# ontology-based data access

> range of semantic techniques, algorithms and systems developed to facilitate access to various types of data sources

**Wikidata**: [Q55118556](https://www.wikidata.org/wiki/Q55118556)  
**Source**: https://4ort.xyz/entity/ontology-based-data-access

## Summary
Ontology-based data access (OBDA) is a collection of semantic techniques, algorithms, and systems designed to facilitate access to various data sources. It is an approach to data integration that allows users to query underlying data, such as relational databases, as a unified virtual knowledge graph (VKG) without physically moving or transforming the data.

## Key Facts
- **Classification:** A subclass of ontology-based data integration and knowledge graph population.
- **Aliases:** Also known as OBDA, virtual knowledge graph (VKG), and RDBMS virtualization.
- **Primary Function:** To provide unified access to various types of data sources using semantic techniques.
- **Implementations:** Used by platforms including ontop, Virtuoso Universal Server, and Ontotext GraphDB.
- **Example Use Case:** The ontop platform uses OBDA to enable querying of relational databases as Virtual RDF Knowledge Graphs via the SPARQL query language.

## FAQs
### Q: What is the main goal of ontology-based data access?
A: The main goal of OBDA is to simplify and unify access to diverse, separate data sources. It creates a virtual, conceptual layer (an ontology) over the existing data, allowing users to query it as a single, coherent knowledge graph.

### Q: What are some other names for ontology-based data access?
A: Ontology-based data access is also known by its acronym, OBDA. Other common terms for this approach include virtual knowledge graph (VKG) and RDBMS virtualization.

### Q: What kinds of systems use OBDA?
A: OBDA is implemented in various data management and knowledge graph platforms. Notable systems that use this approach include ontop, Virtuoso Universal Server, and Ontotext GraphDB.

## Why It Matters
Ontology-based data access (OBDA) is significant because it solves the critical challenge of querying data stored in separate, heterogeneous systems without requiring costly and complex data migration. Instead of physically consolidating data into a new database (a process known as ETL), OBDA creates a virtual semantic layer on top of the existing sources. This allows organizations to leverage their legacy relational databases while benefiting from the flexibility and powerful querying capabilities of knowledge graphs.

By using an ontology as a shared conceptual model, OBDA allows users to ask complex questions in a standardized way (e.g., using SPARQL) without needing to understand the intricate schemas of each underlying database. This democratizes data access, accelerates integration projects, and enables more agile data analytics. It effectively bridges the gap between the structured, tabular world of traditional databases and the interconnected, graph-based paradigm of the Semantic Web.

## Notable For
- **Data Virtualization:** Provides access to data sources as a unified Virtual Knowledge Graph (VKG) without physically moving or duplicating the original data.
- **Semantic Abstraction:** Uses an ontology to create a high-level, business-friendly view of data, hiding the complexity of the underlying database schemas.
- **Standardized Querying:** Enables the use of standard graph query languages, like SPARQL, to access data stored in non-graph formats, such as relational databases.
- **Industry Adoption:** Implemented in several major data platforms, including ontop, Virtuoso Universal Server, and Ontotext GraphDB, demonstrating its practical utility.

## Body
### Definition and Classification
Ontology-based data access (OBDA) refers to a range of semantic techniques, algorithms, and systems developed to facilitate access to various types of data sources. It is formally classified as a subclass of `ontology-based data integration` and `knowledge graph population`. This approach uses an ontology to provide a conceptual representation of a domain, which acts as a mediating layer for querying underlying data stores.

### Terminology
The approach is known by several names, which often highlight different aspects of the technology:
- **OBDA:** The most common acronym for the approach.
- **Virtual Knowledge Graph (VKG):** Emphasizes that the knowledge graph is created on-the-fly and does not require physical data storage.
- **RDBMS Virtualization:** Highlights its common application of creating a virtual graph layer over traditional Relational Database Management Systems.

### Implementations and Use
OBDA is not just a theoretical concept but is implemented in several widely-used data platforms.
- **Systems using OBDA:**
    - ontop
    - Virtuoso Universal Server
    - Ontotext GraphDB
- **Example: ontop**
    - The ontop platform is a prominent example of an OBDA system. It is specifically designed to query relational databases as Virtual RDF Knowledge Graphs. Users can interact with the relational data by writing SPARQL queries against the ontology, and ontop translates these queries into SQL to retrieve the answers directly from the source database.