  Purpose: The purpose of this paper is to propose a tool that generates
authority files to be integrated with linked data by means of learning rules.
AUTHORIS is software developed to enhance authority control and information
exchange among bibliographic and non-bibliographic entities.
  Design / methodology / approach: The article analyzes different methods
previously developed for authority control as well as IFLA and ALA standards
for managing bibliographic records. Semantic Web technologies are also
evaluated. AUTHORIS relies on Drupal and incorporates the protocols of Dublin
Core, SIOC, SKOS and FOAF. The tool has also taken into account the
obsolescence of MARC and its substitution by FRBR and RDA. Its effectiveness
was evaluated applying a learning test proposed by RDA. Over 80 percent of the
actions were carried out correctly.
  Findings: The use of learning rules and the facilities of linked data make it
easier for information organizations to reutilize products for authority
control and distribute them in a fair and efficient manner.
  Research limitations / implications: The ISAD-G records were the ones
presenting most errors. EAD was found to be second in the number of errors
produced. The rest of the formats --MARC 21, Dublin Core, FRAD, RDF, OWL, XBRL
and FOAF-- showed fewer than 20 errors in total.
  Practical implications: AUTHORIS offers institutions the means of sharing
data with a high level of stability, helping to detect records that are
duplicated and contributing to lexical disambiguation and data enrichment.
  Originality / value: The software combines the facilities of linked data, the
potency of the algorithms for converting bibliographic data, and the precision
of learning rules.
