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Location:Lecture Hall HS 15.12 RESOWI building, section C, first floor
TEI MediaWiki extension
T. Pellissier Tanon
Télécom ParisTech, France
MediaWiki  is one of the leading open source wiki engines.
It is well known for being used by Wikipedia but it also powers many other websites including Wikisource , the Wikipedia sister project dedicated to transcription, and the TEI wiki .
MediaWiki default encoding for wiki pages content is a flavor of wikitext. However the platform provides a powerful content abstraction system, allowing, e.g. to use an other content encoding for some or all wiki pages.
The aim of this demo is to present a new MediaWiki extension, called "TEI"  that allows to create MediaWiki pages encoded in TEI P5 instead of Wikitext.
This extension is a work in progress. It provides an implementation of a subset of TEI content tags (i.e. excluding the TEI header) inspired by TEI simplePrint.
A simple XML editor is provided with validation and auto-complete based on a configurable ODD bundled with the extension. A beginning of WYSIWYG editor is also available.
A demo wiki is updated daily with the latest version of the extension  and provides some examples.
Before the demonstration we plan to improve both the WYSIWYG and XML editor, implement the support of more TEI tags and attributes and improve the extension configuration and extensibility. If time permits, we also plan to integrate it with ProofreadPage, an other MediaWiki extension providing a transcription workflow for MediaWiki and currently based on Wikitext .
As TEI is not a format, though many people think it is. It's a de facto standard that specifies Guidelines for document interchange. Actually the Guidelines are based on the XML but this is only one possible technical way of expressing the phenomenons. In the graph you can use multi-hierarchical annotations layers.
Graph models are very easy to read and understand. So DH-People and “normal” scientists have a level of discussion in common. A Graph can be expressed as RDF so the step from a Graph to linked open data is easy to make. In this paper a xml-example will be imported into the graph-database neo4j and then be converted to the Standoff-Property-Json-Format. This data can then be imported into the Standoff-Property-Editor SPEEDy, which can manage multi-hierarchical annotations.
Recogito: from Semantic Annotation to Digital Scholarly Edition
M. Gimena1, R. Simon2, E. Barker3, L. Isaksen4, R. Kahn5, V. Vitale6, A. Rojas Castro7, H. Cayless8
1Consejo Nacional de Investigaciones Científicas y Técnicas, Argentine Republic; 2AIT; 3The Open University; 4University of Exeter; 5Alexander von Humboldt Institut für Internet und Gesellschaft HIIG; 6University of London; 7Cologne Center for eHumanities, Universität zu Köln; 8Duke University
Recogito (https://recogito.pelagios.org/) is a web-based environment for collaborative semantic annotation, developed by Pelagios (https://commons.pelagios.org). It is open source software, supports plaintext (.txt extension) as well as TEI/XML encoded text (.xml extension), and allows users to export the results of their work in different formats, including RDF, TEI/XML, GeoJSON, etc. Originally, the tool has been designed with a focus on scholarly geographic annotation, i.e. the transcription, marking up and geo-resolving of geographical documents such as itineraries, maps and travel reports. More recently, however, the feature set was expanded in order to provide more general annotation functionality. Perhaps the most notable feature of Recogito is the ability to produce semantic markup without the need to work with formal languages directly. Through an easy-to-use interface, users can navigate digitized documents; create personal collections; add tags and comments; build up tagging vocabularies, and geo-resolve place references by linking them to gazetteers. Users can either work alone in a closed workspace, or together as groups of collaborators. Recogito also makes it easy to apply Named Entity Recognition (NER) to TEI documents, with the possibility to choose between different recognition engines and authority files for entity resolution.
In this demo we will show how Recogito can serve as a useful environment for the efficient creation of minimal digital editions. Starting from plaintext source files, we will demonstrate the workflow for uploading content, creating semantic annotations, exporting to TEI, refining the markup, and publishing the results as an online digital edition. As a case study, we will present a geographically annotated corpus of early Argentinian texts. This edition was produced by semantically enriching sources with references to an early colonial american gazetteer, funded in part through a Pelagios Resource Development Grant in 2017.