Dear Colleagues,

Following the success of the Special Issue of Big Data and Cognitive Computing on “Big Data Analytics for Cultural Heritage”, we are delighted to announce a new Special Issue entitled “Big Data Analytics for Cultural Heritage 2nd Edition”.

Although big data was initially coined as a term to represent our inability to manage and process the volumes of data that we record, recent advances in both the technological and algorithmic frontier have led to the development of the field of big data analytics. Big data analytics, i.e., methods and applications designed specifically to operate with vast data sets, have become widely accepted as general-purpose tools that can be applied to any domain.

As such, we have seen the same, or very similar, big data analytics tools applied to fields such as social media, economics, biomedicine, smart cities, and so on. The caveat here is that the meaning of the data is not being considered in the process, such as in the case of deep learning, even if some data structures, such as word embeddings, do reflect structures of meaning.

Cultural heritage, on the other hand, is a domain that produces vast amounts of data but also where the meaning of the data is crucially important in its handling; particularly to the extent that it refers to people’s opinions, perceptions, and interpretations of their past and their present, or to people’s feelings, preferences, and attitudes.

In this Special Issue, we focus on big data analytics methods and tools that have been specifically developed for the domain of cultural heritage, as well as on experiences from the adaptation and/or application of general-purpose solutions to the domain of cultural heritage. The aim is to gather solutions, but also lessons learnt, methodologies, and good practices, that researchers and practitioners can use as a basis for their own work in the domain.

Relevant topics include any aspect of big data analytics, as long as it is applied or aimed at the cultural heritage domain. Indicative topics include (but are not restricted to) the following keywords.

Dr. Manolis Wallace
Dr. Vassilis Poulopoulos
Dr. Angeliki Antoniou
Dr. Martín López-Nores
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• data analytics
• big data visualization
• social media analytics
• pattern detection in archives
• handling of heterogeneous cultural resources
• integration with linked data resources
• analytics on sensor-generated and person-generated data
• named entity recognition in textual and non-textual sources
• identification of semantic relations
• sentiment analysis
• visitor type classification
• user/visitor profiling
• adaptation and personalization of cultural heritage experiences
• context awareness in cultural heritage data
• big data analytics underpinning (semi-)automated content generation (e.g., interactive storytelling)
• big data analytics and computational creativity
• gamification
• trajectories in the physical space
• ethical concerns
• case studies