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Collaboration in textual studies - textgrid

TextGrid http://www.textgrid.de is primarily concerned with historical-critical editions for modern cross-language researchers. Such historical-critical editions often form the basis for more light-weight editions for study and reading. Such editions can be very large and very detailed. They cannot be the result of the work of one individual researcher alone, but have to be the result of a collaborative effort. It is TextGrid’s key innovation to facilitate such (virtual) collaboration across language and national barriers.

In its first phase of funding, TextGrid delivered a modular platform for collaborative textual editing, mainly based on the community standard of the Text Encoding Initiative (TEI). http://www.tei-c.org/index.xml As a community grid for textual studies, TextGrid forms a cornerstone in the emerging German e-Humanities agenda. Its success has also been noted in the UK, where the arts and humanities e-Science initiative allowed researchers to experiment with new technologies to cope with the research data deluge in textual studies. The UK e-Science Scoping Study for textual studies, written by Professor Peter Robinson from Birmingham University, quotes TextGrid as a prime example of how to advance literary and textual studies with new digital services, because it addresses the need for collaborative resource creation, comparison (that is, collation and alignment), analysis and annotation.

TextGrid focuses on advancing digital scholarship for a particular community: TEI-based textual studies research. At the centre of its technology innovation is the deployment of an integrated development environment for the creation of critical editions called TextGridLab. Based on the Eclipse platform, TextGridLab uses Grid technologies for storage and retrieval of textual studies resources. It supports all activities, stakeholders and challenges in the textual studies research lifecycle. Resource discovery, via the web interface or TextGridLab modules, is aided by searching across the entire TextGrid data pool – either full text or metadata-restricted.

Decentralized and collaborative work is always sensible when primary sources grow very large and need to be made available and linked to each other in complex metadata schemes. This is due to the quality of these resources, which demand an integration of different viewpoints. Additionally, new mass quantities of resources need the support of high-performance technology in new investigations of ways that advanced text mining solutions can add to the linking and discovery of textual studies resources. The UK JISC Engage funded HiTHeR project has taken on this challenge.

Use of e-infrastucture in textual studies – hither

In the Digital Humanities, many text-based collections are exposed via searchable websites. One of these resources is the Nineteenth Century Serials Edition (NCSE) in the UK. http://www.ncse.ac.uk The NCSE, a free online scholarly edition of nineteenth-century periodicals and newspapers, has been created as a collaborative project between Birkbeck, University of London, King's College London, the British Library, and Olive Software. The UK Arts and Humanities Research Council funded the project from January 2005 to December 2007. The NCSE corpus contains circa 430,000 articles that originally appeared in roughly 3,500 issues of six 19th Century periodicals. Published over a span of 84 years, materials within the corpus exist in numbered editions and include supplements, wrapper materials and visual elements. A key challenge in creating a digital system for managing such a corpus is to develop appropriate and innovative tools that will assist scholars in finding materials that support their research, while at the same time stimulating and enabling innovative approaches to the material. One goal would be to create a 'semantic view' that would allow users of the resource to find information more intuitively. Such a semantic view can be created by offering users articles with common content through a browsing interface. This is a typical classification task known from many information retrieval and text mining applications. (Nentwich 2003)

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Source:  OpenStax, Research in a connected world. OpenStax CNX. Nov 22, 2009 Download for free at http://cnx.org/content/col10677/1.12
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