ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-04072019-190303


Tipo di tesi
Tesi di laurea magistrale
Autore
ALLORI, ILARIA
URN
etd-04072019-190303
Titolo
Building up a Census of Public Research Organisations. Data Integration and Analysis
Dipartimento
INGEGNERIA DELL'ENERGIA, DEI SISTEMI, DEL TERRITORIO E DELLE COSTRUZIONI
Corso di studi
INGEGNERIA GESTIONALE
Relatori
relatore Prof. Bonaccorsi, Andrea
relatore Dott. Chiarello, Filippo
Parole chiave
  • Bibliometrics
  • Database
  • Public Research Organisations
  • Data Analysis
  • Data Integration
Data inizio appello
02/05/2019
Consultabilità
Non consultabile
Data di rilascio
02/05/2089
Riassunto
The aim of this work is to provide a census of Public Research Organisations in the European Union (EU-27 formation) plus EFTA countries, that is a comprehensive and exhaustive list of entities which depicts the research framework of the reference area, in the analysed time window (2014-2018). The resulting database consists of a list of more than 6000 entities (affiliations), each one of them univocally associated with detailed geographical information, such as the city where the entity runs its activities followed by a NUTS-2 classification.
The novelty of this work resides in the scale of the analysis and in the level of detail: previous research works led to much smaller datasets on a higher level of aggregation, often providing only geographical information for the organisations’ main site (head-quarters). A bottom-up approach has been undertaken in order to create the PROs database, which implied the merging and validation of data from different sources, requiring significant cleaning and tidying efforts.
A database containing geographical information about entities at the lowest level of aggregation possible opens up a new whole spectrum of possibilities research-wise: this present work focuses, in particular, on answering bibliometric-related research questions. The bibliometric data have been retrieved from Scopus through R coding, providing for each combination of year and main field, the number of publications and citations of a given organisation; data have been then wrangled, visualised and analysed using a diverse set of tools, including RStudio software.
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