Knowledge Dissemination: Community Reusable Human and Machine Understandable Content Models for Small Museums and Non Technical Scholars
Abstract: The paper addresses the fundamental gap and challenges observed in knowledge dissemination in the cultural heritage domain. The presentation focused on proposing more innovative ideas to contribute to the solution of the distribution of cultural heritage knowledge over the Web found in small museums.
It showcases a solution based on Community Reusable Human and Machine Understandable Content Models available for download from our community website and Github code repository. Installing the CRHMUCM will extend the functionality of the state of the art Content Management Framework towards museum collections. Furthermore, encapsulates machine-understandable data using the Resource Description Framework in Attributes (RDFa), and the Schema.org vocabulary or ontology.Establishing a community around Community Reusable Human and Machine Understandable Content Models will help the development, upgrading and sharing of models for the benefit of the Cultural Heritage community. A distributed model for Community Reusable Human and Machine Understandable Content Models will allow the community to grow and improve, serving the needs and enabling the infrastructure to scale for the next generation of humanities scholars.
Introduction: With the advent of the internet, the digital age has influenced almost every aspect of human activity and has transformed it into a revolutionary way unseen before. In particular, over the last decade the domain of digital cultural heritage has gained a lot of popularity. The scientific community has shown new possibilities for integrated access to collections of cultural heritage, while memory institutions are increasingly eager to cooperate and provide the best possible access to their collections through the Web.
Access to cultural heritage assets will provide users with a wide range of opportunities to gain new knowledge. Memory institutions were probably the first to digitize information, creating online databases whose access was granted only locally through on-site servers.
Since then, the internet has allowed people to access knowledge from their home computers and thus increasing the number of users drastically (Stainforth, 2016).
Nowadays, the digitization process is undoubtedly essential in the cultural heritage domain and its accessibility is improved continuously due to the open-source communities and technological advancements (Cimadomo et al., 2013).
Problem Statement: Smaller museums and their collections are equally crucial for the knowledge dissemination in the cultural heritage domain. As Barbara Lejeune (2007) points out, small museums could only have a small portion of objects online, it could be much more critical than a large museum online collection.
Unfortunately, the potential of new methodologies and tools to have a transformative impact on smaller projects is higher than the grant funding available to support extensive, expensive and extravagant technical undertakings, usually beneficial only to large and well known museums (Lejeune, 2007; Dombrowski, 2016).
Although there are plenty of ideas for creating online digital collections, there are also numerous limitations. Currently, the majority of small museums are unable to follow the large cultural heritage institutions’ digitization steps, and having their collections online.
Additionally, a lot of times smaller museums do not usually hire experts to plan, develop, create, deploy and maintain a digital collection for them, but rather, they delegate them to museum scholars who are often characterized by limited technological skills (Avgousti, Papaioannou, & Gouveia, 2019).
Further, even if they do manage to digitize their collections these are often stored in isolated data silos which are incompatible with automatic processing and incompetent when searching for related information (Avgousti, Papaioannou, & Gouveia, 2019; Sikos, 2016).
On the other hand, this limitation can be addressed by organizing and publishing data using dominant formats and by adding machine-understandable data (Sikos, 2016).
However, this is not a trivial task, and many humanities scholars with non-technical background usually do not have the technical support to undertake such intricate work. On the contrary, this extra step often requires complex setups and in many cases the use of sophisticated and unfamiliar tools (Avgousti, Papaioannou, & Gouveia, 2019 ; Velios, & Martin, 2016).
Nowadays, the majority of small museums are unable to publish their collections online on their own. It is difficult for small museums and individual researchers to even attempt or follow the larger museums’ digital steps since they will not always be able to host their collections online. The majority of small museums certainly lack the resources and the technical skills or the knowledge needed to develop digital collections of their own. Further, small museums must be empowered to carry out their own projects under the direction of a broader community.
Methodology: This presentation focused on Community Reusable Human and Machine Understandable Content Models that are: a domain-centric approach modular functional structure components. A collection of reusable elements that are taken to satisfy a specific domain that is: small museums and individual scholar’s projects. The result is a shared understanding of both human and machine-understandable content. Moreover, Community Reusable Human and Machine Understandable Content Models are installation components that can extend the functionality of the Drupal Content Management System by automatically populate context, content types, taxonomy vocabulary, content, content collections, design, and semantics. Those installation components can be created ones and reuse across various online museum collections. Through the development of Community Reusable Human and Machine Understandable Content Models, we are focusing on solving a significant problem related to knowledge dissemination by small museums.
Conclusion: The development of an online community for Community Reusable Human and Machine Understandable Content Models will allow digital humanities scholars, site builders, computer scientists, digital humanists, site administrators, web developers and others, to create, develop, collaborate, improve, upgrade and share their models and package to impact cultural heritage community in a very beneficial way.
A distributed model for Community Reusable Human and Machine Understandable Content Models will allow our methodology to grow and be more flexible, serve more varied and diverse needs to develop the infrastructure accordingly so as to cater for the next generation of small museums and humanities scholars.
Avgousti, A., Papaioannou, G. & Ribeiro, G. F. (2019). Content Dissemination from Small-scale Museum and Archival Collections: Community Reusable Human and Machine Understandable Content Models f. Code4Lib Journal, 1–10.
Cimadomo, G. (2013). Documentation and dissemination of cultural heritage: Current solutions and considerations about its digital implementation. Proceedings of the DigitalHeritage 2013 – Federating the 19th Int’l VSMM, 10th Eurographics GCH, and 2nd UNESCO Memory of the World Conferences, Plus Special Sessions FromCAA, Arqueologica 2.0 et Al., 1, 555–562. https://doi.org/10.1109/DigitalHeritage.2013.6743796
Dombrowski, Q. (2016). Drupal for humanists (1st ed.). Texas A&M University Press.
Lejeune, B. (2007). The Effects of Online Catalogues in London and other Museums: A Study of an Alternative Way of Access. – Papers from the Institute of Archeology, 18(S1), 79–97. https://doi.org/10.5334/pia.289
Sikos, L. (2016). Mastering Structured Data on the Semantic Web. Apress; 1st ed.
Stainforth, E. (2016). From museum to memory institution: the politics of European culture online. – Museum & Society, 14(2), 323–337.
Velios, A., & Martin, A. (2016). Off-the-shelf CRM with Drupal: a case study of documenting decorated papers. – International Journal on Digital Libraries. https://doi.org/10.1007/s00799-016-0191-5