Find research datasets worth reusing

opencc-by-4.0Jun 2021View details →

Panel: "Broken for All:: The case for persistent identifiers for digital cultural heritage resources AND Developer Track Session 2

This video contains two sessions from Open Repositories 2021: Panel: "Broken for All": the case for persistent identifiers for digital cultural heritage resources Turner, Adrian (1); Holmes-Wong, Deborah (2); Rafique, Zahid (2); Kunze, John (1); Lohnash, Megan (3); McKinley, Matthew (4), Lund, Allison (5) 1: California Digital Library; 2: University of Southern California Libraries; 3: California Revealed; 4: Omeka; 5: Metropolitan New York Library Council  Cultural heritage institutions within the United States have made significant investments in building unique digital collections, broadly disseminating them on the web and through networks such as the Digital Public Library of America (DPLA). The items within these collections are referenced and cited in a range of sources -- from Wikipedia and scholarly articles, to archival finding aids and classroom lesson plans. However, the application of persistent identifier schemes (e.g. DOI, ARK) for unique digital resources is relatively uncommon within the gallery, library, archive, and museum communities. Relatedly, many repositories and digital asset management systems (DAMS) widely used in these communities simply do not support persistent identifier schemes "out of the box." Hence, the URLs for the items are extremely fragile. If the collections are migrated to a different repository, the URLs can easily break -- impacting downstream networks, confounding researchers, and compounding the problem of link rot. This panel will discuss the critical role of persistent identifiers in digital collections management and dissemination and some of the challenges in applying them. It will feature case studies demonstrating how commonly-available licensed and open-source repositories can be adapted to support them. Developer Track Session 2: Constructing a Repository Test Strategy Built on Docker Containers Brady, Terrence W California Digital Library, United States of America The Merritt Digital Preservation system comprises a dozen microservices and supporting services. Our team found that it was not cost effective to maintain and patch a fleet of servers to support a development environment. Our solution was to replace our development server environment with a stack of dockerized services. Once the stack was containerized, we discovered that we were able to create 3 variants of our development stack with different persistence strategies for database content and cloud storage. With these variants, the team has been able to support a variety of testing scenarios. Deploying a Serverless Application as a Docker Image Brady, Terrence W California Digital Library, United States of America A serverless application consists of a defined runtime (such as Ruby 2.7 or Python 3) and a package of code. This presentation will illustrate 3 types of code packages of different complexity and will describe the challenges of bundling more complicated dependencies such as binary files. In December 2020, the AWS Lambda serverless architecture began to support Docker images as a deployment package. This packaging approach makes it possible to run tests against a code package before it is deployed. This presentation will demonstrate the test and deployment process for a serverless application within the Merritt digital preservation system. Other repository teams hosting their applications on AWS may discover some useful patterns for testing and deploying serverless code to AWS Lambda. Live Demo: Create a Developer Workspace Challenge Pottinger, Hardy Joseph California Digital Library, University of California, Office of the President, United States of America Creating a developer workspace, a place in which you can write and test your code, can seem a daunting task. Sure, someone might have done it before, and they might even share their notes with you, but following those notes and arriving in the same place is like following a treasure map and expecting to get rich. There’s a better way, and I’m willing to prove it. This demo aims to show the process one goes through to craft a development environment with pretty much any tool, but will use Lando to conserve time. Lando is a way to bootstrap a useable development environment. It's built on Docker, and is like Docker-Compose, but much more transparent. It handles the boring details and helps you actually start developing with code in your favorite IDE, and all the services you need in Docker. It's all about making the life of a developer easier. It won't give you an application container you can deploy, but you will develop a deeper understanding of how all the pieces fit together, and you'll have a tool which can deploy those pieces to dev/stage/prod if you wish. The audience will participate in this demo. Building Scalable Serverless Digital Repositories using Amplify Open-source Framework Chen, Yinlin; Jiang, Tingting; Hunter, Lee Virginia Tech, United States of America We develop digital repositories to disseminate different types of digital content and to promote the principles of open access. Our goal is not to provide access to information to just one individual institution or group but to anyone and everyone. With that ambitious goal in mind, how do we enable our digital repositories to have the high availability and flexible scaling capabilities necessary to face unforeseen demand? How do we utilize only the resources we need without the waste of overprovisioning resources? These are some of the most challenging issues that we face. To achieve our goals, we moved from the traditional monolithic, server-based approach to serverless cloud infrastructure. By leveraging the services that AWS provides we have been able to boost the performance of our repositories 10x compared to that of our previous implementation that was hosted in-house. Our repositories now automatically scale up and down to meet any kind of traffic demands, without our intervention. In this talk, we will demonstrate our scalable serverless digital repositories and show the opportunities to explore and reflect on the ways that repositories enable openness for all.

opencc-by-nc-4.0Jul 2021View details →

Exploring opportunities and challenges for intangible cultural heritage at the intersection of institutions, civil society, and migrant communities

This data set was produced in the CultureLabs project to explore the needs and expectations of migrant and refugee communities in several European countries in relation to communicating and sharing their intangible cultural heritage (ICH) practices as well as of cultural and civil society organisations that plan to support this.  The data was gathered across Europe in early 2019 and consists of 101 surveys administered and 27 interviews. 101 surveys were administered to people belonging to migrant and refugee communities in several hosting countries, mostly Italy and Germany, while the countries of origin of respondents covered four continents. The survey consisted of closed-ended questions and was structured into eight thematic areas related to a balanced mix of independent and dependent variables for the generation of correlations and clusters. The thematic areas included: background information; employment status; socioeconomic status; residency or migration status; individual preferences, attitudes, and activities; intercultural awareness; extent of interest and preparedness to become actively involved in cultural activities; and access to and use of digital tools. 27 semi-structured interviews were also conducted. The interviewees were recruited from the collaborative network of the nine partner institutions in the CultureLabs project. Although each interview gave space to the issues raised by the interviewees, four themes were deepened with the majority of participants: interest in cultural activities, expectations from cultural activities, the importance of digital tools for cultural activities, and the relevance of cultural heritage activities for individuals and their socio-cultural integration in the host society. The findings resulted in a peer-reviewed publication available at the following link: <a href="https://www.tandfonline.com/doi/full/10.1080/13527258.2021.1922934">https://www.tandfonline.com/doi/full/10.1080/13527258.2021.1922934</a>   The original dataset has been processed by removing details and parts that might compromise the anonymity of the participant.  This work is supported by the European Union’s Horizon2020 project CultureLabs: Recipes for Social Innovation, under Grant Agreement 770158. The sole responsibility of this work lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.

opencc-by-nc-4.0Jul 2021View details →

Exploring the needs of institutional stakeholders involved in the cultural heritage and social innovation sectors

This data set was produced to gather information and lessons learnt from institutional stakeholders directly or indirectly involved in cultural approaches and/or promoting social integration of disadvantaged groups in order to understand what they need to facilitate participatory and inclusive initiatives.  The data was gathered across Europe in early 2019 and consists of 90 surveys administered and 17 interviews. 90 surveys were administered to actors working at the intersection of cultural heritage and social innovation. The survey’s goal  was  to  gather  insights  about  the  barriers  these  actors  face  in  the  implementation of participatory approaches and the measures adopted to overcome them. Semi-structured  interviews  (n=17)  expanded  upon  the  survey  data  and  were  carried  out through an opportunistic sample of the survey respondents. The findings provided relevant insights in relation to the configuration of approaches for participatory projects, the main faced barriers, and the achieved level of impact. The original dataset has been processed by removing details and parts that might compromise the anonymity of the participant.  This work is supported by the European Union’s Horizon2020 project CultureLabs: Recipes for Social Innovation, under Grant Agreement 770158. The sole responsibility of this work lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.

opencc-by-4.0Mar 2023View details →

cultural heritage elements in Andalusia and demographic data sorted by urban category

Dataset concerning cultural heritage elements and demographic data in Andalusia at the municipality level, as they appear on SIMA (Sistema de Información Multiterritorial de Andalucía), March 2023. They have been sorted by urban category, depending on the number of inhabitants of each municipality: less than 1.000 inhabitants, 1.000 to 10.000 inhabitants, 10.000 to 100.000 inhabitants, and more than 100.000 inhabitants.

opencc-by-sa-4.0Nov 2021View details →

A controlled vocabulary for research and innovation in the field of Cultural Heritage & Heritage Sciences

This controlled vocabulary of keywords related to the field of Cultural Heritage and Heritage Sciences was built by SIRIS Academic in collaboration with IRPET (the Regional Institute for Economic Planning of Tuscany) and the ISPC (Institute of Heritage Science of CNR), in order to identify Cultural related research, development, and innovation activities. The work was carried out by consulting domain experts' advice, and it was ultimately applied to inform regional strategies on Cultural Heritage and research and innovation policy. The aim of this vocabulary is to enable one to retrieve texts (e.g. R&D projects and scientific publications) featuring the concepts included in the present vocabulary in their titles and abstracts, assuming that these records have a certain contribution of applications, techniques and issues, in the domain of Cultural Heritage and Heritage Sciences. The aim of this classification is to identify research products in the domain of Cultural Heritage, ranging from documents in some of its “traditional” disciplines, but also from documents emerging from interdisciplinary projects that apply novel areas and technologies in the domain of Cultural Heritage. The identification of texts in the domain of Cultural Heritage requires a task of text classification. Developing a method that could be applied to decide if a text can be relevant or have some relation to the domain of Cultural Heritage is a challenging task. The definition of what Cultural Heritage is and what it includes is a complex activity, even for domain experts. This is in particular because Cultural Heritage is quite a broad field of knowledge, and there is no full agreement on where the borders of the domain are. To define the scope of the perimeter, in this project, many of the available definitions were taken into account. Because of the high number of resources available in the domain, among thesauruses and taxonomies, the construction of a weakly-supervised controlled vocabulary was considered as the best way of retrieving documents in the domain. Since there is no annotated corpus/dataset of research texts in the domain capable of generalising the diversity of publications that can be related to the cultural domain, but stemming from different disciplines, we have opted for a text classification technique based on rules – specifically, a weakly-supervised controlled vocabulary. As defined by the Getty Institute, a controlled vocabulary is an organized arrangement of words and phrases used to index content and/or to retrieve content through browsing or searching. It typically includes preferred and variant terms and has a defined scope or describes a specific domain. The purpose of controlled vocabularies is to organize information and to provide terminology to catalogue and retrieve information. While capturing the richness of variant terms, controlled vocabularies also promote consistency in preferred terms and the assignment of the same terms to similar content (Harping, 2010). In short, Cultural Heritage is a rather abstractly-defined field, and Heritage Science is a particularly “fuzzy” field within Cultural Heritage. One of the main limitations of the approach we used is that the controlled vocabularies never capture all the lexical and linguistic variants of a term, and we may miss relevant texts if we cannot find the correct pattern to match during the search. But on the other hand, the controlled vocabulary is built from available vocabularies and thesauruses in the domain of Cultural Heritage, which are large resources. All the concepts in these resources are not included directly in the controlled vocabularies, because they would add noise to the classification. Therefore, the automatic weak supervision and a human curation of the final controlled vocabulary is fundamental for achieving correct results. The controlled vocabulary is built taking advantage of these four resources: <ul> <li>The <a href="https://www.getty.edu/research/tools/vocabularies/aat/">Art and Architecture Thesaurus (AAT)</a>: this is a structured vocabulary with approximately 34,000 concepts, including 131,000 words, descriptions and other information related to art, architecture, decorative arts, archival material and material culture, commonly used for cataloguing and for information retrieval.</li> <li> Some cultural heritage categories in <a href="https://en.wikipedia.org/wiki/Category:Cultural_heritage">Wikipedia</a> and <a href="https://dbpedia.org/page/Cultural_heritage">DBpedia</a>: these categories have been used to collect all related articles and subcategories, in order to obtain relevant, similar and specific instances of concepts linked to the domain.  </li> <li> The <a href="https://www.riches-project.eu/riches-taxonomy.html">RICHES Taxonomy</a>: this taxonomy is a theoretical framework of related terms and their definitions, referring to the new concepts in the digital era, with the aim of defining the scope of some digital technologies applied to cultural heritage. </li> <li> <a href="https://www.heritagedata.org/blog/">Heritage Data - Linked Data Vocabularies for Cultural Heritage</a>: a dataset which includes several cultural heritage thesauruses and vocabularies and is recognised as a reference point in the United Kingdom in the domain of cultural heritage. </li> </ul> The collection of concepts extracted from these four resources was composed of more than 60,000 terms, which have been refined as described in the next section.   ## Automatic validation of the controlled vocabulary In order to refine the collection of concepts to have a final set of relevant concepts and terms in the domain of Cultural Heritage, a semi-automatic validation has been applied to remove the irrelevant, too general, and ambiguous terms. To keep the relevant ones, the <a href="https://ncses.nsf.gov/pubs/nsb20206/specialization-and-impact-analysis-combined#:~:text=The%20specialization%20index%20(SI)%20is,the%20total%20output%20across%20all">specialization index (SI) </a>metric has been calculated for each of the keywords in the collection. In this case, the SI can be obtained measuring the fraction of publications with a keyword in a set of publications in the domain of Cultural Heritage and normalizing over the fraction of publications in the open domain with that keyword. After the calculation of the SI, all the keywords below a certain threshold are removed, and a manual supervision step is applied in order to remove non-pertinent keywords. An example of this automatic validation can be observed in the next table: <table> <tbody> <tr> <td> Keyword </td> <td> Specialization Index </td> <td> Automatic threshold </td> <td> Manual supervision </td> </tr> <tr> <td> male </td> <td> 0.27 </td> <td> Removed </td> <td> Accepted </td> </tr> <tr> <td> 3-d laser scanning </td> <td> 0.7 </td> <td> Removed </td> <td> Accepted </td> </tr> <tr> <td> 78 rpm records </td> <td> 20.7 </td> <td> Accepted </td> <td> Removed </td> </tr> <tr> <td> vienna </td> <td> 3.48 </td> <td> Accepted </td> <td> Removed </td> </tr> <tr> <td> radiocarbon dating </td> <td> 13.6 </td> <td> Accepted </td> <td> Accepted </td> </tr> <tr> <td> graffiti </td> <td> 25 </td> <td> Accepted </td> <td> Accepted </td> </tr> <tr> <td> bark painting </td> <td> 20.7 </td> <td> Accepted </td> <td> Accepted </td> </tr> <tr> <td> pompeii </td> <td> 16.23 </td> <td> Accepted </td> <td> Accepted </td> </tr> </tbody> </table> The SI of the final keywords can be used as a probabilistic metric for each keyword. The final list of keywords was manually curated by domain experts.   ## Evaluation of the controlled vocabulary The final controlled vocabulary was evaluated with an external dataset with the aim of calculating its degree of precision. The evaluation dataset was composed of a collection of articles in 4 journals unequivocally considered to fall within the domain of Cultural Heritage. These four journals were: (1) Journal Of Cultural Heritage, (2) Journal On Computing And Cultural Heritage, (3) Journal Of Cultural Heritage Management And Sustainable Development and (4) Digital Applications In Archaeology And Cultural Heritage. This collection was composed of 5,000 articles, considered as the positive set, and another collection of randomly selected 5,000 articles outside of the Cultural Heritage domain, considered as the false set. The Cultural Heritage vocabulary was applied to the evaluation data set, obtaining a 95% of precision. After a set of improvements on the vocabulary, based on the exploration of publications not identified in the first test and the false positive results, we obtained a 98% of precision. The application of the vocabulary taking advantage of the probability of each keyword as its weight of being in the domain did not improve the results, and for this reason the probabilistic approach was discarded.   ## Using the vocabulary to classify publications concerning Cultural Heritage The definition of the vocabulary does not, per se, allow to identify research contributions in Cultural Heritage: this is performed by actually matching the terms in the controlled vocabulary to the content of the gathered research textual records. To successfully carry out this task, a series of pattern matching rules must be defined to capture possible variants of the same concept, such as permutations of words within the concept and/or the presence of null words to be skipped. For this reason, we have carefully crafted matching rules that take into account permutations of words and that allow words within concept to be within a certain distance. In the following table we present some examples of the tagging process on some abstracts: <table> <tbody> <tr> <td> Publication title </td> <td> Publication abstract </td> </tr> <tr> <td> Egocentric visitor localization and artwork detection in cultural sites using synthetic data </td> <td> Computer vision and machine learning can be used in cultural heritage to augment the experience of visitors during the exploration of the cultural site, as well as to assist its management. To achieve such goals, two fundamental tasks should be addressed, i.e., localizing visitors and recognizing the observed artworks. Wearable cameras offer a convenient setting to address both tasks through the analysis of images acquired from the visitors’ points of view. However, the engineering of approaches to address such tasks generally requires large amounts of labeled data. We propose a tool which can be used to collect and automatically label synthetic visual data suitable to study image-based localization and artwork detection. The tool simulates a virtual agent navigating the 3D model of a real cultural site and automatically captures video frames along with the related ground truth camera poses and semantic masks indicating the position of artworks. We generate a dataset of synthetic images starting from the 3D model of a museum located in Siracusa, Italy. The experiments suggest that the proposed tool allows to drastically reduce the effort needed to collect and label data, providing a means to generate large-scale datasets suitable to study localization and artwork detection in cultural sites. </td> </tr> <tr> <td> Discovering Leonardo with artificial intelligence and holograms: A user study </td> <td> Cutting-edge visualization and interaction technologies are increasingly used in museum exhibitions, providing novel ways to engage visitors and enhance their cultural experience. Existing applications are commonly built upon a single technology, focusing on visualization, motion or verbal interaction (e.g., high-resolution projections, gesture interfaces, chatbots). This aspect limits their potential, since museums are highly heterogeneous in terms of visitors profiles and interests, requiring multi-channel, customizable interaction modalities. To this aim, this work describes and evaluates an artificial intelligence powered, interactive holographic stand aimed at describing Leonardo Da Vinci's art. This system provides the users with accurate 3D representations of Leonardo's machines, which can be interactively manipulated through a touchless user interface. It is also able to dialog with the users in natural language about Leonardo's art, while keeping the context of conversation and interactions. Furthermore, the results of a large user study, carried out during art and tech exhibitions, are presented and discussed. The goal was to assess how users of different ages and interests perceive, understand and explore cultural objects when holograms and artificial intelligence are used as instruments of knowledge and analysis. </td> </tr> <tr> <td> Hybrid query expansion using lexical resources and word embeddings for sentence retrieval in question answering </td> <td> Question Answering (QA) systems based on Information Retrieval return precise answers to natural language questions, extracting relevant sentences from document collections. However, questions and sentences cannot be aligned terminologically, generating errors in the sentence retrieval. In order to augment the effectiveness in retrieving relevant sentences from documents, this paper proposes a hybrid Query Expansion (QE) approach, based on lexical resources and word embeddings, for QA systems. In detail, synonyms and hypernyms of relevant terms occurring in the question are first extracted from MultiWordNet and, then, contextualized to the document collection used in the QA system. Finally, the resulting set is ranked and filtered on the basis of wording and sense of the question, by employing a semantic similarity metric built on the top of a Word2Vec model. This latter is locally trained on an extended corpus pertaining the same topic of the documents used in the QA system. This QE approach is implemented into an existing QA system and experimentally evaluated, with respect to different possible configurations and selected baselines, for the Italian language and in the Cultural Heritage domain, assessing its effectiveness in retrieving sentences containing proper answers to questions belonging to four different categories. </td> </tr> <tr> <td> "3D reconstruction and validation of historical background for immersive VR applications and games: The case study of the Forum of Augustus in Rome" </td> <td> "In the last decades, thanks to the success of the video games industry, the sector of technologies applied to cultural heritage has begun to envisage, in this domain, new possibilities for the dissemination of heritage and the study of the past through edutainment models. More recently, experimentation in the field of virtual archaeology has led to the development of virtual museums and interactive applications. Among these, the “serious game” segment – the application of interactive technologies to the cultural heritage domain – is rapidly growing, also including immersive VR technologies. Applied VR games and applications are characterized by a thorough historical background and a validated 3D reconstruction. Indeed, producing such products requires a tailored workflow and large effort in terms of time and professionals involved to guarantee such faithfulness. Drawing on our previous work in the field of virtual archaeology and referring to recent experiences related to the deployment of applied VR games on PlayStation VR, we describe and assess a workflow for the production of historically accurate 3D assets, targeting interactive, immersive VR products. The workflow is supported by the case study of the Forum of Augustus and different output applications, highlighting peculiarities and issues emerging from a multi and interdisciplinary approach. </td> </tr> </tbody> </table> Through this classification process, we identified projects and publications related to heritage, with different levels of relationship and relevance, but mostly relevant to understanding the research competencies in the domain. The resulting research records were reviewed by experts in the domain, given the occurrence of some false positives. Among the main strengths of this step, it’s worth mentioning the fact that the vocabulary is broad and not restricted to the field of Heritage Science (that is, to STEM applications in Cultural Heritage), as it takes advantage of a variety of available resources. Moreover, by looking directly at the textual data, instead of using the assigned bibliometric areas, we can better capture interdisciplinary research. The limitations of this approach were presented at the beginning of this document: for example, relevant texts could be missed if the correct pattern to match during the search is not found.   ## Vocabulary of concepts related to Key Enabling Technologies in the domain of Cultural Heritage and Culture For the development of this vocabulary, the definition of key enabling technologies in the domain of Cultural Heritage and Culture, was based on reference of the <a href="http://www.irpet.it/archives/53165">report 'Technologies, Cultural Heritage and Culture' published on  March 2019</a> by IRPET. A vocabulary for each Key Enabling Technology (hereafter, KET) was prepared by extracting the relevant concepts, words, technologies and examples from the Platform Report document 'Technologies, Cultural Heritage and Culture, within APPENDIX A. DESCRIPTION OF MAIN TECHNOLOGIES FOR ROADMAP (p. 45-61). Each vocabulary contains a set of terms divided into subdomains. The KETs have been divided into the following six groups: <ul> <li> ICT </li> <li> PHOTONICS, MICRO- AND NANO-ELECTRONICS </li> <li> PLATFORMS </li> <li> NANO AND BIOTECHNOLOGY, ADVANCED MATERIALS </li> <li> PARTICLE ANALYTICAL SYSTEMS </li> </ul> The initial keywords extracted from the document were enriched following the approach based on semantic keyword enrichment based on combination of concurrent keywords and word embeddings  (Duran-Silva et al., 2019; Duran-Silva et al., 2021). This second vocabulary has to be used in combination with the Cultural Heritage vocabulary to capture KETs within the domain of cultural heritage.   ## Use of the controlled vocabulary The definition of the vocabulary does not, per se, allow identifying STI contributions to the domain: this activity in fact boils down to actually matching the terms in the controlled vocabulary to the content of the gathered STI textual records. To successfully carry out this task, a series of pattern matching rules must be defined to capture possible variants of the same concept, such as permutations of words within the concept and/or the presence of null words to be skipped. For this reason, we have carefully crafted matching rules that take into account permutations of words and that allow words within concept to be within a certain distance. Some relatively ambiguous keywords (which may match unwanted pieces of text), have a set of associated “extra” terms. These “extra” terms are defined as further terms that must co-appear, in the same sentence, together with their associated ambiguous keywords. SIRIS Academic has developed the <a href="https://github.com/sirisacademic/VocTagger">voc_tagger tool</a>, a multiprocess information extraction system able to identify hidden knowledge in textual documents using “controlled vocabularies”, openly available at GitHub and compatible with these controlled vocabularies.   ## Bibliography Harpring, P. (2010). Introduction to controlled vocabularies: terminology for art, architecture, and other cultural works. Getty Publications. Nicolau Duran-Silva, Enric Fuster, Francesco Alessandro Massucci, César Parra-Rojas, Arnau Quinquillà, Fernando Roda, Bernardo Rondelli, Nicandro Bovenzi, & Chiara Toietta. (2021). A controlled vocabulary for research and innovation in the field of Artificial Intelligence (AI) (Version 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5591987 Duran-Silva, Nicolau, Fuster, Enric, Massucci, Francesco Alessandro, & Quinquillà, Arnau. (2019). A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals (1.2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3567769

opencc-ncJul 2023View details →

Experimental Protocol on Creative Engagement and Meaning Creation in Interactive Experiences for Cultural Heritage. Participants Reinterpretations

The following document contains the material produced for the testing of the "caring prototype" MyTISSE, an interactive user experience on Matisse's painting Bathers by a river (Art Institute of Chicago). Focusing on the change of the pigments made by the artist during the gestation of this canvas, the UX exploits creative engagement to catalyze meaning creation processes. This pubblication contains the images of participants' reinterpretations. All the participants agreed to the reuse and sharing of these data for academic purposes, filling in an ad hoc privacy form.

opencc-by-4.0Jul 2018View details →

Modelling, cataloging, analysing cultural heritage

During the first Project Presentation Session on Wednesday 18.07.2018 14:15 - 15:45 the following 3 projects were presented: <ul> <li>Massoomeh Niknia (Kharazmi University, Theheran, Iran): "Migrating information from Iranian excavation reports: comparing semantic mark-up to information extraction"</li> <li>Giuditta Cirnigliaro (Rutgers University, USA): "The Digital Annotation of Leonardo's Library Items: A Practice-Led Diagrammatic Model for Developing Omeka Exhibits"</li> <li>Simon Gabay (UniNe, Neuchâtel, Switzerland): "A catalogue of 17th c. French autograph manuscripts"</li> </ul>

opencc-byJul 2022View details →

Caesar Statue Cultural Heritage using Scanner

Source: Objaverse 1.0 / Sketchfab

opencc-by-4.0Apr 2022View details →

User Evaluation and Metrics Analysis of a Prototype Web-based Federated Search Engine for Art and Cultural Heritage

This dataset includes the quantitative data of the usage during the evaluation phase of a prototype web-based federated search engine for art and cultural heritage related content. The metrics which resulted in the dataset were in the form of a timeline of actions taken from a user (evaluator) in the course of a single session of interaction with the platform. A total of 20 different metrics were being monitored regarding the usage of the search engine, including submitting a query, a voice query, preforming a visual search, viewing a result, viewing a visual search result, updating an avatar, editing a user profile or changing user preferences, bookmarking and removing bookmarks of results and visual search results, using text to speech of all the various elements, opening the source view of a result and clicking a concept tag. All metrics included the timestamp of the event taking place and the value of the related event (e.g. the term of a search query).

opencc-by-4.0May 2024View details →

A Bibliometric Insight into Immersive Technologies for Cultural Heritage Preservation

Open the record for dataset details and reuse information.

opencc-by-4.0May 2024View details →

Serbian Intangible Cultural Heritage in the Western Balkans: Perils and Prospects of Inclusive Research and Safeguarding (SICHWEB) project 1st year datasets

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opencc-by-4.0Jun 2024View details →

Addressing bias in digital cultural heritage collections metadata: the example of the DE-BIAS project

Open the record for dataset details and reuse information.

opencc-zeroOct 2019View details →

Supplementary material 1 from: Valkó O, Tóth K, Kelemen A, Miglécz T, Radócz S, Sonkoly J, Tóthmérész B, Török P, Deák B (2018) Cultural heritage and biodiversity conservation – plant introduction and practical restoration on ancient burial mounds. Nature Conservation 24: 65-80. https://doi.org/10.3897/natureconservation.24.20019

Supplementary material 1 from: Valkó O, Tóth K, Kelemen A, Miglécz T, Radócz S, Sonkoly J, Tóthmérész B, Török P, Deák B (2018) Cultural heritage and biodiversity conservation – plant introduction and practical restoration on ancient burial mounds. Nature Conservation 24: 65-80. https://doi.org/10.3897/natureconservation.24.20019

opencc-by-4.0Dec 2020View details →

Results Data for the Circular City and Adaptive Reuse of Cultural Heritage Opportunity Index

The data file provides the results data for the article, "Circular City and Adaptive Reuse of Cultural Heritage Index: Measuring the Investment Opportunity in Europe" written by Dr. Gillian Foster and Dr. Ruba Saleh.

opencc-by-4.0Mar 2023View details →

MATERIALS OF ARCHAEOLOGICAL RESEARCH OF THE ARCHAEOLOGICAL HERITAGE OBJECT CULTURAL LAYER OF VORONEZH ON THE TERRITORY OF THE LAND PLOT AT 1, KLUBNAYA STREET AND 30D, 20-LETIYA OKTYABRYA STREET

Archaeological research on the land plot at the address: Voronezh, 1, Klubnaya Street, and 30d, 20-letiya Oktyabrya Street, was carried out as part of the implementation of the section of project documentation to ensure the safety of the identified cultural heritage site "Cultural layer of the city of Voronezh". As a result of the work, additional information was obtained on the history of the coastal part of the city in the XIX-th-XX-th centuries.

opencc-by-4.0Mar 2023View details →

The classification of cultural heritage buildings in Athens using deep learning techniques

Dataset of images from buildings for classification tasks.

Climate change impact on vernacular and archaeological cultural heritage building materials in Europe and Latin America

The analysis and interpretation of past climate data and simulations of climate models for future periods will allow us to study the impacts of climate change on cultural Heritage. The H2020 SCORE project (Sustainable COnservation and REstoration of built cultural heritage – 2020-2024) centres on two types of cultural heritage that differ by their geographical location and therefore their climatic conditions, as are vernacular cultural heritage in Europe (6 sites in Denmark, France, Italy and Spain) and archaeological sites in Latin America (2 sites in Mexico). All the cases study share a fundamental similarity in terms of the use of materials and construction techniques. One objective of the project is to quantify the impacts of continuous climate and pollution changes on building materials of cultural heritage under future IPCC socioeconomic scenarios with high and low mitigation measures at years 2030, 2050 and 2070, using peer-reviewed dose-response equations. We also focus on the degradation effects due to extreme events (heatwave, dry spells and extreme rainfall/flood) of each of the selected regions of our cases study. We apply these climatic conditions past and future) in different models, based on scientific literature, that allow estimate the weathering of the materials employed in the construction of cultural heritage buildings. Finally, we deliver preliminary results for a “cocktail of extreme events” based on the literature review and experiment in laboratory specifically designed to quantify the damages and degradation of building materials due to a realistic series of adverse climate and pollution events. We present here some results of future weathering (2081-2100) compared to near par (2001-2020) for different weathering process under the SSP5- RCP 8.5 scenario. The evolution of each process is different and it is different form one site to the other.

APPENDIX C: PRECUP MAPAMANA: Full list of Culturally and Historically Significant Heritage Assets and Sites in Recto Avenue (NCCA, 2022)

APPENDIX C: PRECUP MAPAMANA: Full list of Culturally and Historically Significant Heritage Assets and Sites in Recto Avenue (NCCA, 2022) for Memoryscapes in Recto-spection: Visualizing Avenida, Recto, and Carriedo, Manila as Virtual Memoryscapes  through immersive mobile technologies and digital heritage interpretation. Thesis Adviser: Dr. Cathe Desiree S. Nadal, Ph. D.

APPENDIX D: PRECUP MAPAMANA: Full list of Culturally and Historically Significant Heritage Assets and Sites in Quiapo District (NCCA, 2022

APPENDIX D: PRECUP MAPAMANA: Full list of Culturally and Historically Significant Heritage Assets and Sites in Quiapo District (NCCA, 2022 in the Recto-Avenida-Carriedo Strip (NCCA, 2022) for Memoryscapes in Recto-spection: Visualizing Avenida, Recto, and Carriedo, Manila as Virtual Memoryscapes  through immersive mobile technologies and digital heritage interpretation. Thesis Adviser: Dr. Cathe Desiree S. Nadal, Ph. D.

APPENDIX B: PRECUP MAPAMANA: Full list of Culturally and Historically Significant Heritage Assets and Sites in Rizal Avenue (NCCA, 2022)

APPENDIX B: PRECUP MAPAMANA: Full list of Culturally and Historically Significant Heritage Assets and Sites in Rizal Avenue (NCCA, 2022) for Memoryscapes in Recto-spection: Visualizing Avenida, Recto, and Carriedo, Manila as Virtual Memoryscapes  through immersive mobile technologies and digital heritage interpretation. Thesis Adviser: Dr. Cathe Desiree S. Nadal, Ph. D.