Teaminology - A New Crowdsourcing Application for Term & Translation Governance, CHAT2013

TAUS - The Language Data Network
TAUS - The Language Data NetworkTAUS - The Language Data Network
Teaminology
CHAT @ TCWorld, Wiesbaden, 2013
teaminology
A crowdsourcing application for
collaborative term and translation governance
developed @ Welocalize

Key features:
 team approach to terminology: users can vote on preferred translations,
quality is ensured through term champions
 statistics on user engagement and the frequency of their suggestions to
report on community health
 centralized platform for simultaneous term / sentence search in
Translation Memories (TMs) and glossaries
 context information through further granularity provided by metadata
 crowdsourcing for terms and for translating entire projects with a
connection into a TMS (e.g. GlobalSight)
teaminology
Background and lessons learned
 First proof of concept 2011 – required enhancements

 Tool needs to be relevant, fun & engaging: focus on user-experience
 Right balance between simplicity (easy-to-use) and controlled
complexity (informed choices)
 Depending on use case, various groups can be engaged:
- end users
- translators
- quality managers
- product experts
- creative consultants
-…
 “It’s ok to make mistakes” – term managers can revisit choices
 Integration
teaminology

SNAPSHOT – term governance concept
teaminology
SNAPSHOT - terminology
teaminology

SNAPSHOT – crowd engagement / reports
teaminology
Global terminology management
Use case illustration
- build consistent language assets
- strong brand image across all languages and
markets
- reduce translation errors
- reduces legal liabilities

- shorten time-to-market
- reuse and retrieve terminology
- engage the supply chain
- connect to TMS and CMS
- global terminology governance across all
stakeholders

- reduce cost for terminology management
teaminology
Harmonizing existing assets
Use case illustration
Inconsistencies
between existing
client Translation
Memories and
Termbases
Translators flag
issues as they go
along, SuperUser
fixes
teaminology
Crowdsourcing & searches
Use case illustration
MLV 1

• French
• German
• Japanese

MLV 2

MLV 3

• French
• Japanese
• Korean

• French
• German
• Korean

Translators across all MLVs and
languages can use 1 platform
for legacy translations, access
metadata (e.g. images),
quickly identify rejected terms
- and crowdsource entire new
sentences
No more search in offline local
TMs
Inspiration from other
languages (e.g. Do-NotTranslatables)
teaminology
Leverage the knowledge of your experts for
better terminology
Questions?
christian.zeh@welocalize.com
lena.marg@welocalize.com
Some technical specs
Server Level 1
• Developed in Java
• The server layer of the application is cross-OS compatible and can run on 64-bit English
Windows Server 2008 R2, 32-bit and 64-bit x86 English Windows Server 2003,
Standard/Enterprise Edition or Ubuntu Linux Server.
• Application server is Jboss 4.2
• Database is MySQL
• JettyServer used for importing/exporting TMs.
• API for GS<>Teaminology to import/export assets that are parts of projects.
Client Layer Technical specs
• Internet Explorer 7 and higher, Firefox 3.5 and higher, and Google Chrome 16.0.912.63 and
higher.
• Java Runtime Environment 1.6 or higher.
1 of 12

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Teaminology - A New Crowdsourcing Application for Term & Translation Governance, CHAT2013

  • 1. Teaminology CHAT @ TCWorld, Wiesbaden, 2013
  • 2. teaminology A crowdsourcing application for collaborative term and translation governance developed @ Welocalize Key features:  team approach to terminology: users can vote on preferred translations, quality is ensured through term champions  statistics on user engagement and the frequency of their suggestions to report on community health  centralized platform for simultaneous term / sentence search in Translation Memories (TMs) and glossaries  context information through further granularity provided by metadata  crowdsourcing for terms and for translating entire projects with a connection into a TMS (e.g. GlobalSight)
  • 3. teaminology Background and lessons learned  First proof of concept 2011 – required enhancements  Tool needs to be relevant, fun & engaging: focus on user-experience  Right balance between simplicity (easy-to-use) and controlled complexity (informed choices)  Depending on use case, various groups can be engaged: - end users - translators - quality managers - product experts - creative consultants -…  “It’s ok to make mistakes” – term managers can revisit choices  Integration
  • 4. teaminology SNAPSHOT – term governance concept
  • 6. teaminology SNAPSHOT – crowd engagement / reports
  • 7. teaminology Global terminology management Use case illustration - build consistent language assets - strong brand image across all languages and markets - reduce translation errors - reduces legal liabilities - shorten time-to-market - reuse and retrieve terminology - engage the supply chain - connect to TMS and CMS - global terminology governance across all stakeholders - reduce cost for terminology management
  • 8. teaminology Harmonizing existing assets Use case illustration Inconsistencies between existing client Translation Memories and Termbases Translators flag issues as they go along, SuperUser fixes
  • 9. teaminology Crowdsourcing & searches Use case illustration MLV 1 • French • German • Japanese MLV 2 MLV 3 • French • Japanese • Korean • French • German • Korean Translators across all MLVs and languages can use 1 platform for legacy translations, access metadata (e.g. images), quickly identify rejected terms - and crowdsource entire new sentences No more search in offline local TMs Inspiration from other languages (e.g. Do-NotTranslatables)
  • 10. teaminology Leverage the knowledge of your experts for better terminology
  • 12. Some technical specs Server Level 1 • Developed in Java • The server layer of the application is cross-OS compatible and can run on 64-bit English Windows Server 2008 R2, 32-bit and 64-bit x86 English Windows Server 2003, Standard/Enterprise Edition or Ubuntu Linux Server. • Application server is Jboss 4.2 • Database is MySQL • JettyServer used for importing/exporting TMs. • API for GS<>Teaminology to import/export assets that are parts of projects. Client Layer Technical specs • Internet Explorer 7 and higher, Firefox 3.5 and higher, and Google Chrome 16.0.912.63 and higher. • Java Runtime Environment 1.6 or higher.