Collective Reasoning over Shared Concepts for the Linguistic Atlas of Sicily
- Autori: Pirrone, D.; Russo, G.; Gentile, A.; Pirrone, R.
- Anno di pubblicazione: 2013
- Tipologia: Capitolo o Saggio (Capitolo o saggio)
- Parole Chiave: ALS,ethnologic research, sociolinguistic research, Linguistic Atlas of Sicily, collective reasoning,shared concepts, Data integration, Social interaction Search engine,Emergent knowledge, Sociolinguistic Spoken Transcription, Linguistic annotation, Linguistic Phenomena, Collective intelligence, Information retrieval, Audio analysis, Wavesurfer, Collective Knowledge System, information exchange, Knowledge Discovery in Database, Linguistic framework, Interviews, Biographic information, Meta-linguistic information, Social characterization, Statistic Information,Diatopia,Filologiche,iBatis framework, spectrogram analysis,Markup language, Geographic information system, Pronunciation, Linguistic tools, Data management, SAX builder, Results dissemination, Geo-localized information,data exploration, geographically referenced visualization
- OA Link: http://hdl.handle.net/10447/95161
In this work, collective intelligence principles are applied in the context of the Linguistic Atlas of Sicily, an interdisciplinary research focusing on the study of the Italian language as it is spoken in Sicily, and its correlation with the Sicilian dialect and other regional varieties spoken in Sicily. The project has been developed over the past two decades and includes a complex information system supporting linguistic research; recently it has grown to allow research scientists to cooperate in an inte-grated environment to produce signiﬁcant scientiﬁc advances in the ﬁeld of ethnologic and sociolinguistic research. An interoperable infrastruc-ture was implemented and organized to allow exchange of information and knowledge between researchers providing tools and methodologies to allow collective reasoning over shared concepts. The project uses dif-ferent types of data (structured, unstructured, multimedia) that require tight data integration and interoperability. Additionally, the framework allows for data aggregation into shared concepts that can be exchanged between researchers and constitute a common knowledge base for the entire research community of the ALS.