Overview

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 development of computer-assisted data integration tools that will facilitate extraction and sharing of new information by a broad community of users. The GCI, with support from the Seaver Institute, will build upon and leverage existing data integration efforts to provide open-source tools tailored to benefit and strengthen the fields of art conservation, conservation science, and art-historical scholarship.

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. Based upon recommendations put forth at the meeting, a program of work will be undertaken, consisting of three main phases: Foundational Research, Framework Development and a Proof-of-Concept Model.

Scope

Integrating Data for Conservation Science, in addition to building on existing data-related projects within the cultural heritage sector, will leverage data integration efforts in other data-rich disciplines. Ultimately, multiple types of data, from both individual researchers and groups of researchers at different institutions, will be connected using new semantic technologies.

This linked 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.

Linking 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.

Components

The initial three-year phase of Integrating Data for Conservation Science initiative is divided into several components:

  • 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 model 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

Page updated: December 2014