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获取性和进一步使用起着关键作用。这原则上适用于所有数据产品，但对于德国数字图书馆（DDB）和Graphikportal等公共平台以及NFDI4Culture和Text+等NFDI联盟不断增长的数据产品来说尤其如此。要整合的数据的质量往往与目标系统所期望的不同。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，数据提供者和数据接受者之间必须进行对话。如果软件用于质量保证，软件开发人员必须在质量要求发生变化时立即对其进行调整。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。该项目的目的是使技术知识不多的领域专家能够自己确定和执行元数据的特定主题质量保证。为此，将开发一个程序和基于网络的软件，使领域专家能够在实际质量保证之前半自动地确定质量要求。随后，将自动生成各种质量保证技术（如Schematron）或现有软件和框架（如元数据质量评估框架）所需的投入。这些现有组件嵌入质量保证过程中，无需先前所需的技术专长即可使用。质量分析和相关的可能的质量改进将单独定义，并且可以彼此独立地进行。该项目开发的软件将成为一个独立的敏捷质量保证流程的核心，而这一流程又可以纳入现有的数据整合流程，但也可以独立于这些流程使用。这一过程将比以前的质量保证机制更加自动化，更容易调整。将解决的具体用例是集成到DDB和Graphikportal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。对该方法的评价嵌入在NFDI财团NFDI4Culture和Text+中。由于这种方法独立于具体的数据格式和技术，因而具有通用性，因此可以转用于其他应用领域的元数据质量保证。

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.