[GOAL] [job] WikiFactMine: Open Access Wikimedian In Residence in Cambridge UK

[Heather Morrison]

Thank you for clarifying that you consider this to be a potential breach of copyright. I argue that your problem reflects a risk-averse approach.

Can you please explain how you think a CC-BY-NC-ND license forbids copying to private computers for data processing purposes? I argue that the kind of data / text mining that you propose is simply an automated form of reading and does not involve creating a derivative work.

One reason I assume you are not creating derivatives is because if you are, then the attribution requirement does apply to CC-BY material. If you are planning to use a public domain license you must not be creating derivatives.

For the sake of clarity I understand we are talking about copying large quantities of material freely available on the Web to private computers for data analysis, with subsequent redistribution limited to copyright-free facts.

best,

Heather Morrison


-------- Original message --------
From: Peter Murray-Rust <pm286 at cam.ac.uk>
Date: 2017-02-27 6:10 PM (GMT-05:00)
To: "Global Open Access List (Successor of AmSci)" <goal at eprints.org>
Subject: Re: [GOAL] [job] WikiFactMine: Open Access Wikimedian In Residence in Cambridge UK



On Mon, Feb 27, 2017 at 5:58 PM, Heather Morrison <Heather.Morrison at uottawa.ca<mailto:Heather.Morrison at uottawa.ca>> wrote:
Another point: we agree that facts are not copyrightable. Assuming we are correct in this assumption, there is no argument for limiting this work to material licensed CC-BY. This kind of work could be carried out with material under any kind of license including all rights reserved.

The research involves **copying** the material (often > 100,000 separate items) to several sites including public repositories and Wikimedia computers. This is only possible in practice with an explicit permissive licence such as CC BY. It would be a potential breach of copyright to use material where explicit permission was not given on the document or metadata intimately semantically associated with it.






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