Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Conference object . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Conference object . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2022
License: CC BY
Data sources: ZENODO
versions View all 2 versions
addClaim

Semantic Storytelling: the RESTORE project vision

Authors: Coradeschi, Francesco; Degl'Innocenti, Emiliano; Di Meo, Carmen; Sanesi, Maurizio; Spadi, Alessia; Spinelli, Federica; Canova, Leonardo;

Semantic Storytelling: the RESTORE project vision

Abstract

In the context of sharing knowledge, “stories” have long played an important role, especially in the field of cultural heritage, where available collections can tell endless stories to their audiences. Nowadays, an enormous amount of information is accessible to everyone and in every moment. It is therefore necessary to optimize the use of tools made available by technological innovation and to set up systems for the transmission of knowledge that can get people closer to the world of culture, too often seen as antiquated and specialized, and that can provide additional value to any artistic and cultural initiative. With the advent of the Semantic Web, large amounts of structured and interconnected data related to various and different kinds of resources in scientific domains have become freely available. Cultural heritage institutions also produce great quantities of data, generating links and therefore enabling connections in a linked open data context. Linked Open Data are the sources from which data scientists can extract the relevant knowledge to engine stories and create visual representation of copious amounts of information to be presented to the public. However, this process should involve both CH/SSH specialists and data analysts. In fact, data without context can’t tell any story and result neither understandable nor interesting; both the theoretical knowledge of the resources and the mathematical introspection are required to create a successful and truthful story. The RESTORE (smart access for digital heritage and memory) project will be presented in this contribution to demonstrate the approach used to manage data from multiple contexts for application in an integrated environment.The aim of the project is to develop good praxis and contents for the innovative use of historical documentation in a multidisciplinary environment, promoting understanding and encouraging its re-use by researchers, operators active on cultural and creative industries and citizens (citizen science). The data management methods implemented by the project make it possible to enable collections of data to describe a story, only through these processes it is possible to tell stories that otherwise would not be told. The project consortium, coordinated by the Istituto Opera del Vocabolario Italiano of the Italian CNR (National Research Council of Italy), includes national Cultural Heritage institutes, such as the State Archives and the Museum of Palazzo Pretorio in Prato and the Archival and Bibliographic Superintendency of Tuscany, and the SPACE SpA software company. The project - co-financed by the Regione Toscana - has its main purpose in the recovery, integration and accessibility of data and digital objects collected by partner, in order to build a knowledge base made of information regarding the history of the city and of its civic institutions, the development of its economic and entrepreneurial system, the role of women in the development of a welfare state and network. Starting a local history approach, it is nonetheless possible to broaden the focus from the local dimension to reconstruct a significant part of the history of European and Mediterranean cities of the 14th century, including commercial and economical aspects.

Keywords

Data communities, SSHOC, Ontologies, Storytelling, Cultural Heritage, Interoperability, RESTORE, DARIAH

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green