DC FieldValueLanguage
dc.contributor.authorKanellopoulou - Botti, Maria-
dc.contributor.authorZampakolas, Christos-
dc.contributor.authorPapadopoulos, Marinos-
dc.contributor.authorGanatsiou, Paraskevi-
dc.date.accessioned2023-10-19T06:49:50Z-
dc.date.available2023-10-19T06:49:50Z-
dc.date.issued2019-
dc.identifier.otherT1wsRZ4AAAAJ:2osOgNQ5qMEC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/544-
dc.description.abstractText and Data Mining (hereinafter, TDM) issue for the purpose of scientific research or for any other purpose which is included in the provisions of the new EU Directive on Copyright in the Digital Single Market (hereinafter, DSM). TDM is a term that includes Web harvesting and Web Archiving activities. Web harvesting and archiving pertains to the processes of collecting from the web and archiving of works that reside on the Web. In the following analysis we will elaborate briefly upon provisions in EU Copyright law which were discussed during the proposal for a new Directive on Copyright in the DSM as well as provisions which are included in the text of art. 3 and art. 4 of the new Directive 2019/790/EU per TDM. In addition, the following analysis presents legislation in very few EU Member States which pertains to TDM and preceded the rulings of Directive 190 2019/790/EU. The most notable examples are the ones from the United Kingdom and Ireland, Germany, the Netherlands and France. The example of Australia is also presented later because it is one of the oldest and most successful worldwide. The National Library of Australia’s digital legal deposit is state of the art. The execution of TDM for Web harvesting and archiving of works found on the Internet is based on algorithmic applications and information technology. It is thus an automated computational process, the precision of which depends on the evolution of algorithms and the software used for their implementation. Later in this article we make a reference to the most commonly used algorithms used in libraries for crawling and harvesting of works found online as well as for analysing their content with the aim of discovering new scientific knowledge from their analysis. Finally, in the text of this article we will address General Data Protection Regulation (GDPR) issues that pertain to TDM and the data subjects whose works have been harvested and/or archived by a library deploying TDM.en_US
dc.language.isoenen_US
dc.relation.ispartofErasmus Law Reviewen_US
dc.sourceErasmus L. Rev. 12, 190, 2019-
dc.subjectWeb harvestingen_US
dc.subjectData analysisen_US
dc.subjectText & data miningen_US
dc.subjectTDMen_US
dc.subjectComputational texten_US
dc.titleText and Data Mining in the EU Acquis Communautaire Tinkering with TDM & Digital Legal Depositen_US
dc.typeArticleen_US
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume12en_US
dc.identifier.spage190en_US
dc.identifier.epage208en_US
dc.linkhttps://www.erasmuslawreview.nl/tijdschrift/ELR/2019/2/ELR-D-19-00024en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.countryGreeceen_US
item.openairetypeArticle-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0009-0004-3941-0725-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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