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
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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
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ES JA, ZH, ...
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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: [email protected]
CONSORTIUM