scholarly journals Empirical Research on Web Harvesting in the Process of Text and Data Mining in National Libraries of EU Member States

2020 ◽  
Vol 10 (01) ◽  
pp. 88-112
Author(s):  
Marinos Papadopoulos ◽  
Maria Botti ◽  
M. A. Paraskevi (Vicky) Ganatsiou ◽  
Christos Zampakolas
Keyword(s):  
Data Mining ◽  
Empirical Research ◽  
Member States ◽  
Eu Member States ◽  
National Libraries ◽  
Text And Data Mining ◽  
Web Harvesting

scholarly journals Text and Data Mining in Directive 2019/790/EU Enhancing Web-Harvesting and Web-Archiving in Libraries and Archives

2019 ◽  
Vol 09 (03) ◽  
pp. 369-395
Author(s):  
Μaria Bottis ◽  
Marinos Papadopoulos ◽  
Christos Zampakolas ◽  
Paraskevi Ganatsiou
Keyword(s):  
Data Mining ◽  
Web Archiving ◽  
Text And Data Mining ◽  
Web Harvesting

Article 3—Text and Data Mining for the Purposes of Scientific Research

2021 ◽  
pp. 25-59
Author(s):  
Eleonora Rosati
Keyword(s):  
Data Mining ◽  
Best Practices ◽  
Cultural Heritage ◽  
Subject Matter ◽  
Scientific Research ◽  
Single Market ◽  
Member States ◽  
Research Organisations ◽  
Text And Data Mining ◽  
Copyright Directive

This chapter focuses on the laws about text and data mining for scientific researchstipulated under Article 3 of the Directive 2019/790 or copyright directive of the Digital Single Market in Europe. It examines the legislation that require Member States to provide an exception for reproductions and extractions made by research organisations and cultural heritage institutions on text and data mining of works or other subject matter for the purposes of scientific research. It also stresses that copies of works or other subject matter on text and data mining will be stored with an appropriate level of security and retained for the purposes of scientific research. The chapter talks about rightholders, which are allowed to apply measures to ensure the security and integrity of the networks and databases. It mentions Member States that encourage rightholders, research organisations, and cultural heritage institutions to define commonly agreed best practices concerning the application of the obligation and measures on text and data mining.

Article 4—Exception or Limitation for Text and Data Mining

2021 ◽  
pp. 60-92
Author(s):  
Eleonora Rosati
Keyword(s):  
Data Mining ◽  
Cultural Heritage ◽  
Subject Matter ◽  
Digital Technologies ◽  
Internal Market ◽  
Member States ◽  
Exceptions And Limitations ◽  
Fair Balance ◽  
Text And Data Mining ◽  
Copyright Directive

This chapter focuses on Article 4 of Directive 2019/790, the European copyright directive, which require Member States to provide for an exception or limitation for reproductions and extractions of works and other subject matter for the purposes of text and data mining. It talks about digital technologies that permit new types of uses that are not clearly covered by the existing Union rules on exceptions and limitations in the fields of research, innovation, education, and preservation of cultural heritage. It also describes the optional nature of exceptions and limitations that could negatively impact the functioning of the internal market. The chapter discusses the exceptions and limitations provided in Directive 2019/790 that seek to achieve a fair balance between the rights and interests of authors, other rightholders, and users. It clarifies that text and data mining can be carried out in relation to mere facts or data that are not protected by copyright.

scholarly journals Social Cohesion in the Time of Crisis: An Empirical Research on EU Member States

2017 ◽  
Vol 4 (3) ◽  
pp. 229-248 ◽  
Author(s):  
Felice Addeo ◽  
Paolo Diana ◽  
Gianmaria Bottoni ◽  
Maria Esposito
Keyword(s):  
Empirical Research ◽  
Social Cohesion ◽  
Member States ◽  
Eu Member States

Evaluation of the Prosperity Levels of EU and EU Candidate Countries by Clustering and PSI Method

2020 ◽  
pp. 81-98
Author(s):  
İbrahim Budak ◽  
Günay Kiliç ◽  
Arzu Organ
Keyword(s):  
Data Mining ◽  
European Union ◽  
Social Status ◽  
Clustering Analysis ◽  
The European Union ◽  
Member States ◽  
Data Mining Techniques ◽  
Eu Member States ◽  
Eu Candidate Countries ◽  
Psi Method

Although prosperity is often associated with the word wealth, it also includes other factors that may be independent of wealth, such as happiness and health. The prosperity state can be defined as a developing, growing, wealth state and a successful social status. Increasing the levels of prosperity is a goal of states. States can create communities in cooperation with other states to improve their level of prosperity. One of these communities is the European Union (EU), which is established by European states. This chapter evaluates the position of EU member states and EU candidate countries' prosperity levels compared to world states. In the study, 2018 Legatum Institute prosperity index of 149 countries was used. These countries are divided into groups by using clustering analysis from data mining techniques. The countries are evaluated using the Preference Selective Index (PSI).

Doing Everything You Can, but Not (yet) Getting it Right: Challenges to Brussels' Great Expectations for Water Quality1

2017 ◽  
Vol 1 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Franca Angela Buelow
Keyword(s):  
Water Status ◽  
Organizational Structures ◽  
Eu Water Framework Directive ◽  
The European Union ◽  
Member States ◽  
Great Expectations ◽  
Eu Member States ◽  
European Water ◽  
Improve Water Quality ◽  
Governance Architecture

To arrive at a good status of all European water bodies is the main objective of the European Union (EU) Water Framework Directive (WFD). Since its adoption in 2000, the policy has fundamentally changed the institutional, procedural and organizational structures of Member States' water management, leading to an Europeanization of national legislation and decision-making structures. The case of WFD implementation in Schleswig-Holstein is an example of the policy's highly innovative governance architecture that unfortunately is not (yet) able to take that one last hurdle: to improve water quality and establish a good water status across EU Member States by 2015 or 2027.

BIOECONOMY DEVELOPMENT POTENTIAL BASED ON MORE EFFICIENT LAND USE IN THE EU

2015 ◽  
Author(s):  
Irina PILVERE ◽  
Aleksejs NIPERS ◽  
Bartosz MICKIEWICZ
Keyword(s):  
Green Growth ◽  
Member States ◽  
Eu Member States ◽  
Growing Stock ◽  
Europe 2020 ◽  
Europe 2020 Strategy ◽  
Analysis And Synthesis ◽  
Key Industries ◽  
The Eu ◽  
Production Resource

Europe 2020 Strategy highlights bioeconomy as a key element for smart and green growth in Europe. Bioeconomy in this case includes agriculture, forestry, fisheries, food and pulp and paper production, parts of chemical, biotechnological and energy industries and plays an important role in the EU’s economy. The growth of key industries of bioeconomy – agriculture and forestry – highly depends on an efficient and productive use of land as a production resource. The overall aim of this paper is to evaluate opportunities for development of the main sectors of bioeconomy (agriculture and forestry) in the EU based on the available resources of land. To achieve this aim, several methods were used – monographic, analysis and synthesis, induction and deduction, statistical analysis methods. The findings show that it is possible to improve the use of land in the EU Member States. If all the Member States reached the average EU level, agricultural products worth EUR 77 bln would be annually additionally produced, which is 19 % more than in 2014, and an extra 5 billion m3 volume of forest growing stock would be gained, which is 20 % more than in 2010.

Vocational Education in the New EU Member States

2007 ◽  
Author(s):  
Mary Canning ◽  
Martin Godfrey ◽  
Dorota Holzer-Zelazewska
Keyword(s):  
Vocational Education ◽  
Member States ◽  
Eu Member States ◽  
New Eu Member States
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