{"title":"使用网络分析评估大规模数字化","authors":"Emily Lapworth","doi":"10.1108/DLP-09-2020-0095","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe purpose of this study is to assess the use of digital collections created via the large-scale digitization of archival collections. The large-scale digitization method specifically examined is the reuse of archival description from finding aids to create digital collections that consist mainly of compound digital objects, equivalent to a folder of items, minimally described at the aggregate level. This paper compares Web analytics data for two large-scale digital collections and one digital collection with rich, item-level description.\n\n\nDesign/methodology/approach\nThis study analyzed one year of Web analytics for three digital collections. The main research question of this study is: Are digital collections of minimally described compound objects used less than digital collections of richly described single objects?\n\n\nFindings\nThis study found that the large-scale digital collections analyzed received less use than the traditional item-level collection, when examined at the item level. At the object level, the large-scale collections did not always receive less use than the traditional item-level collection.\n\n\nResearch limitations/implications\nThis study is limited to three different digital collections from one institution. Web analytics also represent a limited interpretation of “use.”\n\n\nPractical implications\nThis study presents a method for other institutions to assess their own large-scale digitization efforts and contributes to the profession’s understanding of the impact of large-scale digitization.\n\n\nOriginality/value\nThis paper is unique because it uses Web analytics to compare the use of large-scale digital collections to the use of traditional boutique digital collections.\n","PeriodicalId":438470,"journal":{"name":"Digit. Libr. Perspect.","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Assessing large-scale digitization using Web analytics\",\"authors\":\"Emily Lapworth\",\"doi\":\"10.1108/DLP-09-2020-0095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe purpose of this study is to assess the use of digital collections created via the large-scale digitization of archival collections. The large-scale digitization method specifically examined is the reuse of archival description from finding aids to create digital collections that consist mainly of compound digital objects, equivalent to a folder of items, minimally described at the aggregate level. This paper compares Web analytics data for two large-scale digital collections and one digital collection with rich, item-level description.\\n\\n\\nDesign/methodology/approach\\nThis study analyzed one year of Web analytics for three digital collections. The main research question of this study is: Are digital collections of minimally described compound objects used less than digital collections of richly described single objects?\\n\\n\\nFindings\\nThis study found that the large-scale digital collections analyzed received less use than the traditional item-level collection, when examined at the item level. At the object level, the large-scale collections did not always receive less use than the traditional item-level collection.\\n\\n\\nResearch limitations/implications\\nThis study is limited to three different digital collections from one institution. Web analytics also represent a limited interpretation of “use.”\\n\\n\\nPractical implications\\nThis study presents a method for other institutions to assess their own large-scale digitization efforts and contributes to the profession’s understanding of the impact of large-scale digitization.\\n\\n\\nOriginality/value\\nThis paper is unique because it uses Web analytics to compare the use of large-scale digital collections to the use of traditional boutique digital collections.\\n\",\"PeriodicalId\":438470,\"journal\":{\"name\":\"Digit. Libr. Perspect.\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digit. Libr. 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Assessing large-scale digitization using Web analytics
Purpose
The purpose of this study is to assess the use of digital collections created via the large-scale digitization of archival collections. The large-scale digitization method specifically examined is the reuse of archival description from finding aids to create digital collections that consist mainly of compound digital objects, equivalent to a folder of items, minimally described at the aggregate level. This paper compares Web analytics data for two large-scale digital collections and one digital collection with rich, item-level description.
Design/methodology/approach
This study analyzed one year of Web analytics for three digital collections. The main research question of this study is: Are digital collections of minimally described compound objects used less than digital collections of richly described single objects?
Findings
This study found that the large-scale digital collections analyzed received less use than the traditional item-level collection, when examined at the item level. At the object level, the large-scale collections did not always receive less use than the traditional item-level collection.
Research limitations/implications
This study is limited to three different digital collections from one institution. Web analytics also represent a limited interpretation of “use.”
Practical implications
This study presents a method for other institutions to assess their own large-scale digitization efforts and contributes to the profession’s understanding of the impact of large-scale digitization.
Originality/value
This paper is unique because it uses Web analytics to compare the use of large-scale digital collections to the use of traditional boutique digital collections.