There are many online translation agencies that have focused on streamlining the buying experience and making it easy to procure translation. However, in these solutions the translators are faceless, often times leaving much to be desired on the quality side. At TM-Town, we believe the next generation is a system that builds on what these companies have done but also allows the buyer a better selection process to ensure that the best translator (the best specialist) for a particular job is chosen.

1. K E V I N
D I A S
EMPOWERING THE SPECIALIZED TRANSLATO
THROUGH DATA AND TECHNOLOGY
TAUS EXECUTIVE FORUM TOKYO 2016

2. DATA SHARING
TM-Town is a unique new site for you -- the
freelance translator -- to store, manage and share
translation memories (TMs) and glossaries.
2

3. DATA SHARING
“Personally, I have no interest in TM-Town or in
'sharing' my translations, mostly for NDA-related
reasons”
“My customers know of my firm commitment to privacy.
What would they think if they saw my details in a
website about sharing TMs and glossaries?”
“There are usually years of hard work behind translation
memories and I am only willing to share mine with a
selected group of colleagues when needed”
3

4. DATA SHARING
1) What? 2) With whom?
4

5. DATA SHARING
1) What?
- a translation memory file
- a glossary
- a term
- a source document
- a translation (target document)
- a terminology synopsis file*
5

6. DATA SHARING
2) With
whom?- a machine
- a trusted colleague
- a client
- a 3rd party
- the public
- a machine
- a trusted colleague
- a client
- a 3rd party
- the public
6

7. TRANSLATION DATA USE CASES
• Traditional concordance search
• Personalized machine
translation
• Translator discovery
• Predictive typing
• Productivity analysis
• …many more
7
• Traditional concordance search
• Personalized machine
translation
• Translator discovery
• Predictive typing
• Productivity analysis
• …many more

8. TRANSLATION DATA – THE KEY TO BETTER MATCHING
8

9. PUTTING THE PUZZLE PIECES TOGETHER
9
The puzzle pieces:
• Traditional concordance search
• Personalized machine translation
• Translator discovery
• Predictive typing
• Productivity analysis
• Crowdsourcing and scheduling
• Real-time collaboration
• …many more

10. PUTTING THE PUZZLE PIECES TOGETHER
10

11. NEXT GENERATION OUTSOURCING – CASE STUDY
11
Project Manager
Needs: team of translators for an English to French “renewable
energy” government contract job
Problem: how to find a team of specialists for the job?

12. THE FUTURE
• Work is automatically routed to an individual or team of
translators with expertise in the specialized field
- Work doesn’t just go to the first translator with their green light on
- Finds the expert(s) whose brain and TMs include this specialized knowledge
- Work in a translator’s wheelhouse can be done do 2x/3x faster because they
know the domain and the terminology
• Translator has access to real-time effortless collaboration
with peers in that specialized field
• Client gets a higher quality, more consistent translation
back in less time
12

13. NDA VS. COPYRIGHT
• A nondisclosure agreement (NDA) typically protects a party
from disclosure and/or use of any Confidential Information.
• Copyright is a legal right created by the law of a country that
grants the creator of an original work exclusive rights to its use
and distribution, usually for a limited time. The exclusive rights
are not absolute; they are limited by limitations and exceptions
to copyright law, including fair use.
13

14. DETERMINING COPYRIGHT
• Copyright of a termbase or glossary created by the translator during
the translation process is owned by the translator (with a few
exceptions / gray areas)
• Determining who holds the copyright for translation memory is a legal
gray area where the legislation has not caught up with the technology
 Can the source or target text be reproduced from the translation memory?
 Has copyright of the Translation Data been assigned back to the client in any written
agreement?
 Is translation memory a database (legally speaking)?
 Did multiple translators work on the creation of the translation memory?
 Have the source and target documents been significantly altered in the creation of the
translation memory (i.e. through codes and tags added to segments)?
 Are there different copyright holders for the translation memory structure vs. translation
memory content?
14

15. DOES THE TRANSLATOR OWN THE COPYRIGHT OF A TRANSLATION MEMORY (TM)
CREATED DURING THE TRANSLATION PROCESS?
0% 10% 20% 30% 40% 50%
No
It depends
I'm not sure
Yes
* Based on an anonymous survey of 37 professional translators
15

16. DATA SHARING – WHAT ABOUT MY NDA?
The Company and the Contractor agree not to disclose, regardless whether
for use for their own benefit or that of others, or not, any Confidential
Information either during or after the professional relationship, and will not at
any time during or subsequent to this agreement disclose or use in any way
any information or knowledge or data received or developed while working
with the Company or Contractor, including, but not limited to plans, lists,
prospects lists, and trade secrets of either the Company and/or its third party
clients or the Contractor, unless required by law.
16

17. EVOLUTION
• Private vault
1 2 3
• Private vault + redact confidential terms
• Private vault + redact confidential terms + analyze offline
17

18. A NEW TYPE OF TRANSLATION DATA
18

19. FAIR USE – TRANSFORMATIVE USE
19
Transformativeness
From Wikipedia, the free encyclopedia
In United States copyright law, transformativeness is a
characteristic of some derivative works that makes them
transcend, or place in a new light, the underlying works on
which they are based. In computer- and Internet-related
works, the transformative characteristic of the later work is
that it provides the public with a benefit not previously
available to it, which would otherwise remain unavailable.

20. FAIR USE – TRANSFORMATIVE USE
20
• Courts have sometimes found copies made as part
of the production of new technologies to be
transformative uses
• Many commentators suggest that audio and video
mixes and remixes are examples of transformative
works, as well as other kinds of works that use
existing content to do unexpected and new things

21. DATA SHARING – A NEW TYPE OF TRANSLATION
DATA
21
NDA
✓
✓
Copyright

22. CONCLUSIONS
• New innovations in job matching will lead to improved translation
quality and better supply chain efficiency
• The translation industry has only begun to scratch the surface on
uses and applications of new technologies
- It is not a zero sum game; all industry players (end clients, agencies,
translators) will benefit
• New offline analysis tools will help translators leverage their prior
work without infringing copyright law or NDAs
• For translators - specialized domain experts stand to prosper the
most from new innovations in job matching
22