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Texts in a Laboratory

My presentation on the motivations to develop a software system like Tesla - see http://tesla.spinfo.uni-koeln.de
by

Jürgen Hermes

on 14 June 2015

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Transcript of Texts in a Laboratory

Open Science
Scholarly Exchange
The Research Process
Source Code
Components
Byte Code
Gate
General Architecture for Text Engineering
Scholarly Communication
Programming
in the Large
Related Tools/Systems
Texts in a Laboratory
The Data
The Scientist
The Method
The Result
The Publication
Open Access
Open Data
Open Source
(my Def)
Open Data^2
Common Practice
The dinosaur: developed since 1995
UIMA
Unstructured Information Management Architecture
The Pro Architecture from IBM
Weblicht
Web services to for automated text annotation
The web service chain
TextGrid
Virtual research environment for the humanities
The tool for manual text enrichment
Tesla
Architecture Principles
Client-Server-Architecture
Tesla as IDE for
Developers of Text-processing Components
Tesla as Platform for Text-processing Software Users
Use Tesla and MyExperiment to Share Your Experiments
Requirements
Whatever your plans may be - Your object of investigation has to be a stream of characters.
Everything that happens in Tesla, results from reproducible algorithms. If you want to change things manually, do it before or after the Tesla workflow.
Don't expect to much. Tesla is a prototype, developed by two doctoral students without funding from other institutions...
... but perhaps this might change one
day.
Thank you!
Full transcript