Wikidata, Linked Data, SPARQL semantic queries, and Wikidata API

Introduction

This page is a combined research page about Wikidata, Linked Data, SPARQL semantic queries, and Wikidata API.

Wikidata

Overview:

Wikidata is a collaborative project that was launched by the Wikimedia Foundation in 2012. It aims to create a free and open database of structured data to support the work of Wikipedia and other Wikimedia projects, as well as to provide data for anyone in the world to use.

Structure:

The Wikidata repository primarily consists of items, each with a label, description, and aliases. Items are uniquely identified by a "Q" followed by a number. Statements within Wikidata provide detailed characteristics of an item and include a property (identified by a "P" followed by a number) and a corresponding value.

An example:

• Item: Q42
• Label: Douglas Adams
• Description: English writer and humorist
• Aliases: Douglas Noel Adams

Access and Tools:

In addition to providing data for Wikimedia projects, Wikidata also offers various tools and APIs that allow developers to access and use its data in their own projects. This includes tools for querying and exploring the data, as well as APIs for programmatically accessing and updating it. Accessing Wikidata can be done through built-in tools, external tools, or programming interfaces, providing various ways for users to interact with and utilize the data stored within the platform.

Linked Data

Overview:

Linked Data is a method of publishing structured data on the web, enhancing its utility through semantic queries and interlinking. It aligns with the principles of the Semantic Web proposed by Tim Berners-Lee, the inventor of the World Wide Web. The core idea is to create an interconnected network of data using standardized formats and protocols, enabling machines to comprehend and navigate data similarly to human interaction with traditional web documents.

Four Rules of Linked Data:

Sir Tim Berners-Lee established four design principles for Linked Data in 2006 to facilitate the linking, merging, and integration of extensive datasets from diverse sources:

1. Use URIs as names for things:

   • Utilize Uniform Resource Identifiers (URIs) globally to uniquely name digital content, real-world objects, or abstract concepts, distinguishing between different entities across datasets.

2. Use HTTP URIs for lookup:

   • Employ HTTP URIs to simplify resource retrieval, making identified items more accessible and contributing to the global data space.

3. Provide useful information when looking up a URI, using standards (RDF, SPARQL):

   • Use Resource Description Framework (RDF) for data representation and SPARQL for querying, ensuring efficient utilization of URIs and standardized information retrieval.

4. Include links to other URIs for discovery:

   • Enhance data interconnectedness by incorporating links to other URIs, maximizing reuse, and creating a richly interconnected network of machine-processable meaning, akin to the hypertext web.

SPARQL Semantic Queries

Overview:

SPARQL (SPARQL Protocol and RDF Query Language) serves as both a query language and protocol for manipulating data stored in RDF (Resource Description Framework) format—a directed, labeled graph data structure used for representing information on the Web.

Semantic Queries in SPARQL:

Semantic queries in SPARQL provide a distinctive approach to retrieving information from RDF data sources. Unlike conventional SQL queries that rely on data structure, semantic queries focus on the underlying meaning and semantics of the data.

Components of SPARQL Semantic Queries:

• Triple Patterns:

  • SPARQL's foundation lies in triple patterns, expressing relationships in RDF data through subject-predicate-object triples.

• Variables:

  • Variables, denoted by strings starting with a question mark (?), act as placeholders in SPARQL queries, enabling dynamic data retrieval.

• Graph Pattern:

  • Graph patterns expand SPARQL's capabilities, allowing the formulation of intricate query conditions.

• Query Forms:

  • SPARQL offers various query forms such as SELECT, CONSTRUCT, ASK, and DESCRIBE, tailored to diverse needs.

• Filters:

  • Filters in SPARQL queries refine results by applying conditions like variable bindings, comparisons, and regular expressions.

Executing Semantic Queries:

Executing SPARQL queries involves using SPARQL endpoints provided by RDF stores or triple stores. These endpoints accept queries as input and return results in formats like XML, JSON, or CSV.

Conclusion:

In conclusion, semantic queries in SPARQL present a powerful means of querying RDF data, focusing on semantics rather than data structure. Leveraging triple patterns, variables, graph patterns, filters, and aggregates enables efficient and effective retrieval of relevant information from RDF datasets.

Wikidata API

Overview:

The Wikidata API provides programmatic access to read and edit the data stored in Wikidata—a free and open knowledge base editable by both humans and applications. Serving as a central storage for structured data from Wikimedia sister projects, including Wikipedia, Wikivoyage, and Wiktionary, Wikidata's API, based on the MediaWiki API, enables developers to query, search, and manipulate its vast repository of structured data.

Use Cases:

1. Data Integration:

   • Developers leverage the Wikidata API to integrate its rich, structured data into their applications, expanding their datasets with information constantly updated by the community.

2. Semantic Web and Linked Data Applications:

   • Wikidata's structured format and support for RDF (Resource Description Framework) make it an excellent resource for semantic web projects and applications requiring linked data.

3. Bot Development:

   • The API is instrumental in developing bots that automatically update and maintain Wikidata entries, ensuring data accuracy and timeliness.

4. Academic Research:

   • Researchers utilize the API to access and analyze the vast amount of data available on Wikidata for various studies, including linguistics, history, and science.

Access:

The Wikidata API is accessible via HTTP requests to its endpoint, supporting various actions such as querying data, searching for items, and making edits, provided the necessary permissions.

• Explore all API calls in Wikidata's REST API through their official OpenAPI Swagger documentation: Wikidata REST API