Introduction

Transforming non-linked data into linked data is essentially about connecting discrete pieces of information to enable them to be more easily integrated and analyzed. Linked data is a method of publishing structured data to be interlinked and become more useful through semantic queries. It’s based on standard web technologies such as HTTP, RDF (Resource Description Framework), and URIs (Uniform Resource Identifiers). Here’s a simplified description of the process:

Identify the Data

Begin by identifying the datasets that you want to transform into linked data. These could be in various formats, such as CSV, JSON, XML, or relational databases.

OSLO mapping

Model the Data

Create a data model using semantic web standards like RDF that define classes and relationships (ontologies) that describe how different data relates.

Assign URIs

Assign URIs to each entity and concept within your data. URIs are unique identifiers that serve as references to your data entities and potentially provide a way to access them via HTTP.

Create Relationships

Define relationships between different data entities using RDF. This involves creating triples that consist of a subject, predicate, and object, essentially linking other pieces of data.

Standardize Data Formats

Convert your data into a standard format easily integrated with other datasets. RDF is a standard format for linked data, but others like Turtle or JSON-LD exist.