This paper illustrates EFESTO, a mashup platform designed to enable end users to explore information by creating interactive workspaces. Within a Web composition environment, end users dynamically create “live mashups” where relevant information, extracted from heterogeneous data sources - 6745128the Linked Open Data – is integrated according to visually defined queries. Visualizations of the resulting data sets can be flexibly shaped-up at runtime. Functions, exposed by local or remote services, also allow users to manipulate the resulting data depending on their situational needs. With respect to other mashup platforms, EFESTO privileges visual composition paradigms that accommodate the end-user mental model for a lightweight data integration within Web workspaces.
EFESTO: A platform for the end-user development of interactive workspaces for data exploration / Desolda, Giuseppe; Ardito, Carmelo; Matera, Maristella (COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE). - In: Rapid Mashup Development Tools : First International Rapid Mashup Challenge, RMC 2015 [...]. Revised Selected Papers / [a cura di] Florian Daniel; Cesare Pautasso. - STAMPA. - Cham, CH : Springer, 2016. - ISBN 978-3-319-28726-3. - pp. 63-81 [10.1007/978-3-319-28727-0_5]
EFESTO: A platform for the end-user development of interactive workspaces for data exploration
Carmelo Ardito;
2016-01-01
Abstract
This paper illustrates EFESTO, a mashup platform designed to enable end users to explore information by creating interactive workspaces. Within a Web composition environment, end users dynamically create “live mashups” where relevant information, extracted from heterogeneous data sources - 6745128the Linked Open Data – is integrated according to visually defined queries. Visualizations of the resulting data sets can be flexibly shaped-up at runtime. Functions, exposed by local or remote services, also allow users to manipulate the resulting data depending on their situational needs. With respect to other mashup platforms, EFESTO privileges visual composition paradigms that accommodate the end-user mental model for a lightweight data integration within Web workspaces.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
