Chapter 2 Data and tools

In the previous chapter, we discussed research on the semantic annotation of legal resources, along with crucial factors to consider in this endeavor. Building on that theoretical foundation, we will now delve into the core components of this project: the data available to us and a preliminary analysis of its structure. In particular, we choose to provide a demonstration of the data transformation pipeline by annotating the Italian copyright legislation (Gazzetta Ufficiale 1941) with the copyright ontology (García and Gil 2006).

The decision to annotate Italian copyright legislation was influenced by the significant harmonization already present within EU legislation. This uniformity offers an interesting case study that could be expanded across different Member States. While our focus is on this particular legislation, the transformation pipeline has a versatile nature, making it adaptable to diverse domains.

2.3 The Doccano Annotation Tool

Another key element of our data transformation pipeline is Doccano (Nakayama et al. 2018), an open-source web application that supports a variety of annotation needs. Its flexibility and user-friendly interface make it a popular choice among researchers and developers in the fields of natural language processing (NLP) and machine learning.

2.3.1 Features

Doccano offers a range of features that cater to different annotation needs:

  • Labeling Formats: Supports various annotation types including named entity recognition (NER), text classification, and sequence-to-sequence tasks.

  • Collaboration: Multiple annotators can work on the same dataset simultaneously, facilitating collaborative projects.

  • Custom Label Creation: Users can define their own labels tailored to specific projects.

  • Import/Export: Easy import and export of data in formats like JSON and CSV.

  • User Management: Role-based access ensures data security and project management.

  • Semi-automated or automated annotation support

2.4 Conclusion

This chapter discussed the data and tools that are being used for the project work. Initially, we examined the structure of the Italian copyright legislation, formatted in Akoma Ntoso (Gazzetta Ufficiale 1941). In the second section, we explored the previous work by García and Gil (2006) on the development of the Copyright Ontology. The ‘Creation model’ explained how works qualify for copyright. The ‘Rights model’ detailed the protections given to creators. The ‘Actions model’ showed the different activities and interactions possible within copyright. In the third section, we briefly presented the Doccano annotation tool and its main features (Nakayama et al. 2018).

In the next chapter we will go through the various components of the data transformation pipeline and how they interact with each other.

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