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Petris, Marco, University of Hamburg, Germany,
Gius, Evelyn, University of Hamburg, Germany,
Schüch, Lena, University of Hamburg, Germany,
Meister, Jan Christoph, University of Hamburg, Germany,

Context and description

Humanities researchers in the field of literary studies access and read literary texts in digital format via the web in increasing numbers – but, apart from search and find, the cognitive processing of a text still takes place outside the digital realm. The interest essentially motivating human encounters with literature hardly seems to benefit from the new paradigm: hermeneutic, i.e. ‘meaning’ oriented high-order interpretation that transcends a mere decoding of information. The main reason for this might be that hermeneutic activity is not deterministic, but explorative: in the scholarly interpretation of literature we are not looking for the right answer, but for new, plausible and relevant answers. Thus high-order hermeneutic interpretation requires more than the automated string- or word-level pattern analysis of the source object provided by most digital text analysis applications so far, namely the ability to add semantic markup and to analyse both the object-data and the metadata in combination. This requires markup that goes beyond the distinction between procedural vs. descriptive of Coombs et al. (1987) and even beyond the subdivision of descriptive markup into genuinely descriptive vs. performative introduced by Renear (2004). By semantic markup we rather mean a true hermeneutic markup as defined by Pietz (2010: paragraph 1):

By ‘hermeneutic’ markup I mean markup that is deliberately interpretive. It is not limited to describing aspects or features of a text that can be formally defined and objectively verified. Instead, it is devoted to recording a scholar’s or analyst’s observations and conjectures in an open-ended way. As markup, it is capable of automated and semi-automated processing, so that it can be processed at scale and transformed into different representations. By means of a markup regimen perhaps peculiar to itself, a text will be exposed to further processing such as text analysis, visualization or rendition. Texts subjected to consistent interpretive methodologies, or different interpretive methodologies applied to the same text, can be compared. Rather than being devoted primarily to supporting data interchange and reuse – although these benefits would not be excluded – hermeneutic markup is focused on the presentation and explication of the interpretation it expresses.

CLÉA (Collaborative Literature Éxploration and Annotation) was developed to support McGann’s (2004) open-ended, discontinuous, and non-hierarchical model of text-processing and allows the user to express many different readings directly in markup. The web based system not only enables collaborative research but it is based on an approach to markup that transcends the limitations of low-level text description, too.1 CLÉA supports high-level semantic annotation through TEI compliant, non-deterministic stand off markup and acknowledges the standard practice in literary studies, i.e. a constant revision of interpretation (including one’s own) that does not necessarily amount to falsification. CLÉA builds on our open source desktop application CATMA2.

In our workshop, we will address some key challenges of developing and applying CLÉA:

  • We will discuss both the prerequisites mentioned above and their role in the development of CLÉA,
  • present interdisciplinary use cases where a complex tagset that operationalizes literary theory (namely narratology) is applied,
  • give a practical introduction in the use of CLÉA, and
  • provide a hands-on session where participants can annotate their own texts.

Finally, we would like to engage participants in a design critique of CLÉA and a general discussion about requirements for text analysis tools in their fields of interest.


Coombs, J. H., A. H. Renear, and St. J. DeRose (1987). Markup Systems and the Future of Scholarly Text Processing. Communications of the ACM (ACM) 30(11): 933–947. Available online at (last seen 2011-10-31).

McGann, J. (2004). Marking Texts of Many Dimensions. In S. Schreibman, R. Siemans, and J. Unsworth (eds.), A Companion to Digital Humanities, 2004. Oxford: Blackwell, pp. 218-239. Online at (last seen 2011-10-31).

Piez, W. (2010). Towards Hermeneutic Markup: An architectural outline. King’s College, DH 2010, London. Available from: (last seen 2011-10-31).

Renear, A. H. (2004). Text Encoding. In S. Schreibman, R. Siemans, and J. Unsworth (eds.), A Companion to Digital Humanities, 2004. Oxford: Blackwell, pp. 218–239. Online at (last seen 2011-10-31).


1.We define this distinction as follows: description cannot tolerate ambiguity, whereas an interpretation is an interpretation if and only if at least one alternative to it exists. Note that alternative interpretations are not subject to formal restrictions of binary logic: they can affirm, complement or contradict one another. In short, interpretations are of a probabilistic nature and highly context dependent.

2.CLÉA is funded by the European Digital Humanities Award 2010, see CLÉA is funded by the European Digital Humanities Award 2010, see