Digital Knowledge Store. Organizing Humanities Research Data

“数字知识库”项目为柏林-勃兰登堡科学与人文学院的所有数字资源提供了一个中央访问渠道。其结果是一个灵活的基础设施，异构人文研究数据，非常适合长期保存和访问。它是一个高度健壮的服务器应用程序，将信息检索和语义网技术的潜力与渐进式用户界面相结合。数字知识库的目标是进行深度分析，而不仅仅是处理和评估元数据和全文索引。从我们的角度来看，以内容为中心的分析研究数据的机器加工工具是可实现的，以及可取的。因此，数字知识存储不仅准备好使用，而且还在第一个版本中实现。数字知识库在后续应用中的关键点是不仅能够获取研究数据，而且能够对其进行隐含知识和研究意图的智力分析。据我们所知，在图书馆和档案馆的模拟领域，以及在档案和数据中心的数字领域，都没有与之相当的研究数据的智力覆盖。将多语种语言注释、对人员、地点和事件内部标记的分析以及对项目和背景的描述性信息的处理结合起来，是朝着这一方向迈出的第一步。这些步骤的识别、实现和可视化是一个重要的和仍然开放的任务，到目前为止，我们已经获得了重要的经验，这将有助于建立一个扩展的数字知识库模型。这将产生一个既可以被其他机构免费使用，又可以在他们的服务器上安装和运行的产品。不仅意向书，而且目前在研究数据基础设施领域的讨论都表明了这种发展的高需求。在项目的下一步，我们将重点关注已存储在索引和数据库中的数据的质量保证。此外，该研究院当前研究的内置工作流程也将相继优化，特别是研究数据的语义互连。它们将更多地应用于研究，分析和使用数据的日常工作中，并可以转移到其他人文研究机构。

The project "Digital Knowledge Store" created a central access to all digital resources of the Berlin-Brandenburg Academy of Sciences and Humanities. The outcome is a flexible infrastructure for heterogeneous humanities research data which is well suited for long-term preservation and accessibility. It is a highly robust server application which combines the potential of information retrieval and semantic web technologies with a progressive user interface.The Digital Knowledge Store aims for a depth of analysis that doesn't stop at processing and evaluating metadata and a full-text index. From our point of view the content-focused analysis of the research data by machine processing tools is realizable as well as desirable. So the Digital Knowledge Store is not only prepared for usage but is also implemented in a first version. The abil-ity not only to access research data, but also to intellectually analyze it with regard to implicit knowledge and research intention is the crucial point in the follow-up application for the Digital Knowledge StoreAs far as we know there is neither an equivalent of intellectual coverage of research data in the analog sphere of libraries and archives nor one in the digital sphere of archiving and data centers. Combining the multilingual linguistic annotation, analysis of internal markup of persons, places and events, and the processing of descriptive information on projects and context was a first step in that direction. It is an important and still open task to identify, implement and visualize these steps.So far we have gained important experience which will help to build an extended model of the Digital Knowledge Store. This will result in a product which can be both used freely by other institutions and be installed and run on their servers. Not only the letters of intent but also the current discussions in the area of research data infrastructures show the high demand of such a development.In the next step of the project we will focus on quality assurance of the data already stored in the index and databases. Also the built-in workflows for the current research in the academy will be optimized successively, especially for the semantic interconnections of the research data. They will be applied even more into the daily routine of researching, analyzing and usage of data and can be transferred to other humanities research institutions.