Database

All project members are collaborating in the establishment of a scholarly database to document both the reversal of verdicts and past atrocities.

The database will include policy documents and implementation records from national, provincial, and county levels. It will furthermore incorporate relevant data on case revisions, drawn from local gazetteers and party histories, as well as ego documents from contemporary witnesses. Roughly 500 of these documents will also be translated into English.

The foundation for our database is built on Omeka, a flexible and open source web publishing platform that focuses on the display of archives, scholarly collections, and exhibitions. However, we have modified Omeka in several ways to better meet our project’s specific needs, such as reworking the code base to focus specifically on text-based documents.

Our database includes extensive metadata for each document, allowing for searches of related documents, subject areas, and creators. We also provide English translations for a subset of featured documents.

Furthermore, we have replaced the standard search functionality with the search engine Solr, which offers solid Chinese language support. Solr also enables users to take advantage of hit highlighting in the results and faceting capabilities (multiple filters). Because our database makes heavy use of content taxonomies – closely following the Dublin Core metadata standard built into Omeka’s core – these tools will enable researchers to progressively narrow down search results by adding filters, such as document identifiers or tags.

A search on the term “区别工作” in combination with a faceted search on the tag “原工商业者“ results in four hits. These hits could be further narrowed with a faceted identifier search.

In order to provide both beginners and advanced researchers with background information on commonly used terminology and persons, we have also included a contextual glossary that offers additional information.

Glossary entry on 陈野苹 that provides the reader with a short biography.

Last but not least, our database encourages users to actively participate in the transcription process of handwritten source material.

Transcribe
Omeka’s transcribe function allows for collaborative transcription of hand-written materials.

Our aim is to have between four and five thousand documents and articles in the database by the project’s end in 2019. Availability until then will be restricted to the University of Freiburg network. By the time we finish our editorial work, however, we plan to make it available to a larger audience of scientists and researchers for their own use, and to provide us with feedback.