Title
Multiple-source Data Collection and Processing into a Graph Database Supporting Cultural Heritage Applications
Abstract
AbstractThe continuous growth of available resources on the web, both in the form of Linked Open Data and on Social Networks, provides an important opportunity to gather information concerning specific kinds of touristic activities like, for example, cultural tourism, eco-tourism, bike-tourism, and so on. Both decision makers and tourists can take advantage from these data, as demonstrated by previous works, with institutional actors foreseeing an increase in the use of this data to substitute other time-consuming and expensive approaches. However, managing multiple sources built with different goals and structures is not straightforward, so specific design choices must be made when assembling this kind of information. Graph databases represent an ideal way to combine multiple-source data but, to be successful, strategies accounting for inconsistencies and format differences have to be defined to support coherent analysis. Also, the continuously changing nature of crowd-sourced data makes it difficult, for the research community, to compare technological approaches to the different tasks that are linked to cultural heritage, from recommendation to management. To support the research effort in this direction, we describe the data ingestion and enrichment procedure we followed to organise knowledge coming from three different sources, namely Wikidata, Wikipedia, and Flickr, into a single, application-oriented, resource organised as a graph database. We present the potential use of this resource to perform multiple source analyses targeting the specific case of cultural tourism on a nationwide scale, and we propose its use as a shared benchmark for technological applications designed to support optimal management of cultural resources.
Year
DOI
Venue
2021
10.1145/3465741
Journal on Computing and Cultural Heritage
Keywords
DocType
Volume
Graph databases, multiple-source datasets, linked open data, social networks
Journal
14
Issue
ISSN
Citations 
4
1556-4673
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Antonio Origlia15013.99
Silvia Rossi210519.81
S. Di Martino314510.03
Francesco Cutugno47618.01
Maria Laura Chiacchio500.34