DISCO: Data Integration for Conservation Science seeks to improve the ways scientific and technical studies contribute to the conservation and understanding of works of art through the development of open-source software that will integrate conservation science data by facilitating better management, extraction and sharing practices. The GCI will build upon and leverage existing data integration efforts to provide a software system tailored to benefit and strengthen the fields of art conservation, conservation science, and art-historical scholarship for a broad community of users.

Background

During an analysis or treatment campaign conservation scientists and practicing conservators gather or generate an enormous amount of data on an object, artist, or site. The same is true for curators and art historians, who increasingly are incorporating technical studies into their work. Taken together, all these different types of data–images, text, and analytical measurements–may inform the way conservation treatment programs are undertaken and how historic, artistic, technological, and cultural interpretations are made. Unfortunately however, because of challenges in comparing data acquired in different formats, all data relating to an object (or group of objects) are rarely "taken together", but more often are considered in isolation.

As instrumentation capabilities continue to advance, a single researcher's ability to collect data is rapidly surpassing his or her ability to fully analyze, interpret, and synthesize the information generated. Consequently subtle, but important, phenomena or relationships are becoming increasingly difficult to identify in an overwhelming data stream.

What is needed is a way to integrate all the data relating to the research topic under study–whether that be a single object, group of objects, artist, or artist's workshop–into a concise and accurate representation that facilitates making comparisons, finding correlations, and ultimately leading to new insights and discoveries.

The need for such data integration is not unique to cultural heritage. Other data-rich disciplines, such as astronomy, medicine, chemistry, finance, and gaming have begun to develop resources attuned to the needs of their respective stakeholders. Individual aspects of data integration for cultural heritage, such as the building of research networks to exchange data or the visualization of conservation technical images, have also begun to be addressed in recent years.

In 2013, an experts meeting convened at the GCI made evident the need and opportunity for advancement in the area of data integration for conservation science. In 2014, the project embarked upon an initial three-year phase of work, funded by the Seaver Institute, involving:

• Determining the state of the field of data integration in interdisciplinary fields, open source data projects, metadata standards, and specialized vocabularies and ontologies for describing conservation/conservation science data
• Developing/refining specialized vocabularies and ontologies as necessary
• Specifying requirements for a data integration platform based on use cases from a variety of stakeholders in conservation/conservation science
• Developing a proof-of-concept system to integrate scientific, imaging, and textual data for conservation projects
• Seeding and supporting a community of experts and stakeholders in the area of conservation science

In 2017, the project team demonstrated a viable proof-of-concept system, helping to the lay the foundation for further development of fully-functional system. The DISCO proof-of-concept system was built using the Arches open-source cultural heritage data management platform and incorporated standards such as the International Image Interoperability Framework (IIIF) and the CIDOC Conceptual Reference Model in order to facilitate integration and sharing.

Scope

DISCO: Data Integration for Conservation Science will build upon its initial phase of work to develop a robust software platform for the integration of conservation science data, so that ultimately, multiple types of data, from both individual researchers and groups of researchers at different institutions, can be connected and fully-utilized. The project will continue to leverage existing open-source and semantic technologies and standards to achieve this goal.

This integrated data will facilitate interrogation, visualization, and data interpretation, helping researchers, for example, draw comparisons and correlations between different works of art, different studies, and different points in an object's history.

Integrating data from multiple sources will add value to each individual data source, and the community of experts built around the shared data will improve the quality of data interpretation.

In these ways, scientific and technical studies will be more effectively leveraged to advance cultural heritage research by creating a more open, collaborative, and global research community, bringing new insights to the understanding and conservation of cultural heritage.

Page updated: January 2019