A case study about the automatic creation of faceted class numbers for special topics starting from data available on the semantic web is described. The aim is to investigate two questions: 1) Is the automatic, quick, cost-effective, large-scale production of a Schedule of Colon Classification class numbers for literary classics possible?, and 2) More generally: which are the requirements for an automatic production of class numbers of a faceted scheme of classification? What kind of research is necessary to develop such a process? The case study focuses on data extracted from data.bnf.fr and on their reuse to get correct and complete Colon Classification class numbers for a sample of Italian literature writers (born from 1800 to 1900). The process of creation of class numbers starting from data identification and extraction, through their cleanup, transformation and translation in classified notation by means of Open Refine is presented. Case study results and their relevance for starting questions are discussed and research questions for possible future developments are identified.
From semantic web to faceted classification – a case study and five lines of future research
Bianchini, Carlo
2020-01-01
Abstract
A case study about the automatic creation of faceted class numbers for special topics starting from data available on the semantic web is described. The aim is to investigate two questions: 1) Is the automatic, quick, cost-effective, large-scale production of a Schedule of Colon Classification class numbers for literary classics possible?, and 2) More generally: which are the requirements for an automatic production of class numbers of a faceted scheme of classification? What kind of research is necessary to develop such a process? The case study focuses on data extracted from data.bnf.fr and on their reuse to get correct and complete Colon Classification class numbers for a sample of Italian literature writers (born from 1800 to 1900). The process of creation of class numbers starting from data identification and extraction, through their cleanup, transformation and translation in classified notation by means of Open Refine is presented. Case study results and their relevance for starting questions are discussed and research questions for possible future developments are identified.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
