Archivist in the machine: paradata for AI-based automation in the archives

IF 1.4 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

ARCHIVAL SCIENCE Pub Date : 2023-01-20 DOI:10.1007/s10502-023-09408-8

Jeremy Davet, Babak Hamidzadeh, Patricia Franks

{"title":"Archivist in the machine: paradata for AI-based automation in the archives","authors":"Jeremy Davet, Babak Hamidzadeh, Patricia Franks","doi":"10.1007/s10502-023-09408-8","DOIUrl":null,"url":null,"abstract":"<div><p>Recently introduced into the archival sphere, ‘paradata’ is a conceptual framework for defining the character of information resource processing. (Davet J, Hamidzadeh B, Franks P, Bunn J (2022) Tracking the functions of AI as paradata & pursuing archival accountability. In: Archiving 2022: Final Programs and Proceedings, 7-10 June 2022. Society for imaging science and technology, Springfield, VA, USA, pp 83–88) While it need not be applied exclusively to artificial intelligence-based automated systems, paradata can be, should be, and is currently used to explicate the function of AI in the archives. The use of paradata in relation to AI can help ensure that archival ethical principles continue to be honored in an age of increasing automation. This paper summarizes the theoretical background of paradata, documentation created during recent experiments with machine learning-based AI which gestures toward the varieties of paradata already being collected by researchers, and some of the factors which condition paradata’s use. A few currently available data structures for the representation and display of paradata are evaluated, with an eye toward their suitability for different stakeholder groups. Future directions for theoretical and practical research are suggested.</p></div>","PeriodicalId":46131,"journal":{"name":"ARCHIVAL SCIENCE","volume":"23 2","pages":"275 - 295"},"PeriodicalIF":1.4000,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ARCHIVAL SCIENCE","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s10502-023-09408-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}

引用次数: 0

Abstract

Recently introduced into the archival sphere, ‘paradata’ is a conceptual framework for defining the character of information resource processing. (Davet J, Hamidzadeh B, Franks P, Bunn J (2022) Tracking the functions of AI as paradata & pursuing archival accountability. In: Archiving 2022: Final Programs and Proceedings, 7-10 June 2022. Society for imaging science and technology, Springfield, VA, USA, pp 83–88) While it need not be applied exclusively to artificial intelligence-based automated systems, paradata can be, should be, and is currently used to explicate the function of AI in the archives. The use of paradata in relation to AI can help ensure that archival ethical principles continue to be honored in an age of increasing automation. This paper summarizes the theoretical background of paradata, documentation created during recent experiments with machine learning-based AI which gestures toward the varieties of paradata already being collected by researchers, and some of the factors which condition paradata’s use. A few currently available data structures for the representation and display of paradata are evaluated, with an eye toward their suitability for different stakeholder groups. Future directions for theoretical and practical research are suggested.

查看原文本刊更多论文

机器中的档案管理员:基于人工智能的档案自动化的典范

最近引入档案领域的“paradata”是一个定义信息资源处理特征的概念框架。（Davet J，Hamidzadeh B，Franks P，Bunn J（2022）追踪人工智能作为paradata的功能&；追求档案问责制。2022年6月7日至10日，《2022年归档：最终计划和论文集》。成像科学与技术学会，美国弗吉尼亚州斯普林菲尔德，第83–88页）虽然它不需要专门应用于基于人工智能的自动化系统，但paradata可以、应该并且目前正在用于解释档案中人工智能的功能。与人工智能相关的paradata的使用有助于确保档案伦理原则在日益自动化的时代继续得到尊重。本文总结了paradata的理论背景、最近使用基于机器学习的人工智能进行实验时创建的文件，这些文件指向了研究人员已经收集的各种paradata，以及制约paradata使用的一些因素。评估了目前用于表示和显示paradata的一些可用数据结构，着眼于它们对不同利益相关者群体的适用性。提出了今后理论和实践研究的方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

ARCHIVAL SCIENCE INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

2.70

自引率

18.20%

发文量

期刊介绍： Archival Science promotes the development of archival science as an autonomous scientific discipline. The journal covers all aspects of archival science theory, methodology, and practice. Moreover, it investigates different cultural approaches to creation, management and provision of access to archives, records, and data. It also seeks to promote the exchange and comparison of concepts, views and attitudes related to recordkeeping issues around the world.Archival Science''s approach is integrated, interdisciplinary, and intercultural. Its scope encompasses the entire field of recorded process-related information, analyzed in terms of form, structure, and context. To meet its objectives, the journal draws from scientific disciplines that deal with the function of records and the way they are created, preserved, and retrieved; the context in which information is generated, managed, and used; and the social and cultural environment of records creation at different times and places.Covers all aspects of archival science theory, methodology, and practiceInvestigates different cultural approaches to creation, management and provision of access to archives, records, and dataPromotes the exchange and comparison of concepts, views, and attitudes related to recordkeeping issues around the worldAddresses the entire field of recorded process-related information, analyzed in terms of form, structure, and context