Graph-based data models have recently gained much popularity as powerful means for data representation in several database application areas. Notable examples of application domains where data is naturally represented in graph-based form are knowledge bases, biological and chemical databases, Web-scattered data, healthcare, personal information management (PIM), enterprise information management (EIM) systems, online mapping/routing services, and social networks, just to mention a few. The heterogeneity, complexity and largeness of contents that characterize datasets in these fields unquestionably make the querying experience a really challenging task. This special issue of the Journal of Computer and System Sciences follows the 2013 and 2014 editions of the International Workshop on Querying Graph Structured Data (GraphQ), which were co-located with the International Conference on Extending Database Technology and were held in Genoa, Italy and in Athens, Greece, respectively. The two editions of the workshop attracted a large world-wide audience of researchers and professionals, and yielded several excellent presentations exploring how to effectively and efficiently support graph queries in different application domains. This special issue includes a shortlist of selected contributions that were extended to provide deeper investigations along three main research directions: (1) graph query answering; (2) graph query processing; (3) graph data dynamics.
Journal of Computer and System Sciences Special Issue on Query Answering on Graph-Structured Data / Mandreoli, Federica; Martoglia, Riccardo; Penzo, Wilma. - In: JOURNAL OF COMPUTER AND SYSTEM SCIENCES. - ISSN 0022-0000. - STAMPA. - 82:1(2016), pp. 1-2. [10.1016/j.jcss.2015.09.001]
Journal of Computer and System Sciences Special Issue on Query Answering on Graph-Structured Data
MANDREOLI, Federica;MARTOGLIA, Riccardo;
2016
Abstract
Graph-based data models have recently gained much popularity as powerful means for data representation in several database application areas. Notable examples of application domains where data is naturally represented in graph-based form are knowledge bases, biological and chemical databases, Web-scattered data, healthcare, personal information management (PIM), enterprise information management (EIM) systems, online mapping/routing services, and social networks, just to mention a few. The heterogeneity, complexity and largeness of contents that characterize datasets in these fields unquestionably make the querying experience a really challenging task. This special issue of the Journal of Computer and System Sciences follows the 2013 and 2014 editions of the International Workshop on Querying Graph Structured Data (GraphQ), which were co-located with the International Conference on Extending Database Technology and were held in Genoa, Italy and in Athens, Greece, respectively. The two editions of the workshop attracted a large world-wide audience of researchers and professionals, and yielded several excellent presentations exploring how to effectively and efficiently support graph queries in different application domains. This special issue includes a shortlist of selected contributions that were extended to provide deeper investigations along three main research directions: (1) graph query answering; (2) graph query processing; (3) graph data dynamics.Pubblicazioni consigliate
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