CNL-ER: A Controlled Natural Language for Specifying and Verbalising Entity Relationship Models

The first step towards designing an information system is conceptual modelling where domain experts and knowledge engineers identify the necessary information together to build an information system. Entity relationship modelling is one of the most popular conceptual modelling techniques that represents an information system in terms of entities, attributes and relationships. Entity relationship models are constructed graphically but are often difficult to understand by domain experts. To overcome this problem, we suggest to verbalise these models in a controlled natural language. In this paper, we present CNL-ER, a controlled natural language for specifying and verbalising entity relationship (ER) models that not only solves the verbalisation problem for these models but also provides the benefits of automatic verification and validation, and semantic round-tripping which makes the communication process transparent between the domain experts and the knowledge engineers.

[1]  Terry Halpin,et al.  ORM/NIAM Object-Role Modeling , 1998 .

[2]  Robert J. Gaizauskas,et al.  CM-Builder: A Natural Language-Based CASE Tool for Object-Oriented Analysis , 2003, Automated Software Engineering.

[3]  Stuart M. Shieber,et al.  Prolog and Natural-Language Analysis , 1987 .

[4]  Qing Li,et al.  Entity-Relationship Diagram , 2009 .

[5]  Diego Calvanese,et al.  Reasoning on UML class diagrams , 2005, Artif. Intell..

[6]  Richard Barker,et al.  CASE method - entity relationship modelling , 1990, Computer aided systems engineering.

[7]  Rolf Schwitter,et al.  Controlled Natural Languages for Knowledge Representation , 2010, COLING.

[8]  Domenico Lembo,et al.  Eddy: A Graphical Editor for OWL 2 Ontologies , 2016, IJCAI.

[9]  Vincenzo Gervasi,et al.  On the Systematic Analysis of Natural Language Requirements with CIRCE , 2006, Automated Software Engineering.

[10]  Rodina Ahmad,et al.  Class Diagram Extraction from Textual Requirements Using Natural Language Processing (NLP) Techniques , 2010, 2010 Second International Conference on Computer Research and Development.

[11]  Rolf Schwitter,et al.  Specifying Conceptual Models Using Restricted Natural Language , 2018, ALTA.

[12]  Il-Yeol Song,et al.  Entity Relationship Model , 2018, Encyclopedia of Database Systems.

[13]  Domenico Lembo,et al.  Easy OWL Drawing with the Graphol Visual Ontology Language , 2016, KR.

[14]  C. Maria Keet,et al.  Multilingual verbalization of ORM conceptual models and axiomatized ontologies , 2014 .

[15]  Joseph J. FrantiskaJr..  Entity-Relationship Diagrams , 2018 .

[16]  Enrico Franconi,et al.  ORM2: Formalisation and Encoding in OWL2 , 2012, OTM Workshops.

[17]  Sergio Tessaris,et al.  The ICOM 3.0 intelligent conceptual modelling tool and methodology , 2012, Semantic Web.

[18]  Gerard O’Regan,et al.  Unified Modelling Language , 2014 .

[19]  Alexander Borgida,et al.  Conceptual Modeling of Information Systems , 1985, On Knowledge Base Management Systems.

[20]  Adrian Paschke,et al.  RuleML 1.0: The Overarching Specification of Web Rules , 2010, RuleML.

[21]  Harald Störrle.  How are Conceptual Models used in Industrial Software Development? A Descriptive Survey , 2019, SE/SWM.

[22]  Terry A. Halpin.  Object-Role Modeling , 2018, Encyclopedia of Database Systems.

[23]  Luisa Mich,et al.  NL-OOPS: from natural language to object oriented requirements using the natural language processing system LOLITA , 1996, Natural Language Engineering.

[24]  David T. Bourgeois.  Information Systems for Business and Beyond , 2014 .

[25]  Kenneth C. Laudon,et al.  Management Information Systems: Managing the Digital Firm Plus MyMISLab with Pearson eText -- Access Card Package , 2015 .

[26]  M. Saeki,et al.  Software Development Process From Natural Language Specification , 1989, 11th International Conference on Software Engineering.

[27]  Carsten Lutz,et al.  Reasoning about Entity Relationship Diagrams with Complex Attribute Dependencies , 2002, Description Logics.