Research ‐ Linked Data and SPARQL - bounswe/bounswe2024group8 GitHub Wiki

Linked Data

Linked data is a type of data used in web applications that is structured in such a way that it is readable by not only humans, but also computers.

In linked data, every single data entry has a URI, and is connected (linked) to URIs of other related data entries. The URIs follow the standard HTTP protocol, therefore the data can be retrieved using web browsers. In addition, contents of linked data should follow the RDF format, which is a standard model for data interchange on the Web.

Here are some advantages of linked data:

  1. As linked data provides a common standard for storing and linking data entries, it makes it possible for different systems and applications to integrate and exchange data easily.
  2. Because linked data defines relationships between different entities, it adds semantic meaning to data entries. This enhances data understanding (both by humans and by machines).
  3. Because of the distributed nature of the web, as more data sources start using linked data principles, the web of linked data continues to grow. Therefore, as time goes on, linked data provides more coverage of many different domains.
  4. By making data openly accessible and linkable on the web, linked data encourages transparency and collaboration.

In spite of all these advantages, implementing linked data is quite complex as it requires expertise in various semantic web technologies such as RDF and SPARQL.

SPARQL

SPARQL is a recursive acronym that stands for SPARQL Protocol and RDF Query Language. It provides a powerful tool for querying RDF datasets, which are used in linked data. The syntax of SPARQL resembles SQL, therefore learning to write expressive SPARQL queries is not very difficult if you are familiar with SQL.

Among many other features, some of the most powerful tools provided by SPARQL are:

  1. Pattern matching: Comparing patterns of literals, variables, and URIs against the data graph
  2. Filtering: Refining the results based on specific criteria such as value comparisons, regular expressions, logical conditions, etc.
  3. Aggregation: Efficiently running over many entries to perform operations such as summing, counting, averaging values etc.

Both linked data and SPARQL are crucial components of the Semantic Web (also known as Web 3.0), which is an extension of the World Wide Web through standards set by the World Wide Web Consortium.