Editorial

3 pages, 1406 KiB

Open AccessEditorial

Special Issue on AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition

by Liliana Ardissono, George E. Raptis and Noemi Mauro

Appl. Sci. 2022, 12(19), 10118; https://doi.org/10.3390/app121910118 - 08 Oct 2022

Cited by 2 | Viewed by 1133

The richness of tangible and intangible cultural heritage (CH) poses great opportunities and challenges in the development of successful information and communications technology (ICT) tools for its curation, exploration and fruition [...] Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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18 pages, 2233 KiB

Open AccessArticle

Fostering the Creation of Personalized Content for Cultural Visits

by Riccardo De Benedictis, Carlo De Medio, Augusto Palombini, Gabriella Cortellessa, Carla Limongelli and Amedeo Cesta

Appl. Sci. 2021, 11(16), 7401; https://doi.org/10.3390/app11167401 - 12 Aug 2021

Cited by 3 | Viewed by 1616

Abstract

Among more dramatic effects, the COVID-19 scenario also raised the need for new online information and communication services, promoting the spread of software solutions whose usefulness will last well beyond the pandemic situation. Particularly in the cultural heritage domain, it has been unveiled [...] Read more.

Among more dramatic effects, the COVID-19 scenario also raised the need for new online information and communication services, promoting the spread of software solutions whose usefulness will last well beyond the pandemic situation. Particularly in the cultural heritage domain, it has been unveiled the relevance of new AI-based approaches, able to dynamically aggregate information and making them available for a customized fruition aimed to the individual cultural growth. Here, we integrate machine learning techniques for the automatic generation of contents for an intelligent tutoring system grounded on automated planning techniques. We present a solution for semantic, intelligent creation of personalized cultural contents, born as a lesson-making assistant, but developed as to become a multi-function “cultural crossover”, useful in the frame of a wide range of planning, dissemination, and managing activities for cultural heritage contents. Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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25 pages, 781 KiB

Open AccessArticle

A Context-Aware Middleware for Context Modeling and Reasoning: A Case-Study in Smart Cultural Spaces

by Konstantinos Michalakis, Yannis Christodoulou, George Caridakis, Yorghos Voutos and Phivos Mylonas

Appl. Sci. 2021, 11(13), 5770; https://doi.org/10.3390/app11135770 - 22 Jun 2021

Cited by 6 | Viewed by 3295

Abstract

The proliferation of smart things and the subsequent emergence of the Internet of Things has motivated the deployment of intelligent spaces that provide automated services to users. Context-awareness refers to the ability of the system to be aware of the virtual and physical [...] Read more.

The proliferation of smart things and the subsequent emergence of the Internet of Things has motivated the deployment of intelligent spaces that provide automated services to users. Context-awareness refers to the ability of the system to be aware of the virtual and physical environment, allowing more efficient personalization. Context modeling and reasoning are two important aspects of context-aware computing, since they enable the representation of contextual data and inference of high-level, meaningful information. Context-awareness middleware systems integrate context modeling and reasoning, providing abstraction and supporting heterogeneous context streams. In this work, such a context-awareness middleware system is presented, which integrates a proposed context model based on the adaptation and combination of the most prominent context categorization schemata. A hybrid reasoning procedure, which combines multiple techniques, is also proposed and integrated. The proposed system was evaluated in a real-case-scenario cultural space, which supports preventive conservation. The evaluation showed that the proposed system efficiently addressed both conceptual aspects, through means of representation and reasoning, and implementation aspects, through means of performance. Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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34 pages, 4361 KiB

Open AccessArticle

Wikidata Support in the Creation of Rich Semantic Metadata for Historical Archives

by Davide Colla, Annamaria Goy, Marco Leontino and Diego Magro

Appl. Sci. 2021, 11(10), 4378; https://doi.org/10.3390/app11104378 - 12 May 2021

Cited by 5 | Viewed by 2094

Abstract

The research question this paper aims at answering is the following: In an ontology-driven annotation system, can the information extracted from external resources (namely, Wikidata) provide users with useful suggestions in the characterization of entities used for the annotation of documents from historical [...] Read more.

The research question this paper aims at answering is the following: In an ontology-driven annotation system, can the information extracted from external resources (namely, Wikidata) provide users with useful suggestions in the characterization of entities used for the annotation of documents from historical archives? The context of the research is the PRiSMHA project, in which the main goal is the development of a proof-of-concept prototype ontology-driven system for semantic metadata generation. The assumption behind this effort is that an effective access to historical archives needs a rich semantic knowledge, relying on a domain ontology, that describes the content of archival resources. In the paper, we present a new feature of the annotation system: when characterizing a new entity (e.g., a person), some properties describing it are automatically pre-filled in, and more complex semantic representations (e.g., events the entity is involved in) are suggested; both kinds of suggestions are based on information retrieved from Wikidata. In the paper, we describe the automatic algorithm devised to support the definition of the mappings between the Wikidata semantic model and the PRiSMHA ontology, as well as the process used to extract information from Wikidata and to generate suggestions based on the defined mappings. Finally, we discuss the results of a qualitative evaluation of the suggestions, which provides a positive answer to the initial research question and indicates possible improvements. Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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30 pages, 9236 KiB

Open AccessArticle

A UWB-Driven Self-Actuated Projector Platform for Interactive Augmented Reality Applications

by Ahmed Elsharkawy, Khawar Naheem, Dongwoo Koo and Mun Sang Kim

Appl. Sci. 2021, 11(6), 2871; https://doi.org/10.3390/app11062871 - 23 Mar 2021

Cited by 10 | Viewed by 3341

Abstract

With the rapid development of interactive technology, creating systems that allow users to define their interactive envelope freely and provide multi-interactive modalities is important to build up an intuitive interactive space. We present an indoor interactive system where a human can customize and [...] Read more.

With the rapid development of interactive technology, creating systems that allow users to define their interactive envelope freely and provide multi-interactive modalities is important to build up an intuitive interactive space. We present an indoor interactive system where a human can customize and interact through a projected screen utilizing the surrounding surfaces. An ultra-wideband (UWB) wireless sensor network was used to assist human-centered interaction design and navigate the self-actuated projector platform. We developed a UWB-based calibration algorithm to facilitate the interaction with the customized projected screens, where a hand-held input device was designed to perform mid-air interactive functions. Sixteen participants were recruited to evaluate the system performance. A prototype level implementation was tested inside a simulated museum environment, where a self-actuated projector provides interactive explanatory content for the on-display artifacts under the user’s command. Our results depict the applicability to designate the interactive screen efficiently indoors and interact with the augmented content with reasonable accuracy and relatively low workload. Our findings also provide valuable user experience information regarding the design of mobile and projection-based augmented reality systems, with the ability to overcome the limitations of other conventional techniques. Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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22 pages, 509 KiB

Open AccessFeature PaperArticle

MuMIA: Multimodal Interactions to Better Understand Art Contexts

by George E. Raptis, Giannis Kavvetsos and Christina Katsini

Appl. Sci. 2021, 11(6), 2695; https://doi.org/10.3390/app11062695 - 17 Mar 2021

Cited by 10 | Viewed by 2384

Abstract

Cultural heritage is a challenging domain of application for novel interactive technologies, where varying aspects in the way that cultural assets are delivered play a major role in enhancing the visitor experience, either onsite or online. Technology-supported natural human–computer interaction that is based [...] Read more.

Cultural heritage is a challenging domain of application for novel interactive technologies, where varying aspects in the way that cultural assets are delivered play a major role in enhancing the visitor experience, either onsite or online. Technology-supported natural human–computer interaction that is based on multimodalities is a key factor in enabling wider and enriched access to cultural heritage assets. In this paper, we present the design and evaluation of an interactive system that aims to support visitors towards a better understanding of art contexts through the use of a multimodal interface, based on visual and audio interactions. The results of the evaluation study shed light on the dimensions of evoking natural interactions within cultural heritage environments, using micro-narratives for self-exploration and understanding of cultural content, and the intersection between human–computer interaction and artificial intelligence within cultural heritage. We expect our findings to provide useful insights for practitioners and researchers of the broad human–computer interaction and cultural heritage communities on designing and evaluating multimodal interfaces to better support visitor experiences. Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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25 pages, 4585 KiB

Open AccessArticle

Optimal Planning Method for Large-Scale Historical Exhibits in the Taiwan Railway Museum

by Lin Pey Fan and Tzu How Chu

Appl. Sci. 2021, 11(5), 2424; https://doi.org/10.3390/app11052424 - 09 Mar 2021

Cited by 2 | Viewed by 5741

Abstract

The curation design of cultural heritage sites, such as museums, influence the level of visitor satisfaction and the possibility of revisitation; therefore, an efficient exhibit layout is critical. The difficulty of determining the behavior of visitors and the layout of galleries means that [...] Read more.

The curation design of cultural heritage sites, such as museums, influence the level of visitor satisfaction and the possibility of revisitation; therefore, an efficient exhibit layout is critical. The difficulty of determining the behavior of visitors and the layout of galleries means that exhibition layout is a knowledge-intensive, time-consuming process. The progressive development of machine learning provides a low-cost and highly flexible workflow in the management of museums, compared to traditional curation design. For example, the facility’s optimal layout, floor, and furniture arrangement can be obtained through the repeated adjustment of artificial intelligence algorithms within a relatively short time. In particular, an optimal planning method is indispensable for the immense and heavy trains in the railway museum. In this study, we created an innovative strategy to integrate the domain knowledge of exhibit displaying, spatial planning, and machine learning to establish a customized recommendation scheme. Guided by an interactive experience model and the morphology of point–line–plane–stereo, we obtained three aspects (visitors, objects, and space), 12 dimensions (orientation, visiting time, visual distance, centrality, main path, district, capacity, etc.), 30 physical principles, 24 suggestions, and five main procedures to implement layout patterns and templates to create an exhibit layout guide for the National Railway Museum of Taiwan, which is currently being transferred from the railway workshop for the sake of preserving the rail culture heritage. Our results are suitable and extendible to different museums by adjusting the criteria used to establish a new recommendation scheme. Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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30 pages, 602 KiB

Open AccessEditor’s ChoiceArticle

Human-Centered Artificial Intelligence for Designing Accessible Cultural Heritage

by Galena Pisoni, Natalia Díaz-Rodríguez, Hannie Gijlers and Linda Tonolli

Appl. Sci. 2021, 11(2), 870; https://doi.org/10.3390/app11020870 - 19 Jan 2021

Cited by 42 | Viewed by 11967

Abstract

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it [...] Read more.

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it presents how recent and future artificial intelligence (AI) developments can be used for this aim, i.e.,improving and widening online and in situ accessibility. From the literature review analysis, we articulate a conceptual framework that incorporates key elements that constitute museum and cultural heritage online experiences and how these elements are related to each other. Concrete opportunities for future directions empirical research for accessibility of cultural heritage contents are suggested and further discussed. Full article

(This article belongs to the Special Issue AI and HCI Methods and Techniques for Cultural Heritage Curation, Exploration and Fruition)

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