Agile quality assurance of metadata on cultural objects in the context of data integration processes

文物元数据的质量对文物的可访问性和进一步使用起着至关重要的作用。原则上，这适用于所有的数据产品，但对于常见的平台，如德国数字图书馆（DDB）和graphhikportal，以及NFDI联盟不断增长的数据产品，如NFDI4Culture和Text+，更是如此。要集成的数据的质量通常与目标系统所期望的质量不同。在将数据纳入目标系统之前，必须对数据进行分析，并在必要时进行调整，这通常是一个耗时的过程，并在数据提供者和数据接收者之间进行对话。如果软件用于质量保证，那么一旦质量需求发生变化，软件开发人员就必须对其进行调整。到目前为止，领域专家几乎没有机会使用现有的工具自己执行质量保证，更不用说适应现有的质量需求了。该项目的目的是使具有很少技术知识的领域专家能够定义和执行元数据本身的特定主题的质量保证。为此，将开发一个过程和基于web的软件，允许领域专家在实际质量保证之前半自动地定义质量需求。随后，各种质量保证技术（例如Schematron）或现有软件和框架（例如元数据质量评估框架）所需的输入将自动生成。这些现有组件嵌入在质量保证过程中，无需以前所需的技术专门知识即可使用。质量分析和相关的可能的质量改进应分开定义，并可相互独立地进行。项目中开发的软件将成为敏捷质量保证的自包含过程的核心，该过程可以集成到现有的数据集成过程中，但也可以独立于它们使用。这个过程将比以前的质量保证机制更加自动化，更容易适应。将要解决的具体用例是集成到DDB和graphhikportal中的LIDO数据的质量保证，以及TextGrid存储库中的TEI头数据的质量保证。该方法的评估嵌入NFDI联盟NFDI4Culture and Text+。由于该方法独立于具体的数据格式和技术，因此具有通用性，因此可以将元数据的质量保证转移到其他应用领域。

The quality of metadata of cultural objects plays a critical role in their accessibility and further use. This applies in principle to all data offerings, but it is particularly true for common platforms such as the German Digital Library (DDB) and the Graphikportal as well as for the growing data offerings of NFDI consortia such as NFDI4Culture and Text+. The quality of the data to be integrated is very often different from that expected by the target systems. The data must be analysed and, if necessary, adapted prior to the integration into a target system in a usually time-consuming process and in dialogue between data providers and data recipients. If software is used for quality assurance, it must be adapted by software developers as soon as changes are made to the quality requirements. So far, domain experts have hardly had a chance to carry out quality assurance on their own with existing tools, much less to adapt existing quality requirements. The aim of the project is to enable domain experts with little technological knowledge to define and carry out the subject-specific quality assurance of metadata themselves. To this end, a process and web-based software will be developed that allows the domain experts to semi-automatically define the quality requirements prior to the actual quality assurance. Subsequently, the required input for various quality assurance techniques, e.g. Schematron, or existing software and frameworks, such as the Metadata Quality Assessment Framework, will be generated automatically. These existing components are embedded in the quality assurance process and can be used without the technical expertise previously required. The quality analysis and associated possible quality improvements will be defined separately and can be carried out independently of each other. The software developed in the project will be the core of a self-contained process for agile quality assurance, which in turn can be integrated into existing data integration processes, but can also be used independently of them. The process will be more automated and easier to adapt than previous quality assurance mechanisms. The concrete use cases that will be addressed are the quality assurance of LIDO data for integration into the DDB and the Graphikportal, and of TEI header data in the TextGrid repository. The evaluation of the approach is embedded in the NFDI consortia NFDI4Culture and Text+. Since the approach is independent of concrete data formats and technologies and thus generic, transferability to the quality assurance of metadata in other application areas is possible.