What is COSCHKR?

COSCH aims to provide ‘an optimal framework to overcome those limitations of projects that are usually object-dependent and application-driven, leading to unshared and non-standardized results - providing an interdisciplinary framework for scientists and technicians (developers of measurement systems, software and technologies for a wide range of applications, as well as material scientists, physicists and chemists) and the heritage specialists (art historians, conservators, archaeologists, curators and others) to facilitate the exchange of interests, needs, capabilities, constraints, limits and perspectives' (Boochs et al. 2014, 1).

‘Cultural Heritage is the domain where arguably one of the largest numbers of interdisciplinary activities concentrates in a common goal. From discovery to restoration and analysis of objects, various activities from completely different disciplines are involved. These disciplines need to communicate with each other through a reliable platform for achieving the appropriate result. COSCHKR (COSCH Knowledge Representation) intends to provide such platform. The purpose is twofold: 1) to bridge between technical expertise in documentation and the expertise in restoration and analysis and 2) to reuse already existing knowledge within individual and cross domains for the obvious benefits. In this sense, the COSCHKR should present a platform to store and represent knowledge of individual domain with interrelations to other expert domains' (Boochs et al. 2014, 4).

‘COSCHKR benefits from the recent developments in the Semantic Web framework and its underlying technologies. The knowledge model is expressed through the Web Ontology Language (OWL), which is W3C recommendation to define ontology since 2004 (Horrocks [et al.] 2007)' (Boochs et al. 2014, 4).

Who is it for?

‘COSCHKR Knowledge model encapsulates the expert knowledge from different domains of CH, which will be utilized through an interactive frontend tool. COSCHKR Application is intended to provide a common platform to experts and CH users alike to put forward their queries and get answers without worrying about the complexity of the backend model. The application should allow seeking answers in varying nature: simple to complex and should invoke the knowledge model to infer underlying facts and heuristics' (Boochs et al. 2014, 5).

The COSCHKR App is intended to emulate the decision-making ability of experts. The objective is to guide users through complex decision-making processes using interactive and intelligent question-and-answer procedures. The main purpose of this system is not to replace any expert in the decision making process, but to help him/her to make the right decision. The COSCHKR knowledge model is designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules rather than through conventional procedural code. It consists of two sub-systems: the knowledge base and the inference engine. The knowledge base represents known facts and rules and the inference engine applies the rules to the known facts to deduce new facts.

How to contribute to COSCHKR?

The reliability of COSCHKR App depends on the accuracy of the underlying COSCHKR knowledge model. Henceforth, it is of upmost importance to gather expert information of domains involved in CH spectral and spatial documentation for structuring and communicating it within the knowledge model. Thus the first step consists of collecting comprehensive quality knowledge, through 1) face-to-face discussions, 2) questionnaires, 3) STSMs and 4) case studies supported by COSCH. This collected knowledge, which is related to individual  CH objects and documentation techniques, will be structured by the COSCHKR Working Group. These steps on the one hand allow adding knowledge of different domains to COSCHKR while on the other hand help creating domain based inference rules for COSCHKR.

The COSCHKR App can be extended further through knowledge collected from other experts in CH documentation beyond COSCH. This will not only help to upgrade knowledge inside the knowledge model, but will also help to infer new rules and/or to update existing standards/guidelines inside COSCHKR.

A COSCHKR – Technology Editing Form (TEF) is set up to show, comment on and verify already collected content, to propose modifications and to enter new information. In its actual stage,  the TEF is mainly aimed at experts from spatial and spectral domains to evaluate the current hierarchical structures of their technical devices and procedures with the aim of providing critical analyses and updates to the system.  This is a part of knowledge gathering and should not be confused with the COSCHKR App. The application is currently being developed and will be set up through different phases from now until the end of 2016.

COSCHKR questionnaire: klick here

Exemplary completed COSCHKR questionnaire: Germolles

COSCHKR presentation, Joint WG meeting in Neuchâtel, 13 October 2015: presentation

COSCHKR GUI simulation: At the very end of the development of the COSCH knowledge representation COSCHKR a GUI will be created which allows end-users querying the ontology. This PDF simulates such a query. It displays an examplary input by a fictitious user, the complex relationships which are operated by the ontology and are running in the background, and the final recommendation for the user.

Interested in the COSCHKR .owl file? Please contact the Action Chair Prof. Dr.-Ing. Frank Boochs.

COSCHKR taxonomical hierarchy of the top-level class "Technologies": image


Boochs et al. 2014: Boochs, F., Trémeau, A., Murphy, O., Gerke, M., Lerma, J.L., Karma­charya, A., Karaszewski, M.: Towards A Knowledge Model Bridging Technologies And Applications In Cultural Heritage Documentation, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5, 81-88, doi:10.5194/isprsannals-II-5-81-2014, 2014.

Horrocks et al. 2007: Horrocks, I., Patel-Schneider, P.F., McGuinness, D.L., Welty, C.A.: OWL: A Description Logic Based Ontology Language for the Semantic Web. In: The Description Logic Handbook: Theory, Implementation, and Applications (2nd Edition), 2007, 1-32. Cambridge University Press.

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