The field of epistemic logic developed into an interdisciplinary area focused on explicating epistemic issues in, for example, artificial intelligence, computer security, game theory, economics, multiagent systems and the social sciences. Inspired, in part, by issues in these different ‘application’ areas, in this paper I propose an epistemic logic T for metadata extracted from scientific papers on COVID-19. More in details, I introduce a structure S to syntactically and semantically modelling metadata extracted with systems for extracting structured (...) metadata from scientific articles in a born-digital form. These systems will be considered, in the logical model created, as ‘Metadata extraction agents’. In this case MEA taken into consideration are CERMINE and TeamBeam. In an increasingly data-driven world, modelling data or metadata means to help systematise existing information and support the research community in building solutions to the COVID-19 pandemic. (shrink)

In this article we develop a logical model for automatic extraction of structured metadata. We introduce a new predicate???? – reads ‘extract’ – and a structure???? to syntactically and semantically define metadata extracted with any automatic metadata extraction system. These systems will be considered, in the logical model created, as knowledge extraction agents. In this case KEA taken into consideration is CERMINE, a comprehensive open-source system for extracting structured metadata from scientific articles in a born-digital form.

In an increasingly data-driven world, the question of data – or metadata – veracity is now a central issue not only in the world of information but also in the legal one. Data veracity describes a closeness to truth on a higher level than a measure such as accuracy does. High veracity data is data that can be relied upon when making decisions, thus reducing the risk of basing choices on untrue information. The article uses epistemic logic to model (...) structured metadata automatically extracted from legal papers, and the tools of metaontology to propose a definition of veracity as truthmaker. (shrink)

Decisions of regulatory government bodies and courts affect many aspects of citizens’ lives. These organizations and courts are expected to provide timely and coherent decisions, although they struggle to keep up with the increasing demand. The ability of machine learning (ML) models to predict such decisions based on past cases under similar circumstances was assessed in some recent works. The dominant conclusion is that the prediction goal is achievable with high accuracy. Nevertheless, most of those works do not consider important (...) aspects for ML models that can impact performance and affect real-world usefulness, such as consistency, out-of-sample applicability, generality, and explainability preservation. To our knowledge, none considered all those aspects, and no previous study addressed the joint use of metadata and text-extracted variables to predict administrative decisions. We propose a predictive model that addresses the abovementioned concerns based on a two-stage cascade classifier. The model employs a first-stage prediction based on textual features extracted from the original documents and a second-stage classifier that includes proceedings’ metadata. The study was conducted using time-based cross-validation, built on data available before the predicted judgment. It provides predictions as soon as the decision date is scheduled and only considers the first document in each proceeding, along with the metadata recorded when the infringement is first registered. Finally, the proposed model provides local explainability by preserving visibility on the textual features and employing the SHapley Additive exPlanations (SHAP). Our findings suggest that this cascade approach surpasses the standalone stages and achieves relatively high Precision and Recall when both text and metadata are available while preserving real-world usefulness. With a weighted F1 score of 0.900, the results outperform the text-only baseline by 1.24% and the metadata-only baseline by 5.63%, with better discriminative properties evaluated by the receiver operating characteristic and precision-recall curves. (shrink)

This paper initially follows the final part of the debate between singularism and descriptivism to the point of convergence, and discusses the notion of acquaintanceless singular thought. Then a sketch of a mental files model is presented. Firstly, the triggering mechanisms for opening files are discussed. Two kinds of discourse situations, acquaintance-situations and decoding-situations, are identified and different triggering mechanisms are postulated for each. Secondly, a bipartite structure of a file is introduced, combining an objectual part, encompassing what traditionally has (...) been associated with the notion of a mental file, serving the purpose of storing information about the referent of the file, and a metadata part, serving the purpose of storing information about the file itself. Being capable of encoding a variety of types of mental files, this structure is then employed to illustrate how singularity/descriptivity of the files can be manipulated and how we can account for the cognitive discernibility of files containing identical objectual information and grounded with the same acquaintance relations. (shrink)

Organizations need enterprise content management (ECM) to play a more important role in business initiatives as video, social networking, analytics and other trends place greater demands on ECM applications. Gartner has revised its Maturity Model for ECM to reflect these new demands. Enterprise architects, information managers and leaders of ECM initiatives can use the model to assess where their organization is today and what level of maturity it must reach to achieve its business goals. Key Findings Gartner's Maturity Model for (...) ECM defines five levels of increasing ECM maturity: Initial (Level 1), Opportunistic, Organized, Enterprise and Transformative (Level 5). ECM maturity is about achieving the right level of ECM capabilities for a particular organization, and optimizing its investment. The majority of organizations are at the Opportunistic and Organized levels. At first, information governance occurs within the scope of tactical content management projects, which typically span two or three information silos. People perform governance roles informally. At Level 3, the ECM strategy supports organization goals, and ECM leaders use business metrics to measure their program. Recommendations At Level 1, look for areas where content silos hurt the business and operations. Then establish governance to start bridging the gaps. At Level 2, work with business process owners to understand the role of content. Identify areas where ECM and business process management (BPM) suites can be integrated. At Level 3, survey the metadata schemas in use for content within the organization. Work toward normalizing and standardizing all metadata efforts across the organization. (shrink)

Large language models (LLMs) such as ChatGPT are opening up new areas of research and teaching potential across a variety of domains. The purpose of the present conceptual paper is to map this new terrain from the point of view of Critical Discourse Studies (CDS). We demonstrate that the usage of LLMs raises concerns that definitely fall within the remit of CDS; among them, power and inequality. After an initial explanation of LLMs, we focus on three key areas of reflection. (...) The first is a general stock-taking, where we look at CDS’ theoretical underpinnings and what they imply for working with AI-generated language data. The second issue is authorship, where we assess the traceability of linguistic metadata and the ethically sensitive situation with regard to ownership of texts. The third area is linguistic homogenisation, where we examine how LLM usage privileges the mainstream. Afterwards, we explore ways in which LLMs could be used in research, and we discuss the implications of exploring their use in the classroom through a CDS lens. We close the paper with some observations on likely future developments in AI and how CDS can contribute with its distinctive theoretical, methodological and critical apparatus. (shrink)

This article investigates the role of Scholarly Digital Editions in advancing textual scholarship, with a focus on Judeo-Arabic, a unique linguistic variety using Hebrew script to represent Arabic. It proposes a stratified model for Scholarly Digital Editions to handle Judeo-Arabic’s orthographic complexities, including transcription, script conversion, normalization, and metadata integration. The study highlights the critical role of managing noise in textual editing, particularly during data acquisition, where any distortion or omission of orthographic elements can compromise scholarly integrity. A case (...) study of a medieval Judeo-Arabic manuscript illustrates the model’s application, highlighting how it preserves textual integrity and enriches scholarly analysis. This methodology not only addresses Judeo-Arabic specific challenges but is also adaptable to other allographic systems. (shrink)

Technological innovations, despite their several benefits, may have drawbacks, thus, they need a control mechanism or directional channel. Responsible innovation (RI) has gained popularity in technology-intensive countries as a way to regulate otherwise uncontrollable and radical technological innovations. However, existing RI research lacks a clear theoretical foundation and has not adequately addressed the commercial and performance aspects of innovative products and firms. The current research proposes an empirically testable model for RI by conducting a structured literature review, focusing on the (...) commercial aspect of innovative products and firms’ sustainability performance in the financial, social, and environmental dimensions. The study suggests a link between RI and the resource-based theory of the firm and proposes that RI can be seen as a distinctive competency developed through the firm’s resources and capabilities. The model would help enterprises achieve ethical and social acceptability and improve sustainability performance. Metadata examination of 98 articles yielded insights. The findings and future research directions of this study provide new insights for business strategy and policy. (shrink)

According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone to (...) be able to assimilate and mine data from related investigations for purposes of meta-analysis. While computers have the potential for assisting investigators in the extraction, management and analysis of these data, information contained in the traditional journal publication is still largely unstructured, free-text descriptions of study design, experimental application and results interpretation, making it difficult for computers to gain access to the content of what is being conveyed without significant manual intervention. In order to circumvent these roadblocks and make the most of the output from the biomedical research enterprise, a variety of related standards in knowledge representation are being developed, proposed and adopted in the biomedical community. In this chapter, we will explore the current status of efforts to develop minimum information standards for the representation of a biomedical experiment, ontologies composed of shared vocabularies assembled into subsumption hierarchical structures, and extensible relational data models that link the information components together in a machine-readable and human-useable framework for data mining purposes. (shrink)

The European Union is working towards harmonizing legislation across Europe, in order to improve cross-border interchange of legal information. This goal is supported for instance via standards such as the European Law Identifier and the European Case Law Identifier, which provide technical specifications for Web identifiers and suggestions for vocabularies to be used to describe metadata pertaining to legal documents in a machine readable format. Notably, these ECLI and ELI metadata standards adhere to the RDF data format which (...) forms the basis of Linked Data, and therefore have the potential to form a basis for a pan-European legal Knowledge Graph. Unfortunately, to date said specifications have only been partially adopted by EU member states. In this paper we describe a methodology to transform the existing legal information system used in Austria to such a legal knowledge graph covering different steps from modeling national specific aspects, to population, and finally the integration of legal data from other countries through linked data. We demonstrate the usefulness of this approach by exemplifying practical use cases from legal information search, which are not possible in an automated fashion so far. (shrink)

Digital cultural archives and databases are promising an era of heritage democratization and an enhancement of the role of arts in everyday cultures. It is hoped that mass digitization initiatives in many corners of the world can facilitate the secure preservation of human cultural heritage, with easy access and diverse ways for creative reuse. Understanding the dialogic processes within these increasingly vast databases necessitates a dynamic conceptualization of data they contain. The paper argues that this can be found in Juri (...) Lotman’s cultural semiotic notion of text and text’s functions in culture. It elaborates on the three key characteristics of text – expression, boundary, and structure – as manifested within the digital semiosphere. At the same time, the textual dialogues within digital archives are increasingly conditioned by metadata, which is hereby conceptualized as metalanguage inducing a modeling effect on archived texts and defining their possible sphere of dynamics. To balance the explanations of creative operations of digital archives, the paper also demonstrates their auto-communicative mechanisms for facilitating cultural continuities and stability. (shrink)

Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential uses of their biological materials when they donate samples for future research. We propose a novel consent framework which we call “demonstrated consent” that leverages blockchain technology and generative AI to address this problem. In a demonstrated consent model, each donated sample is associated with a unique non-fungible token (NFT) on a blockchain, which records in its (...) class='Hi'>metadata information about the planned and past uses of the sample in research, and is updated with each use of the sample. This information is accessible to a large language model (LLM) customized to present this information in an understandable and interactive manner. Thus, our model uses blockchain and generative AI technologies to track, make available, and explain information regarding planned and past uses of donated samples. (shrink)

Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential uses of their biological materials when they donate samples for future research. We propose a novel consent framework which we call “demonstrated consent” that leverages blockchain technology and generative AI to address this problem. In a demonstrated consent model, each donated sample is associated with a unique non-fungible token (NFT) on a blockchain, which records in its (...) class='Hi'>metadata information about the planned and past uses of the sample in research, and is updated with each use of the sample. This information is accessible to a large language model (LLM) customized to present this information in an understandable and interactive manner. Thus, our model uses blockchain and generative AI technologies to track, make available, and explain information regarding planned and past uses of donated samples. (shrink)

In recent years, the amount of data in the world is growing rapidly. Data growth also occurs in the government sector. All ministries and institutions at every level are data producers. These government-owned data have a high potential if they can be used properly. Open government data can stimulate innovation and economic growth and enhance business models. In order to increase the willingness of citizens to use open government data and enjoy the benefits mentioned, the quality of open government data (...) needs to be improved. The quality of open government data encompasses a variety of dimensions and criteria. Also, the importance of each dimension and criterion in increasing the quality of open government data is different. Therefore, we are faced with a complex system that requires proper decision-making and management. In fact, we are dealing with decision-making in the complex management system. Given the importance of this issue, the purpose of this study is to provide a new and comprehensive method to improve the quality of open government data and increase the willingness of citizens to use the data by considering the complex network of citizens and organizations. For this purpose, library studies have been used to extract comprehensive and effective dimensions and criteria. The statistical population includes all articles related to the criteria of improving the quality of open government data and increasing the willingness of citizens to use the data. The probabilistic sampling method of simple random samples has been used, and 10 articles in this field have been reviewed. After extracting the criteria as well as the data of 112 governmental organizations and institutions related to each criterion from the open data portal, the complex network of citizens and governmental organizations and institutions has been analyzed in order to identify high-degree centrality organizations. Then, the data characteristics of the organizations that were most desired by the citizens were extracted using data mining techniques including the regression model. Also, field method and multicriteria decision-making technique including the DEMATEL technique have been used to express the solutions and identify the cause-and-effect relationships between the solutions. The criteria extracted in improving the quality of open government data and increasing the willingness of citizens to use the data are included: “data originality,” “license openness,” “up-to-datedness,” “data access,” “metadata completeness,” “number of data sets,” “format openness,” “nondiscrimination,” “understandable,” “number of categories of data sets,” “free,” “lack of missing data,” “data request ability,” “visualization,” “feedback,” and “data subject matter.” Based on the results obtained from the analysis of the complex network and the regression model, the criterion of “society subject” with a coefficient of 72.564 and a positive sign has the greatest impact on increasing the number of citizens' visits to open government data. After that, the criterion of “format openness” with a coefficient of 52.682 and a positive sign has the second rank in increasing the number of visits. Extracting comprehensive and effective criteria in improving the quality of open government data and increasing citizens' willingness to use data, calculating the weight and importance of each criterion by analyzing the complex network of citizens and organizations, as well as providing solutions, can help managers in decision-making and proper management in the complex system of citizens and government organizations. (shrink)

SKOS (Simple Knowledge Organization System) is a recommendation from the World Wide Web Consortium (W3C) for representing controlled vocabularies, taxonomies, thesauri, classifications, and similar systems for organizing and indexing information as linked data elements in the Semantic Web, using the Resource Description Framework (RDF). The SKOS data model is centered on “concepts”, which can have preferred and alternate labels in any language as well as other metadata, and which are identified by addresses on the World Wide Web (URIs). Concepts (...) are grouped into hierarchies through “broader” and “narrower” relations, with “top concepts” at the broadest conceptual level. Concepts are also organized into “concept schemes”, also identified by URIs. Other relations, mappings, and groupings are also supported. This article discusses the history of the development of SKOS and provides notes on adoption, uses, and limitations. (shrink)

The ethics of describing and indexing works which have an element of deception is an important topic within the arena of knowledge organization (KO). However, what happens if the unreal element is for artistic purposes and is part of the experience of the document? The focus of this article is on the KO of art documentation. It considers art documents where unreality and mistruth are part of a document’s creative and artistic purpose. Three examples of exhibition documentation for contemporary art (...) are explored. These illuminate the KO implications of unreal elements in artworks, exhibitions and documents, and the interplay between them. Three models are then presented relating to the KO of unreality. Model one shows how the wishes of the creator are a significant part of ethical KO for art and the ethical KO decisions which result from the performative and experiential aspects of art documentation. Model two illustrates how the placement of the unreality in relation to metadata creation can have a critical impact on ethical decisions in KO. Model three posits unreal-ness as a novel type of information about metadata creation, introducing categories such as motive for the deception. It shows how this original way of contemplating applied ethics in KO is vital for all ethically challenging works. Ultimately, considering the KO ethics of art documentation extends our thinking about how to deal with deception and unreality and adds an important aesthetic-ethical dimension to the corpus of work on KO ethics. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

Patent landscaping is the process of finding patents related to a particular topic. It is important for companies, investors, governments, and academics seeking to gauge innovation and assess risk. However, there is no broadly recognized best approach to landscaping. Frequently, patent landscaping is a bespoke human-driven process that relies heavily on complex queries over bibliographic patent databases. In this paper, we present Automated Patent Landscaping, an approach that jointly leverages human domain expertise, heuristics based on patent metadata, and machine (...) learning to generate high-quality patent landscapes with minimal effort. In particular, this paper describes a flexible automated methodology to construct a patent landscape for a topic based on an initial seed set of patents. This approach takes human-selected seed patents that are representative of a topic, such as operating systems, and uses structure inherent in patent data such as references and class codes to “expand” the seed set to a set of “probably-related” patents and anti-seed “probably-unrelated” patents. The expanded set of patents is then pruned with a semi-supervised machine learning model trained on seed and anti-seed patents. This removes patents from the expanded set that are unrelated to the topic and ensures a comprehensive and accurate landscape. (shrink)

This study investigates the types of misinformation spread on Twitter that evokes scientific authority or evidence when making false claims about the antimalarial drug hydroxychloroquine as a treatment for COVID-19. Specifically, we examined tweets generated after former U.S. President Donald Trump retweeted misinformation about the drug using an unsupervised machine learning approach called the biterm topic model that is used to cluster tweets into misinformation topics based on textual similarity. The top 10 tweets from each topic cluster were content coded (...) for three types of misinformation categories related to scientific authority: medical endorsements of hydroxychloroquine, scientific information used to support hydroxychloroquine’s use, and a comparison group that included scientific evidence opposing hydroxychloroquine’s use. Results show a much higher volume of tweets featuring medical endorsements and use of supportive scientific information compared to accurate and updated scientific evidence, that misinformation-related tweets propagated for a longer time frame, and the majority of hydroxychloroquine Twitter discourse expressed positive views about the drug. Metadata from Twitter accounts found that prominent users within misinformation discourse were more likely to have media or political affiliation and explicitly expressed support for President Trump. Conversely, prominent accounts within the scientific opposition discourse primarily consisted of medical doctors or scientists but had far less influence in the Twitter discourse. Implications of these findings and connections to related social media research are discussed, as well as cognitive mechanisms for understanding susceptibility to misinformation and strategies to combat misinformation spread via online platforms. (shrink)

Researchers in the fields of sign language and gesture studies frequently present their participants with video stimuli showing actors performing linguistic signs or co-speech gestures. Up to now, such video stimuli have been mostly controlled only for some of the technical aspects of the video material, leaving open the possibility that systematic differences in video stimulus materials may be concealed in the actual motion properties of the actor’s movements. Computer vision methods such as OpenPose enable the fitting of body-pose models (...) to the consecutive frames of a video clip and thereby make it possible to recover the movements performed by the actor in a particular video clip without the use of a point-based or markerless motion-tracking system during recording. The OpenPoseR package provides a straightforward and reproducible way of working with these body-pose model data extracted from video clips using OpenPose, allowing researchers in the fields of sign language and gesture studies to quantify the amount of motion pertaining only to the movements performed by the actor in a video clip. These quantitative measures can be used for controlling differences in the movements of an actor in stimulus video clips or, for example, between different conditions of an experiment. In addition, the package also provides a set of functions for generating plots for data visualization, as well as an easy-to-use way of automatically extracting metadata from large sets of video files. (shrink)

Great progress to digitize the world’s available Biodiversity and Biogeography data have been made recently, but managing data from many different providers and research domains still remains a challenge. A review of the current landscape of metadata standards and ontologies in Biodiversity sciences suggests that existing standards, such as the Darwin Core terminology, are inadequate for describing Biodiversity data in a semantically meaningful and computationally useful way. As a contribution to fill this gap, we present an ontology-based system, called (...) BiGe-Onto, designed to manage data together from Biodiversity and Biogeography. As data sources, we use two internationally recognized repositories: the Global Biodiversity Information Facility (GBIF) and the Ocean Biogeographic Information System (OBIS). BiGe-Onto system is composed of (i) BiGe-Onto Architecture (ii) a conceptual model called BiGe-Onto specified in OntoUML, (iii) an operational version of BiGe-Onto encoded in OWL 2, and (iv) an integrated dataset for its exploitation through a SPARQL endpoint. We will show use cases that allow researchers to answer questions that manage information from both domains. (shrink)

With the ever-growing accessibility of case law online, it has become challenging to manually identify case law relevant to one’s legal issue. In the Netherlands, the planned increase in the online publication of case law is expected to exacerbate this challenge. In this paper, we tried to predict whether court decisions are cited by other courts or not after being published, thus in a way distinguishing between more and less authoritative cases. This type of system may be used to process (...) the large amounts of available data by filtering out large quantities of non-authoritative decisions, thus helping legal practitioners and scholars to find relevant decisions more easily, and drastically reducing the time spent on preparation and analysis. For the Dutch Supreme Court, the match between our prediction and the actual data was relatively strong (with a Matthews Correlation Coefficient of 0.60). Our results were less successful for the Council of State and the district courts (MCC scores of 0.26 and 0.17, relatively). We also attempted to identify the most informative characteristics of a decision. We found that a completely explainable model, consisting only of handcrafted metadata features, performs almost as well as a less well-explainable system based on all text of the decision. (shrink)

We present a novel annotated dataset of legal cases pertaining to Article 6 – the right to a fair trial – of the European Convention on Human Rights (ECHR). This dataset will serve as a useful resource to the research community, to assist in the training and evaluation of AI systems designed to embody the legal reasoning involved in determining the appropriate legal outcome from a description of the case material. The annotations were applied to provide finer-grain classifications of legal (...) cases at the document level. Each classification label was sourced from a domain knowledge model, derived with legal expert guidance and known as an Angelic Domain Model (ADM), such that the classifications correspond to the actual legal rationales used by the Court when determining the outcome of a given case. We discuss our annotation pipeline, including annotator training, inter-annotator reliability evaluation, and the dissemination of the annotation outputs and associated metadata. (shrink)

The demand for integrating and sharing heterogeneous data online has attracted the interest of cultural institutions in making information access and retrieval more effective via Semantic Web technologies. The present study proposes a digital repository for 3D scans of modernist sculptures in public spaces in the city of Rio de Janeiro, Brazil, with a view to ensuring access, use, reuse and preservation of this information. This is a qualitative exploratory experimental study based on the scientific literature and specific empirical material. (...) It presents the analysis results of vocabularies for physical artifact documents and their digital counterparts on the Semantic Web and a discussion on how these align with the nature of the metadata determined here, as well as a metadata modeling prototype implemented on the Tainacan platform and aimed at cataloging digital 3D replicas. We claim that the proposed model for documenting cultural heritage assets on Tainacan is easy to implement, in that it uses accessible technology with a wide internet user base, highly expressive in its descriptions of 3D and multimedia content and based on well-established metadata and ontology standards recommended by regulatory bodies and communities such as the World Wide Web Consortium and International Organization for Standardization. Keywords: networked heritage documents, digital repositories, 3D digitization, semantic annotation. (shrink)

Background Neuroscientific approaches have historically triggered changes in the conception of creativity and artistic experience, which can be revealed by noting the intersection of these fields of study in terms of variables such as global trends, methodologies, objects of study, or application of new technologies; however, these neuroscientific approaches are still often considered as disciplines detached from the arts and humanities. In this light, the question arises as to what evidence the history of neurotechnologies provides at the intersection of creativity (...) and aesthetic experience. Methods We conducted a century-long bibliometric analysis of key parameters in multidisciplinary studies published in the Scopus database. Screening techniques based on the PRISMA method and advanced data analysis techniques were applied to 3612 documents metadata from the years 1922 to 2022. We made graphical representations of the results applying algorithmic and clusterization processes to keywords and authors relationships. Results From the analyses, we found a) a shift from a personality-focus quantitative analysis to a field-focus qualitative approach, considering topics such as art, perception, aesthetics and beauty; b) The locus of interest in fMRI-supported neuroanatomy has been shifting toward EEG technologies and models based on machine learning and deep learning in recent years; c) four main clusters were identified in the study approaches: humanistic, creative, neuroaesthetic and medical; d) the neuroaesthetics cluster is the most central and relevant, mediating between creativity and neuroscience; e) neuroaesthetics and neuroethics are two of the neologism that better characterizes the challenges that this convergence of studies will have in the next years. Conclusions Through a longitudinal analysis, we evidenced the great influence that neuroscience is having on the thematic direction of the arts and humanities. The perspective presented shows how this field is being consolidated and helps to define it as a new opportunity of great potential for future researchers. (shrink)

With the rapid growth of online product reviews, many users refer to others’ opinions before deciding to purchase any product. However, unfortunately, this fact has promoted the constant use of fake reviews, resulting in many wrong purchase decisions. The effective identification of deceptive reviews becomes a crucial yet challenging task in this research field. The existing supervised learning methods require a large number of labeled examples of deceptive and truthful opinions by domain experts, while the available unsupervised learning methods are (...) inefficient because they depend on the features of reviewers to detect each fake review. Therefore, by focusing on the detection efficiency problem and the limitation of large amount of labeled examples dependence, in this paper, we proposed an effective semisupervised learning approach for detecting spam reviews. Firstly, a time series model of all the reviews of a product is constructed, and then the suspected time intervals are captured based on the burst review increases in these intervals. Secondly, a co-training two-view semisupervised learning algorithm was performed in each captured interval, in which linguistic cues, metadata, and user purchase behaviors were synthetically employed to classify the reviews and check whether they are spam ones or not. A series of numerical experiments on a real dataset acquired from Taobao.com have confirmed the effectiveness of the proposed model, not only reaping benefits in terms of time efficiency and high accuracy but also overcoming the shortcomings of supervised learning methods, which depend on large amounts of labeled examples. And a trade-off balance was obtained between accuracy and efficiency. (shrink)

Using the example of the Herzog August Bibliothek, the paper shows how (medieval) manuscripts are currently catalogued in the digital environment and how the data is published and shared with other relevant communities. The paper focuses both on the process of data production as well as the exchange and re-use of data. In particular, the paper will discuss the challenges of distributing the data into non-specialised databases. Two elements are crucial here: firstly, the standardised modelling of manuscript-related information, including (...) semantic enrichment. Secondly, the challenge of providing as much data as possible on the Web and offering interfaces to access the data. (shrink)

" In Imagination and the Meaningful Brain, psychoanalyst Arnold Modell claims that subjective human experience must be included in any scientific...

Digital Rights Management (DRM) covers the description, identification, trading, protection, monitoring and tracking of all forms of rights over both tangible and intangible assets. The Digital Object Identifier (DOI) system provides a framework for the persistent identification of entities involved in this domain. Although the system has been very well designed to manage object identifiers, some important questions relating to the creation and assignment of identifiers are left open. The paradigm of a Referent Tracking System (RTS) recently advanced in the (...) healthcare and life sciences environment is able to fill these gaps. This is demonstrated by pointing out inconsistencies in the existing DOI models and by showing how they can be corrected using an RTS. (shrink)

Abstract.Since the gene splicing debates of the 1980s, the public has been exposed to an ongoing sequence of genetic and reproductive technologies. Many issue areas have outcomes that lose track of people's inner values or engender opposing religious viewpoints defying final resolution. This essay relocates the discussion of what is an acceptable application from the individual to the societal level, examining technologies that stand to address large numbers of people and thus call for policy resolution, rather than individual fiat, in (...) their application. A major source of guidance is the “Genetic Frontiers” series of professional dialogues and conferences held by the National Conference for Community and Justice from 2002 to 2004. Genetic testing, human gene therapy, genetic engineering of plants and animals, and stem cell technology are examined. While differences in perspective on the beginning of life persist, a stepwise approach to the examination of genetic testing reveals areas of general agreement. Stewardship of life, human co‐creativity with the divine, and social justice help define the bounds of application of genetic engineering and therapy; compassionate care plays a major role in establishing stem cell policy. Active, sustained dialogue is a useful resource for enabling sharing of religious values and crystallization of policies. (shrink)

Aristotle is oftentimes viewed through a strictly philosophical lens as heir to Plato and has having introduced logical rigor where an emphasis on the theory of Forms formerly prevailed. It must be appreciated that Aristotle was the son of a physician, and that his inculcation of the thought of other Greek philosophers addressing health and the natural elements led to an extremely broad set of biologically- and medically-related writings. As this article proposes, Aristotle deepened the fourfold theory of the elements (...) with anatomic and physiologic observations. In books like History of Animals, Parts of Animals, and the lost Anatomai, he actively dissected organisms and recorded his findings. The corpus of medically-related literature Aristotle developed had a direct influence on subsequent Greek thinkers, including Galen, and on Medieval Islamic and modern Western practitioners such as William Harvey. Aristotle's ideas continue to influence modern medical thinkers in Europe and America through both his interpretation by European philosophers gaining the attention of medical humanists, and his writings' enduring impact on medical researchers balancing scientific with more personalistic approaches to medicine. (shrink)