/specs.htm
OMG: OCL Specification (2016). www.omg.org/spec/OCL
OMG: UML Specification (2016). www.omg.org/spec/UML
Sevilla Ruiz, D., Morales, S.F., García Molina, J.: Inferring versioned schemas from NoSQL databases and its applications. In: Johannesson, P., Lee, M.L., Liddle, S.W., Opdahl, A.L., López, Ó.P. (eds.) ER 2015. LNCS, vol. 9381, pp. 467–480. Springer, Heidelberg (2015). doi:10.1007/978-3-319-25264-3_35
TinkerPop: Blueprints API (2016). blueprints.tinkerpop.com
TinkerPop: The Gremlin Language (2016). gremlin.tinkerpop.com
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Daniel, G., Sunyé, G., Cabot, J. (2016). UMLtoGraphDB: Mapping Conceptual Schemas to Graph Databases. In: Comyn-Wattiau, I., Tanaka, K., Song, IY., Yamamoto, S., Saeki, M. (eds) Conceptual Modeling. ER 2016. Lecture Notes in Computer Science(), vol 9974. Springer, Cham. https://doi.org/10.1007/978-3-319-46397-1_33
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