Conceptual Data Modeling: Entity-Relationship Models as Thinging Machines
Sabah Al-Fedaghi

TL;DR
This paper explores enhancing entity-relationship data models by applying a new 'thinging machine' methodology to add processing, ontological clarity, and temporal concepts, aiming to deepen understanding and expressiveness.
Contribution
It introduces a novel application of the thinging machine model to ER, integrating processing actions, ontological elements, and temporal notions into data modeling.
Findings
Enhanced ER models with processing capabilities
Clearer ontological representation of entities and relationships
Inclusion of time-oriented concepts like events
Abstract
Data modeling is a process of developing a model to design and develop a data system that supports an organization s various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims at providing richer expressiveness and incorporating a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate viewing of connections and ideas on a database. The described structure of the data is often represented in an entity-relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes and relationships. This paper is an attempt to examine the basic ER modeling notions to analyze the concepts to which they refer…
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Taxonomy
TopicsData Quality and Management · Service-Oriented Architecture and Web Services · Semantic Web and Ontologies
