Presentation as presented at the ITOC workshop in Philadelphia, 20 February 2016. Uses and Benefits for the Social Sciences research community. By GESIS - Leibniz Institute for the Social Sciences

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twitter.com/openminted_eu
Peter Mutschke
ITOC Workshop
Philadelphia – February 20, 2016
Open Mining Infrastructure for
Text & Data (OpenMinTeD)

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Goal of Text Mining
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implementation of transformational processes
that …
uncover knowledge in unstructured text
 salient content items
 hidden relationships between content items
…to assist researchers and scientific data
curators in making sense of the textual data

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The phases of text mining
taken from ICT2015 presentation (N. Manola)@openminted_eu
NLP Analysis
Entity
Recognition
Data Mining
Knowledge
Discovery
Information
Extraction
STAGE 1 STAGE 2 STAGE 3 STAGE 4
Information
Retrieval
OPENMINTED - The Open Mining Infrastructure for Text and Data

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Challenges
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Text Mining (TM)
 remains a fragmented set of tools
 TM requires particular technological and analytical skills
as well as domain knowledge
 no shared knowledge how to apply
 lack of a central infrastructure
(may rule out use of TM for small research groups)
high entry costs:
need to share infrastructure costs

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Putting it all together
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OpenMinTeD
Establish an open and sustainable Text and
Data Mining (TDM) platform and infrastructure
where researchers can collaboratively create,
discover, share and re-use knowledge from a
wide range of text based scientific and
scholarly related sources

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OpenMinTeD – working on
many fronts
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ACCESSIBLE
CONTENT
DISCOVERABLE
SERVICES
EFFICIENT
PROCESSING
TDM
COMMUNITIES
VALUE ADDED
APPS
Via standardised programmatic
interfaces and access rules
Well-documented easily
discoverable text mining services
and workflows which process,
analyse and annotate text
Operate on public e-Infrastructures
via standarized APIs
Different scientific communities
have different challenges
Community-driven applications to
illustrate the value of the
infastructure. Engage with industry.
OPENMINTED - The Open Mining Infrastructure for Text and Data
taken from ICT2015 presentation (N. Manola)

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Bridging the gap between different
communities
@openminted_eu

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The project
Starts: June 2015
Duration: 3 years
16 Partners:
- 6 mining research groups
- 3 content providers
- 1 data center
- 1 library association
- 2 legal experts
- 6 community related partners
- 2 SMEs
Athena RIC
Univ. of Manchester (NacTem)
Univ. of Darmstadt
INRA
EMBL-EBI
Agro-Know
LIBER
Univ. of Amsterdam
Open University UK
EPFL
CNIO
Univ. of Sheffield (GATE)
GESIS
GRNET
Frontiers
Univ. of Stirling
PARTNERS
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OPENMINTED = The Open Mining Infrastructure for Text and Data
taken from ICT2015 presentation (N. Manola)

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OpenMinTeD users
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 TM consumer to advance their science
 Service Providers to enhance their
tools
 TM researcher to share their algorithms
 Content providers to enrich their
content

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Infrastructural approach
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 OpenMinted does not build new services,
but adopts and adapts existing services for
new communities
 Focuses on interoperability across text
mining services and content providers
 Creates an open & collaborative space for
researchers to use the best fitting textmining
services available

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Data centre Data centre Data centre Data centre
in public cloud
Publisher text
corpus
OpenAIRE/CORE text
corpus
PMC text
corpus
Other text
corpora
Other text
corpora
Other text
corpora
Other types of text
corpora
Layer 3:
Interoperability
to shared storage and
computing resources
Language resources
Language resources
Language resources Language resources
Layer 2:
Interoperability of
language resources
& corpora
Layer 1:
Interoperability
of text mining services
(platforms or
components)
Language resources and corpora registry service
Platform services
Users: researchers, curators, text-miners and new services developers
Registry Workflow ManagementAuth2 & Policy management Annotator Accounting
Mining Platforms Mining Platforms Mining Platforms
Proprietary architectures
Mining Platforms
OPENMINTED = The Open Mining Infrastructure for Text and Data
The architecture
taken from ICT2015 presentation (N. Manola)

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RESEARCH
ANALYTICS
SOCIAL
SCIENCES
AGRICULTURELIFE
SCIENCES
Bottom-up approach
OpenMinTeD works with 4 use cases, which
give their requirements and evaluate the results.
OPENMINTED = The Open Mining Infrastructure for Text and Data
taken from ICT2015 presentation (N. Manola)

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Science driven approach
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GESIS: Infrastructure for the
Social Sciences
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GESIS Research Data Cycle
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Study planningArchiving and
registering
Searching
Data collectionData analysis
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Difficulties in Information Seeking
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Problems Processing Search Results
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Usefulness of TM enhanced search services
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Social Science Use case
Develop and evaluate methods for
automatic detection and linking of named
entities in Social Science publications in
order to advance reliable and context-
sensitive retrieval and linking of relevant
entities
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Enhancing Search in Text and Data
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 classical named entity recognition and
disambiguation of relevant entities (names,
places, organizations, terms) to enhance
automatic indexing
 recognition of vague variable mentions to
enhance linking of data and publications
 enrich data with context information from text
to enhance retrievability of data sets

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Identifying references to survey variables
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OLGA NEŠPOROVÁ, ZDENĚK
R. NEŠPOR (2009). “Religion: An
Unsolved Problem for the Modern
Czech Nation”
ISSP 2008
Link Database
v39: Believe in life after death
v40: Believe in Heaven

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Benefits from user perspective
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 semantic search: understanding the contextual
meaning of (search) terms
 fuzzy phrase search: search for attitudes,
survey questions in texts (under vagueness)
 link retrieval: search and retrieval of links
between text and data
 dataset retrieval: facilitating search for research
data in data catalogues at the level of items and
variables

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Contact us
www.openminted.eu
peter.mutschke@gesis.org
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