Crowdsourcing meaning: a hands-on introduction to CLÉA, the Collaborative Literature Éxploration and Annotation Environment

1. 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 highorder 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 highorder 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 objectdata 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 nonhierarchical 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 lowlevel text description, too.1
CLÉA supports high-level
semantic annotation through TEI compliant, nondeterministic 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.
References
Coombs, J. H., A. H. Renear, and St. J. DeRose
(1987). Markup Systems and the Future of Scholarly
Digital Humanities 2012
25
Text Processing. Communications of the ACM (ACM)
30(11): 933–947. Available online at http://xml.co
verpages.org/coombs.html (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 http://www.digitalhumanities.org/compani
on/view?docId=blackwell/9781405103213/9781
405103213.xml&chunk.id=ss1-3-4&toc.depth=1
&toc.id=ss1-3-4&brand=9781405103213_brand=
default (last seen 2011-10-31).
Piez, W. (2010). Towards Hermeneutic Markup:
An architectural outline. King’s College, DH 2010,
London. Available from: http://piez.org/w
endell/papers/dh2010/index.html (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 http://www.digitalhumanities.org/compani
on/view?docId=blackwell/9781405103213/9781
405103213.xml&chunk.id=ss1-3-5&toc.depth=1
&toc.id=ss1-3-5&brand=default (last seen
2011-10-31).
Notes
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 http://www.catma.de