[Open-contentmining] Elsevier's policy on Text and Data Mining

[Peter Murray-Rust]

Recently announced:
http://www.elsevier.com/about/universal-access/content-mining-policies

Text and Data Mining

As the volume of scholarly output increases, we recognize that researchers
are increasingly interested in using tools such as text mining to explore
patterns and trends across large databases of content.

Elsevier has for many years actively collaborated with researchers and
institutes to facilitate text and data mining, both by enabling access and
by investing in our platforms to support these initiatives. Our text and
data mining policy is intended to simplify access for researchers, as well
as clearly detailing the terms and conditions of this access.
 *Elsevier's policy*


*For subscription content:*

   - *Academic subscribers:* Researchers at these institutions can text
   mine subscribed content on ScienceDirect for non-commercial purposes, via
   the ScienceDirect API's. Access is granted to faculty, researchers, staff
   and students at the subscribing institution. The terms and conditions of
   this access are summarized below.  Please speak to your Elsevier Account
   Manager for further details.
   - *Corporate and other subscribers:* Please contact your Elsevier
   Account Manager to find out more about our text mining products and
   services.
   - *Non-subscriber access: *Requests are considered on a case-by-case
   basis, and can be made by emailing UniversalAccess at elsevier.com.

*For open access content:* Text and Data mining permission are determined
by the author's choice of user license. This information is detailed in the
individual articles. Read more on user
licenses.<http://www.elsevier.com/about/universal-access/content-mining-policies/?a=120946>

Terms and conditions of text and data mining

   - Text mining access is provided to subscribers for non-commercial
   purposes
   - Access is via the ScienceDirect APIs only
   - Text mining output adheres to the following conditions:


1. Output can contain "snippets" of up to 200 characters of the original
text

2. Licensed as CC-BY-NC

3. Includes DOI link to original content

*Note:* We request that all access to content for text mining purposes
takes place through our APIs and remind you that in order to maintain
performance and availability for all users, the terms and conditions of
access to ScienceDirect continue to prohibit the use of robots, spiders,
crawlers or other automated programs, or algorithms to download content
from the website itself.
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Let's have your comments!


-- 
Peter Murray-Rust
Reader in Molecular Informatics
Unilever Centre, Dep. Of Chemistry
University of Cambridge
CB2 1EW, UK
+44-1223-763069
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