In recent years semantic technologies have become increasingly popular to represent, manage and publish data in the humanities. Virtual research environments with semantic backends are used to build complex networks, data is exposed as triples using RDF, and important vocabularies and thesauri are available as linked data. Ontologies like the CIDOC Conceptual Reference Model (CRM) are the semantic backbone of this approach and provide interoperability and data exchange beyond pure linking.
WissKI (wiss-ki.eu) is a ready-to-be-used web-based virtual research environment and publishing framework that in its core relies on Semantic Web technologies to represent the curated knowledge. The user experience for data acquisition and presentation, however, intentionally borrows from traditional modes, while the user profits from the possibilities of linked and semantically enriched data. Thus, the system enables digital humanists to produce high-quality linked data, without having to cope with technical issues of the Semantic Web and ontologies in general or the often-quoted pecularities of CIDOC CRM in particular. This is achieved by defining a mapping between traditional index card or tabular style on the one hand and graph-based linked data on the other hand. The mapping may be opaque to the users and only be managed by an (ontological) administrator. Also, mappings may be shared between systems and projects, so that best practice patterns may evolve; this actually already has happened and still happens.
By default, data may be input and displayed either as free text or as structured data via forms. Free text may be input through a graphical editor and is semantically indexed in terms of named entity recognition results, calendar date specifications, mentioned events, and also technical terms as far as appropriate authority files are available (e.g. Getty's Art and Architecture Thesaurus). Form input provides mechanisms for error reduction like spelling variants, e.g. by showing autocompletion hints that are again backed by available authorities. From the textual annotations, RDF triples may be generated and be reused as structured data. Furthermore, the system allows the upload, derivation and display of images. Other, more application-specific ways of data acquisition like mass imports or 2D/3D annotation may be included through extensions.
From the technical perspective, WissKI is based on Drupal (drupal.org). Drupal is a widely used Web Content Management System with a big and active user and developer community. It has a modular architecture and there exists a vast variety of third party extension. Being such an extension, WissKI profits from a stable core system (security updates!) and also from these community contributions, providing all sorts of functionality.
As Drupal itself, WissKI is published as open source and can be downloaded from the project web site (wiss-ki.eu) or from github.
Although WissKI in its core is domain-agnostic, it is designed to best fit the needs of object centered documentation and research as it is typical for many memory institutions, but also for research projects from art history, biodiversity, architecture, epigraphy, etc. As such it naturally goes together with the CIDOC CRM, an ontology designed for the documentation of cultural heritage. It is used by several academic and memory institutions in Germany in national and international research projects; it is used for such diverse purposes as research environment, curated collection management, virtual exhibition, or in courses and seminars.
The tutorial aims at all researchers, archivists and curators who are interested in object documentation, in particular its semantic disclosure integrating data from (database and content management systems) form-based input and plain text fields. Furthermore it addresses people interested in applications of the CIDOC CRM.
This half-day tutorial
gives a short introduction to the (technical) approach of WissKI,
presents current use cases and modes of use,
shows how to install, configure, and use WissKI, and
includes a hands-on for semantic modelling and data acquisition with WissKI and CIDOC CRM.
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