R&D team

The R&D team strives to innovate humanities research with digital research methods. We share our knowledge of methodology with interested and motivated scholars, students, and developers through open source prototypes, workshops and intensive training. Our work is regularly published in articles in national and international journals and presented at (inter)national conferences.

As a team within the Digital Infrastructure department, the R&D team supports infrastructure in multiple ways. Once prototypes have proven the validity of our approach, they can be incorporated into existing infrastructure or developed further into stable and scalable production software. In addition to fostering new software, we also contribute to researchers’ innovative use of digital infrastructure products in their ongoing work, thus providing our product teams with useful feedback.

In order to create new collaborations and expand existing lines of research, the R&D team offers consulting services on a variety of topics. We are open to ideas from researchers as well as developers from other teams and will provide advice on new project proposals.


Research Themes

The R&D agenda currently consists of three research themes inspired by previous innovative work by R&D team members:

i) Data scopes and tool criticism

Researchers increasingly use a variety of digital data and tools in humanities research. The R&D Team proposes to develop a coherent methodology using the concept of data scopes. Data scopes provide a means for discussing how data processing can be incorporated into new methods that can be used in relevant research fields in the humanities. Tool criticism provides a methodology to evaluate tools for the applicability for a certain research task.​

ii) Scholarly web annotation

Annotations allow researchers to enrich data sets. Using web based stand-off annotations researchers can enrich data sets without changing the original content. This means the creator or owner does not have to give permission or be responsible for the annotations created by others, which contributes to wider resource sharing. Scholarly web annotation as a theme focuses on both conceptual models of annotation and the practical implementation of annotation methodology.

iii) Text as a Graph

Text as a graph (TAG) is a new data model for text that strives to address well-known limitations of SGML and XML. TAG enables scholars to model their notion of text in an effective and idiomatic manner, which allows for advanced textual analysis and synthesizes knowledge from different domains of research. Researchers no longer have to resort to workarounds when transcribing and modelling text and, making use of the Alexandria implementation, they can collaborate effectively on edition projects.

Sample Projects

Data Scopes 2019 is a workshop with which we contribute to methodological reflection on and consolidation of the collection of methods that are already used by many in the humanities (often in the form of tools) in addition to the existing methods.

Scholarly Web Annotation Client is a Javascript annotation client for RDFa enriched web resources.

TAG is an alternative (graph-based) data model for text, which allows to explore a more flexible way of digital editing than is available with the single hierarchy afforded by XML.

Alexandria accommodates the encoding of multiple, coexisting views on text and thus supports various approaches to scholarly editing.

Hyper Collate is a prototype collation engine that is able to handle in-text variation if it’s marked with the TEI/XML elements.