# data modeling

> (in software engineering) process of creating a data model for an information system by applying certain formal techniques

**Wikidata**: [Q367664](https://www.wikidata.org/wiki/Q367664)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Data_modeling)  
**Source**: https://4ort.xyz/entity/data-modeling

## Summary  
Data modeling is the process of creating a data model for an information system by applying formal techniques, primarily within software engineering. It defines how data is structured, stored, and accessed. This practice ensures consistency, accuracy, and usability across systems.

## Key Facts  
- Data modeling falls under the broader categories of **scientific modeling** and **data governance**.  
- It produces **data models**, which define structures and relationships among data elements.  
- Related disciplines include **dimensional modeling**, **UML modeling**, and **data hierarchy**.  
- Tools like **GNU Ferret** support data modeling workflows.  
- Notable figures in the field include **Terry Halpin** (Australian computer scientist) and **Rafael Goncalves** (Senior Semantic Web Engineer).  
- The ACM classification code for data modeling is **10010112**.  
- Aliases include **data modelling** (British English), **modelado de datos** (Spanish), and **modelling**.  

## FAQs  
### Q: What is data modeling used for?  
A: Data modeling is used to define and structure data within information systems, ensuring clarity, consistency, and efficient access. It supports database design, integration, and governance.

### Q: Who uses data modeling?  
A: Software engineers, data architects, database designers, and IT professionals use data modeling to build reliable and scalable systems.

### Q: How does data modeling relate to data governance?  
A: Data modeling is a component of data governance, helping enforce standards and policies that ensure high-quality, consistent data across an organization.

## Why It Matters  
Data modeling plays a critical role in software development and data management by providing a blueprint for how data will be organized and used. It reduces ambiguity, prevents data redundancy, and improves interoperability between systems. By establishing clear rules and relationships early in the design phase, data modeling helps avoid costly errors during implementation. In enterprise environments, it supports compliance, scalability, and decision-making through well-defined data architectures.

## Notable For  
- Formalizing the structure and semantics of data in information systems  
- Being foundational to both relational database design and data warehouse architecture  
- Supporting multiple modeling paradigms including dimensional and UML approaches  
- Enabling cross-disciplinary collaboration between business stakeholders and technical teams  

## Body  
### Definition and Scope  
Data modeling is defined as the process of creating a data model for an information system using formal techniques. It is primarily applied in software engineering but also intersects with data science, business analysis, and enterprise architecture.

### Classifications and Relationships  
Data modeling is classified as a subclass of:
- **Scientific modeling**
- **Data governance**

It is closely related to:
- **Dimensional modeling**: Used in data warehousing
- **UML modeling**: Visual representation of software systems
- **Data hierarchy**: Organizes data into nested levels

### Outputs and Applications  
The primary output of data modeling is a **data model**, which specifies:
- Entities and their attributes
- Relationships between entities
- Constraints and rules governing data behavior

These models guide the implementation of databases, APIs, and data integration platforms.

### Tools and Practitioners  
Tools such as **GNU Ferret** assist practitioners in visualizing and validating data models. Prominent contributors to the field include:
- **Terry Halpin**, known for his work in conceptual modeling and ORM (Object-Role Modeling)
- **Rafael Goncalves**, involved in semantic web technologies and data interoperability

### Standards and Identifiers  
Several identifiers reference data modeling across knowledge bases:
- **ACM Classification Code (2012)**: 10010112
- **ESCO Skill ID**: fbafa41f-cd05-4109-a649-8b44d306d779
- **UNBIS Thesaurus ID**: 1001500
- **Zhihu Topic ID**: 19658196 ("数据建模")
- **Freebase ID**: /m/038_nf

Multiple Wikipedia editions cover the topic, including languages such as English, French, German, Spanish, and Chinese.

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## References

1. Freebase Data Dumps. 2013
2. Quora
3. [OpenAlex](https://docs.openalex.org/download-snapshot/snapshot-data-format)