Medici 2: A Scalable Content Management System for Cultural Heritage Datasets

Authors: Constantinos Sophocleous, Luigi Marini, Ropertos Georgiou, Mohammed Elfarargy, and Kenton McHenry

Abstract: Digitizing large collections of Cultural Heritage (CH) resources and providing tools for their management, analysis and visualization is critical to CH research. A key element in achieving the above goal is to provide user-friendly software offering an abstract interface for interaction with a variety of digital content types. To address these needs, the Medici content management system is being developed in a collaborative effort between the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign, Bibliotheca Alexandrina (BA) in Egypt, and the Cyprus Institute (CyI). The project is pursued in the framework of European Project “Linking Scientific Computing in Europe and Eastern Mediterranean 2” (LinkSCEEM2) and supported by work funded through the U.S. National Science Foundation (NSF), the U.S. National Archives and Records Administration (NARA), the U.S. National Institutes of Health (NIH), the U.S. National Endowment for the Humanities (NEH), the U.S. Office of Naval Research (ONR), the U.S. Environmental Protection Agency (EPA) as well as other private sector efforts.

Medici is a Web 2.0 environment integrating analysis tools for the auto-curation of un-curated digital data, allowing automatic processing of input (CH) datasets, and visualization of both data and collections. It offers a simple user interface for dataset preprocessing, previewing, automatic metadata extraction, user input of metadata and provenance support, storage, archiving and management, representation and reproduction. Building on previous experience (Medici 1), NCSA, and CyI are working towards the improvement of the technical, performance and functionality aspects of the system. The current version of Medici (Medici 2) is the result of these efforts. It is a scalable, flexible, robust distributed framework with wide data format support (including 3D models and Reflectance Transformation Imaging-RTI) and metadata functionality. We provide an overview of Medici 2’s current features supported by representative use cases as well as a discussion of future development directions

Citation: Constantinos Sophocleous, Luigi Marini, Ropertos Georgiou, Mohammed Elfarargy, and Kenton McHenry. (2017). Medici 2: A Scalable Content Management System for Cultural Heritage Datasets. Code4Lib Journal, Issue 36.

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