Unveiling of Intellectual Property Rights in CORDIS: Harnessing the Power of RML

In our previous post, we delved into the world of knowledge graphs and how they revolutionise the way we access and analyse information within the CORDIS repository. Today, we are excited to introduce a new content type that enhances data integration and accessibility.

Introduction to Intellectual Property Rights

Intellectual Property Rights (IPR) are legal protections granted to the creators of original works, including inventions, literary and artistic works, symbols, names, and images used in commerce. These rights enable creators to control and benefit from the use of their creations, fostering innovation and ensuring that the creators are recognized and rewarded for their contributions. Key forms of IPR include patents, trademarks, copyrights, and trade secrets, each serving to protect different types of intellectual property.

IPRs in the Context of CORDIS

CORDIS, the Community Research and Development Information Service, is the European Commission's primary source of information on EU-funded research projects and their outcomes. As highlighted in a previous LinkedIn post by Cognizone, CORDIS plays a crucial role in disseminating information about the innovations and research advancements funded by the EU, making it a gateway to Europe’s research and development landscape.

Recently, CORDIS has expanded its repository to include a new type of content: Intellectual Property Rights. This addition is significant because it provides detailed records of the legal protections associated with innovations stemming from EU-funded projects. By including IPRs, CORDIS offers a comprehensive view of not only the research outputs but also the formal recognition and protection these outputs receive. This makes it easier for stakeholders to track and understand the legal and commercial potential of these innovations.

Introducing RML: The Power Behind Data Transformation

Our latest content type is initially published as XML, a widely-used format for structuring data. To enhance interoperability and make the data more accessible, we convert this XML into RDF using RML (RDF Mapping Language). This conversion process will soon be integrated into the CORDIS knowledge graph, further enriching it. But what exactly is RML, and why is it important?

What is RML?

RML is a powerful language designed to define rules for mapping data from various formats, such as XML, JSON, and CSV, into RDF. RML extends the W3C-recommended R2RML standard, which focuses on mapping relational databases to RDF, by supporting a broader range of data formats.

How RML Works

The process of converting XML to RDF using RML involves several steps:

• IPR Data in XML: The initial data, such as IPR data, is published in XML format.
• RML Mapping Rules: These XML files are accompanied by RML mapping rules that define how the XML data should be transformed into RDF.
• RML Processor: The RML Processor applies these mapping rules to convert the XML data into RDF format.
• IPR Data in RDF: The result is RDF data that can be easily integrated into the CORDIS knowledge graph and queried alongside other datasets.

Benefits of Using RML

• Flexibility: RML allows for the transformation of diverse data formats into RDF, making it a versatile tool for data integration.
• Efficiency: RML streamlines the data transformation process, reducing the time and effort required to prepare data for analysis.
• Consistency: RML provides a standardised approach to data mapping, ensuring uniformity and reliability across different datasets.

Why This Matters

The transition from XML to RDF using RML is significant because it enables:

• Enhanced Data Integration: RML allows for the combination of data from multiple sources into a unified RDF format, facilitating better data analysis and discovery.
• Reduced Mapping Time: RML significantly decreases the time required for mapping data into the ontology, streamlining the transformation process and improving overall efficiency.
• Improved Data Quality: By applying consistent mapping rules, RML helps maintain data integrity and accuracy throughout the transformation process.
• Advanced Querying Capabilities: With data in RDF format integrated into the knowledge graph, users can perform complex queries across interconnected datasets, uncovering deeper insights and trends.

Looking Ahead

In our upcoming posts, we will provide a deeper dive into the concepts of IPRs and RML. We will also offer a technical tutorial on how to use RML and explore the various functions it supports.

Stay tuned as we continue to explore these exciting developments and their implications for the future of data integration and knowledge management.

Finally, all that's left is a big shout-out to our partners SIMAVI Software Imagination & Vision and Altia , as well as our subcontractors Thomas Francart and Datoptron in this project.

Written by Alexandros Vassiliades, Natan Cox