Levels of Curation, Appraisal, Digital Preservation and Reuse in Successful CoreTrustSeal Applications 2017-2023
收藏CESSDA2025-05-05 更新2025-05-24 收录
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CoreTrustSeal (https://www.coretrustseal.org) is an international non-profit organization offering a certification procedure for trustworthy digital repositories since 2017. To obtain certification, repositories complete an application via an online tool in which they provide background information about the repository as well as responses to the 16 CoreTrustSeal Requirements.
The successful applications are published in PDF documents whose structure and layout changed over time as the tool used to create them evolved. While the PDF format ensures that the published information remains fixed and stable, it also means that processing and analyzing the candidates’ responses other than intellectually is very difficult as they are largely unstructured text locked in PDFs. Therefore, tracking developments in the responses over time and across Requirements versions is difficult.
To address this issue, continuing and expanding previous work by Lindlar and Rudnik, this dataset codes information from the responses that all successful CoreTrustSeal applicants between 2017-2023 provided to the requirements dealing with Appraisal, Preservation Plan, and Data Reuse. In addition, provided background information (Repository type and Level of Curation) were coded.
Finally, all URLs provided in the responses to the mentioned requirements were checked using a Python script to determine the extent of evidence no longer accessible due to link rot.
CoreTrustSeal(https://www.coretrustseal.org)是一家国际性非营利组织,自2017年起为可信数字仓储提供认证流程。若要获得认证,仓储方需通过在线工具提交申请,提供仓储背景信息,并回复16项CoreTrustSeal认证要求。
成功通过审核的申请将以PDF文档形式发布,随着用于生成此类文档的工具迭代更新,这些PDF的结构与版式也随时间发生变化。尽管PDF格式确保了发布信息的固定性与稳定性,但这也意味着除人工研读外,对申请者的回复进行处理与分析极为困难——因为这些回复大多是被锁定在PDF中的非结构化文本。因此,追踪不同时间节点及不同版本认证要求下的回复进展颇具挑战。
为解决这一问题,本数据集延续并拓展了Lindlar与Rudnik的前期研究工作,对2017至2023年间所有通过CoreTrustSeal认证的申请者在评估、保存计划与数据复用相关认证要求下提交的回复信息进行编码。此外,申请者提供的背景信息(仓储类型与管理级别)也被一并编码。
最后,本数据集通过Python脚本对上述相关要求的回复中提及的所有URL进行了检测,以评估因链接失效导致无法访问的证据占比。



