Project deliverable Open Access

Deliverable 1.3: Report on data gathering V.1

Sacco, Pier Luigi; De Domenico, Manlio; Artime, Oriol; Tartari, Maria; Pilati, Federico

Böhm, Katinka; Irollo, Alba; Niccolucci, Franco; Pajares, Sonsoles; Bočytė, Rasa; Uboldi, Sara; Pedrini, Sabrina

This Deliverable aims to briefly describe the data collection processes, the datasets gathered and the preliminary data analysis on users’ behavioural changes that were carried out by the WP1 working group. The inDICEs data collection processed and/or stored within the first 12 months of the project consists of: 

a) data analyzed as part of the inDICEs participatory platform, where results are made available through the Open Observatory

b) data of relevance provided by third-parties such as 

  • Enumerate
  • Nemo
  • Eurostat
  • State of the commons
  • United Nations Conference on Trade and Developmen
  • Digital Economy and Society Index
  • EU open data portal

c) online content gathered continuously, made accessible by means of the Visual Analytics Dashboard that covers:

  • Online news and web sources
  • Twitter posts
  • Youtube videos
  • Facebook pages

d) FBK collected on-line datasets on cultural production, from the following sources:

  • Wikipedia
  • Tiktok
  • Deviantart
  • AllTheater
  • IMDB

and was gathered with the purpose to:

a) monitor and analyze the state of cultural digitization via WLT analytical tools and through the Visual Analytical Dashboard, configured for culture-based web sources (news, websites, social networks, blogs, forums) and with domain-relevant keywords according to a series of pre-sets and new indicators [as described in Deliverable D1.1].

b) stimulate behavioural changes in the users of participatory platforms in order to favour production and access. To understand how this process of collective cultural production works, inDICEs chose Wikipedia as its first case study, in order to extract new useful indicators to fill the open Repository available for single researchers and institutes.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 870792.
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