The document summarizes a presentation about the FREME project. The FREME project is developing technology and business cases around digital content and linked data. It involves technology providers, business case partners, and dissemination partners. The business cases focus on digital publishing, translation, agriculture data, and website personalization across multiple languages. FREME aims to address gaps in current solutions by developing interfaces and services to enrich content with machine translation, terminology annotation, and linked data.

1. FREME Business Cases – FREME at FEISGILTT 2015 WWW.FREME-PROJECT.EU 1
Co-funded by the Horizon 2020
Framework Programme of the European Union
Grant Agreement Number 644771
FEISGILTT 2015 |BERLIN, 2 JUNE 2015
Felix Sasaki, DFKI / W3C Fellow
On behalf of the FREME Consortium
FREME BUSINESS CASES
www.freme-project.eu

2. FREME Business Cases – FREME at FEISGILTT 2015 WWW.FREME-PROJECT.EU 2
THE FREME PROJECT
• Two year H2020 Innovation action; start February 2020
• Industry partners leading four business cases around
digital content and (linked) data
• Technology development bridging language and data
• Outreach and business modelling demonstrating monetization of the multilingual
data value chain

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GROUPING OF PARTNERS
• Technology solution providers
◦ DFKI, InfAI, iMinds, Tilde
• Business Case Partners
◦ iMinds, VistaTEC, Agro-Know, Wripl
• Dissemination and Business Modeling
◦ ISMB

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CHALLENGE AND OPPORTUNITY: BIG DATA IS GROWING ACROSS
LANGUAGES, SECTORS AND DOMAINS
• BC: Digital publishing
• BC: Translation and localisation
• BC: Agriculture and food domain data
• BC: Web site personalisation
Agriculture
metadata, user
content, news
content, …
WHAT LIES AHEAD FOR SEVERAL INDUSTRIES? SEE THE FREME BUSINESS CASES
FR
ES
JA, ZH, ...
AR

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CURRENT STATE OF SOLUTIONS
Machine
translation,
terminology
annotation, ...
Linked data
creation &
processing
GAPS THAT HINDER BUSINESS:
• Plethora of formats
• Adaptability and platform dependency
• Language coverage
• Usability “The right tool for the right person
in given and new enterprises”:
technology influences job profiles

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FREME TO THE RESCUE: ENRICHING DIGITAL CONTENT
Machine
translation,
terminology
annotation, ...
Linked data
creation &
processing
LT and LD as first class
citizens on the Web
A SET OF INTERFACES* - DESIGN DRIVEN
BY BUSINESS CASES
LT and LD for various
user types: (application)
developer, content
architect, content
author, translator, …
* Graphical interfaces
* Software Interfaces

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FREME E-SERVICES – BIRDS EYE VIEW
• e-Entity
◦ Automatic annotation of named entities
• e-Terminology
◦ Annotation of terms and linkage to term databases
• e-Link
◦ Enrichment with information from (linked) (open) data sources*
• e-Translation
◦ Cloud based machine translation
• e-Internationalisation
◦ ITS 2.0 metadata to govern the multilingual & semantic content workflow
• e-Publishing
◦ Publish enriched content in ePub format
* More on this: see presentation FEISGILTT 4 June 

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BUSINESS CASES

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AUTHORING AND PUBLISHING MULTILINGUALLY AND SEMANTICALLY
ENRICHED EBOOKS
• Challenge
◦ Moving to digital publishing workflows leads to high costs. Added value beyond the content
itself is needed.
• Solution
◦ Easy to integrate solutions, based on standardised interfaces for software components and
authors, responding to usability requirements

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AUTHORING AND PUBLISHING MULTILINGUALLY AND SEMANTICALLY
ENRICHED EBOOKS
• Example: Integration into ePub editing mode of oXygen XML Editor
e-Entity: annotate named entities

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INTEGRATING SEMANTIC ENRICHMENT INTO MULTILINGUAL
CONTENT IN TRANSLATION AND LOCALISATION
• Challenge
◦ Localisation service providers are under pressure: more speed, better quality, lower
payment rates per translation outcomes. LSPs need to offer additional services, going
beyond translation
• Solution
◦ Allow translators to work with linked data sources during the translation process, to add
additional information to the translated content.

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INTEGRATING SEMANTIC ENRICHMENT INTO MULTILINGUAL
CONTENT IN TRANSLATION AND LOCALISATION
• Example: Integration into XLIFF 2.0 editing mode of oXygen XML Editor
• Combination of services
◦ e-Entity: annotate named entities
◦ e-Link: fetch additional information from a linked data source like dbpedia, specific to the
type of entities (places, persons, …)

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INTEGRATING SEMANTIC ENRICHMENT INTO MULTILINGUAL
CONTENT IN TRANSLATION AND LOCALISATION
• Enriching content with machine readable information – represented as JSON 
◦ Input: “Welcome to Berlin … Marlene Dietrich!”
◦ Output:
[
{
"@id": "dbpedia:Marlene_Dietrich",
"@type": "person",
"born": "1901-12-27"
},
{
"@id": "dbpedia:Berlin",
"@type": "place",
"population": "3746444"
}
]
May be basis e.g. for
multilingual generation:
• “… born 1901”
• “… geboren 1901”
• “…１９０１年生まれ”
• …

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ENHANCING THE CROSS LANGUAGE SHARING AND ACCESS TO OPEN
AGRICULTURAL AND FOOD DATA
• Challenge
◦ Content metadata is not available in multiple languages, needs to be curated manually, and
the metadata is not linked to external data sources.
• Solution
◦ Via FREME, make metadata available in several languages
◦ Easy data discovery for users with different linguistic profiles
◦ Allow to reach out to new markets

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FREME-EMPOWERED PERSONALISED CONTENT RECOMMENDATIONS
• Challenge
◦ Personalised content recommendations for content rich websites help to increase
engagement of users on a website. Current solutions focuses on English web sites.
• Solution
◦ Using FREME, content recommendation will be provided in several languages
◦ The e-Services e-Entity and e-Translation will help to identify user relevant items in Web
content

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WANT TO TRY THINGS OUT?
• Go to http://api.freme-project.eu/doc/0.1/
• Check out API demo calls
• More tomorrow = FEISGILTT day 2, during the “linked data” presentation

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DEMO:
ENRICHMENT IN OXYGEN XML EDITOR
DISCLAIMER: NOT YET FREME BASED, BUT
SHOWS THE POSSIBILITIES OF COMBINING
E-ENTITY AND E-LINK

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LESSONS TO LEARN FOR PROJECTS INVOLVING ENRICHMENT
• Adequate interfaces for the user type in question are key
◦ E.g. content creator vs. translator
• Hide complexity of technologies in a user specific way
◦ Ability to adapt linked data queries without knowing linked data – “I want to find
information about cities and related tourists sites in the radius of X miles”
• New job roles may be needed
◦ Today: content architect, set up of content workflows
◦ With FREME: enrichment architect, set up of language and data tooling (e.g. preparing
linked data queries)
• FREME may also help to automatize the collaboration between departments (e.g.
localisation <> marketing) within one organisation

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CHALLENGES
• Technical, e.g.: How to store enrichment information in the format being enriched?
◦ RDF as storage and processing format not widely deployed e.g. in multilingual content
creation
• Closing knowledge gaps
◦ Sharing knowledge between different types of tool developers: language technology, linked
data, localisation, content creation, …
• Aspects of data sets
◦ Availability for commercial purposes, quality, sustainability, complexity of the data (“How
do I find X?”)
• Qualification & tooling
◦ Teaching translators just enough linked data to do proper enrichment
• Convincing (end) customers: developing killer applications using FREME

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NEXT STEPS FOR FREME
Creating & updating prototypes of e-Services
Agile approach: gathering feedback from business cases feeds implementations
Potential input to standardisation of the open Web platform: ease access to
data (sources + technologies) and language technologies for various user types
Learn more at www.freme-project.eu
Idea: discuss concrete standardisation opportunities at a W3C workshop on
interfaces to LT & LD technologies? Ping me if interested 

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CONTACTS
FELIX SASAKI
Senior Researcher DFKI / W3C Fellow
On behalf of the FREME consortium
E-mail: felix.sasaki@dfki.de
CONSORTIUM