Difference between revisions of "Handke, Guibault, and Vallbe (2015)"

From Copyright EVIDENCE
(Created page with "{{MainSource |Source={{Source |Name of Study=Handke, Guibault, and Vallbe (2015) |Author=Christian Handke; Lucie Guibault; Joan-Josep Vallbe |Title=Is Europe Falling Behind in...")
 
 
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|Source={{Source
 
|Source={{Source
 
|Name of Study=Handke, Guibault, and Vallbe (2015)
 
|Name of Study=Handke, Guibault, and Vallbe (2015)
|Author=Christian Handke; Lucie Guibault; Joan-Josep Vallbe
+
|Author=Handke, C.; Guibault, L.; Vallbe, J.;
 
|Title=Is Europe Falling Behind in Data Mining? Copyright's Impact on Data Mining in Academic Research
 
|Title=Is Europe Falling Behind in Data Mining? Copyright's Impact on Data Mining in Academic Research
 
|Year=2015
 
|Year=2015
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|Abstract=“This empirical paper discusses how copyright affects data mining (DM) by academic researchers. Based on bibliometric data, we show that where DM for academic research requires the express consent of rights holders: (1) DM makes up a significantly lower share of total research output; and (2) stronger rule-of-law is associated with less DM research. To our knowledge, this is the first time that an empirical study bears out a significant negative association between copyright protection and innovation.”
 
|Abstract=“This empirical paper discusses how copyright affects data mining (DM) by academic researchers. Based on bibliometric data, we show that where DM for academic research requires the express consent of rights holders: (1) DM makes up a significantly lower share of total research output; and (2) stronger rule-of-law is associated with less DM research. To our knowledge, this is the first time that an empirical study bears out a significant negative association between copyright protection and innovation.”
 
|Link=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2608513
 
|Link=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2608513
|Reference=Ginarte and Park (1997); Baker and Cunningham (2006); Tsai (2012); Fillipov (2014); Hargreaves et al. (2014);
+
|Reference=Ginarte and Park (1997);Baker and Cunningham (2006);Tsai (2012);Fillipov (2014);Hargreaves et al. (2014);
|Plain Text Proposition=Data-mining based articles are more common in countries with where data-mining is “probably allowed” under copyright law, suggesting a more permissive jurisdiction is more likely to have more data-mining based research. Furthermore, countries with high data-mining article outputs also tend to have larger total research output.  
+
|Plain Text Proposition=Data-mining based articles are more common in countries with where data-mining is “probably allowed” under copyright law, suggesting a more permissive jurisdiction is more likely to have more data-mining based research. Furthermore, countries with high data-mining article outputs also tend to have larger total research output. Countries in which data-mining is most likely not allowed, or definitely not allowed, have a lower output of data-mining based articles. Similarly, countries with stronger adherence to the rule of law have less data-mining based research outputs. As this leads to stronger enforcement the authors note that this, combined with copyright legislation which does not clearly permit data-mining, reduces overall data-mining outputs.As EU/EEA Member states have less permissive copyright laws regarding data-mining usage, the authors suggest that there is overall weaker performance  from these states comparatively. This may lead data-mining practitioners to base their activities in other jurisdictions, so that they have reassurance of the legality of their activities.
 
+
|FundamentalIssue=1. Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare,5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)
Countries in which data-mining is most likely not allowed, or definitely not allowed, have a lower output of data-mining based articles. Similarly, countries with stronger adherence to the rule of law have less data-mining based research outputs. As this leads to stronger enforcement the authors note that this, combined with copyright legislation which does not clearly permit data-mining, reduces overall data-mining outputs.
+
|EvidenceBasedPolicy=B. Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction)
 
 
As EU/EEA Member states have less permissive copyright laws regarding data-mining usage, the authors suggest that there is overall weaker performance  from these states comparatively. This may lead data-mining practitioners to base their activities in other jurisdictions, so that they have reassurance of the legality of their activities.
 
|FundamentalIssue=1. Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare, 5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media),
 
|EvidenceBasedPolicy=B. Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction),
 
 
|Discipline=D23: Organizational Behavior • Transaction Costs • Property Rights, K11: Property Law, L86: Information and Internet Services • Computer Software, O34: Intellectual Property and Intellectual Capital
 
|Discipline=D23: Organizational Behavior • Transaction Costs • Property Rights, K11: Property Law, L86: Information and Internet Services • Computer Software, O34: Intellectual Property and Intellectual Capital
 
|Intervention-Response=The authors suggest that the benefits in generating information goods through legalising data-mining outweigh the potential cons (such as private firms’ loss of exclusive control over valuable data). As such, copyright exceptions in the EU should be tailored to enable data-mining, as this appears to benefit research output overall.
 
|Intervention-Response=The authors suggest that the benefits in generating information goods through legalising data-mining outweigh the potential cons (such as private firms’ loss of exclusive control over valuable data). As such, copyright exceptions in the EU should be tailored to enable data-mining, as this appears to benefit research output overall.
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|Method of Analysis=Regression Analysis
 
|Method of Analysis=Regression Analysis
 
|Industry=Publishing of books, periodicals and other publishing;
 
|Industry=Publishing of books, periodicals and other publishing;
|Country=Global; Europe;
+
|Country=Global;Europe;
 
|Cross-country=Yes
 
|Cross-country=Yes
 
|Comparative=Yes
 
|Comparative=Yes
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|Literature review=No
 
|Literature review=No
 
}}
 
}}
|Dataset=
 
 
}}
 
}}

Latest revision as of 08:33, 25 May 2020

Advertising Architectural Publishing of books, periodicals and other publishing Programming and broadcasting Computer programming Computer consultancy Creative, arts and entertainment Cultural education Libraries, archives, museums and other cultural activities

Film and motion pictures Sound recording and music publishing Photographic activities PR and communication Software publishing Video game publishing Specialised design Television programmes Translation and interpretation

1. Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare 2. Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)? 3. Harmony of interest assumption between authors and publishers (creators and producers/investors) 4. Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption) 5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)

A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right) B. Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction) C. Mass digitisation/orphan works (non-use; extended collective licensing) D. Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability) E. Fair remuneration (levies; copyright contracts) F. Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness)

Source Details

Handke, Guibault, and Vallbe (2015)
Title: Is Europe Falling Behind in Data Mining? Copyright's Impact on Data Mining in Academic Research
Author(s): Handke, C., Guibault, L., Vallbe, J.
Year: 2015
Citation: Handke, C., Guibault, L. and Vallbé, J. Is Europe Falling Behind in Data Mining? Copyright's Impact on Data Mining in Academic Research. Available at SSRN: https://ssrn.com/abstract=2608513 or http://dx.doi.org/10.2139/ssrn.2608513
Link(s): Open Access
Key Related Studies:
Discipline:
Linked by:
About the Data
Data Description: The research concerns an analysis of bibliometric data (obtained from Thomson Reuter’s Web of Science) from 42 large economies, including the 15 largest EU Member States. The data gathered spans the years 1992-2014. In this scenario, the output of research which requires data-mining, and total researcher output are the dependent variables, and the copyright law practices in each jurisdiction and the independent variables. GDP per capita, country population size, and the level of rule of law were used as control variables.
Data Type: Primary data
Secondary Data Sources:
Data Collection Methods:
Data Analysis Methods:
Industry(ies):
Country(ies):
Cross Country Study?: Yes
Comparative Study?: Yes
Literature review?: No
Government or policy study?: No
Time Period(s) of Collection:
  • 1992-2014
Funder(s):

Abstract

“This empirical paper discusses how copyright affects data mining (DM) by academic researchers. Based on bibliometric data, we show that where DM for academic research requires the express consent of rights holders: (1) DM makes up a significantly lower share of total research output; and (2) stronger rule-of-law is associated with less DM research. To our knowledge, this is the first time that an empirical study bears out a significant negative association between copyright protection and innovation.”

Main Results of the Study

Data-mining based articles are more common in countries with where data-mining is “probably allowed” under copyright law, suggesting a more permissive jurisdiction is more likely to have more data-mining based research. Furthermore, countries with high data-mining article outputs also tend to have larger total research output. Countries in which data-mining is most likely not allowed, or definitely not allowed, have a lower output of data-mining based articles. Similarly, countries with stronger adherence to the rule of law have less data-mining based research outputs. As this leads to stronger enforcement the authors note that this, combined with copyright legislation which does not clearly permit data-mining, reduces overall data-mining outputs.As EU/EEA Member states have less permissive copyright laws regarding data-mining usage, the authors suggest that there is overall weaker performance from these states comparatively. This may lead data-mining practitioners to base their activities in other jurisdictions, so that they have reassurance of the legality of their activities.

Policy Implications as Stated By Author

The authors suggest that the benefits in generating information goods through legalising data-mining outweigh the potential cons (such as private firms’ loss of exclusive control over valuable data). As such, copyright exceptions in the EU should be tailored to enable data-mining, as this appears to benefit research output overall.


Coverage of Study

Coverage of Fundamental Issues
Issue Included within Study
Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare
Green-tick.png
Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)?
Harmony of interest assumption between authors and publishers (creators and producers/investors)
Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption)
Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)
Green-tick.png
Coverage of Evidence Based Policies
Issue Included within Study
Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right)
Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction)
Green-tick.png
Mass digitisation/orphan works (non-use; extended collective licensing)
Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability)
Fair remuneration (levies; copyright contracts)
Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness)

Datasets

{{{Dataset}}}