Authoris：语义Web中的权限控制工具
Authoris: a tool for authority control in the semantic web
摘要：
目的：本文的目的是提出一个工具，生成的权威文件，通过学习规则与链接的数据集成。CNOORIS是为加强书目和非书目实体之间的权威控制和信息交流而开发的软件。设计/方法/途径：本文分析了之前为权威控制开发的不同方法以及管理书目记录的IFLA和ALA标准。语义Web技术也进行了评估。CANORIS依赖于Drupal，并结合了都柏林核心，SIOC，SKOS和FOAF的协议。这一工具还考虑到机读目录已经过时，并被《财务报告准则》和《建议数据分析》所取代。其有效性进行了评估，采用RDA提出的学习测试。80%以上的行动都是正确的。调查结果：学习规则的使用和关联数据的便利使信息组织更容易重新利用产品进行权限控制，并以公平有效的方式分发产品。研究限制/影响：ISAD-G的记录是最错误的。EAD被发现在产生的错误数量上排名第二。其余的格式--MARC 21、都柏林核心、FRAD、RDF、OWL、XBRL和FOAF--总共显示了不到20个错误。实际影响：CANORIS为机构提供了高度稳定的数据共享手段，有助于检测重复记录，并有助于消除词汇歧义和丰富数据。创意/价值：该软件结合了链接数据的便利性、书目数据转换算法的有效性和学习规则的精确性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
