Technologies and infrastructures supporting text and data analytics: Challenges and Solutions
1. OpenDataMonitor
Horizon 2020
Coordination and Support Action
GARRI-3-2014 Scientific Information in the Digital Age:
Text and Data Mining (TDM)
Project number: 665940
TECHNOLOGIES AND INFRASTRUCTURES SUPPORTING TEXT AND
DATA ANALYTICS: CHALLENGES AND SOLUTIONS
FutureTDM
Reducing Barriers and Increasing Uptake of Text and Data Mining for Research Environments
using a Collaborative Knowledge and Open Information Approach
FutureTDM Symposium, Salzburg
June 13th, 2017
2. Technologies and infrastructures supporting text and data analytics: challenges and solutions
• The TDM Landscape: Infrastructure and
Technical Implementation
• Maria Eskevich (Radboud University)
• Panel discussion
▪ Mihai Lupu (Data Market Austria)
▪ Maria Gavriilidou (clarin:el)
▪ Nelson Silva (know-centre)
▪ Stelios Piperidis (OpenMinTed)
• Discussion
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3. Technologies and infrastructures supporting text and data analytics: challenges and solutions
Panel Discussion
1. A research or industrial application question to be replied to
through TDM presupposes the existence of the appropriate
data (textual or other).
What are the main technical challenges you have faced
and how have you tried to overcome them?
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4. Technologies and infrastructures supporting text and data analytics: challenges and solutions
Panel Discussion
2. Complex, but sometimes even simpler, questions demand
the orchestration of different text and data processing
components or services.
How easy has it been to discover such components /
services and chain them together?
What are the main challenges?
How do/have you overcome them?
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5. Technologies and infrastructures supporting text and data analytics: challenges and solutions
Panel Discussion
3. a. Textual data to be mined may be rendered in different
languages.
How easy has it been to find and reuse the necessary
tools for the language at hand?
b. Language processing tools, or more generally TDM,
needs the appropriate language resources (lexica/models/
etc).
How easy has it been to find and reuse the necessary
tools for the language at hand?
What are the main challenges and how do/have you
overcome them?
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6. Technologies and infrastructures supporting text and data analytics: challenges and solutions
Panel Discussion
4. The open source software movement has resulted in many
tools being available through different outlets/repositories.
How much has your research/application development
benefitted from such software?
How easy has it been to reuse such software solutions?
What are the main challenges you have faced?
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7. Technologies and infrastructures supporting text and data analytics: challenges and solutions
Panel Discussion
5. The EU and national governments have recently launched
sizeable research infrastructures making available data and
tools for or relevant to TDM.
How easy has it been for you to access and use such
infrastructures?
Have they helped you solve part of your research/
application question?
What would be your main requirements from a TDM
infrastructure?
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