Search

Breeding programs around the world continually collect data on large numbers of individuals. To be able to combine data collected across regions, years, and experiments, research communities develop standard operating procedures for data collection and measurement. One such method is a crop ontology, or a standardized vocabulary for collecting data on commonly measured traits. The ontology is also computer readable to facilitate the use of data management systems such as databases. Blueberry breeders and researchers across the United States have come together to develop the first standardized crop ontology in blueberry (Vaccinium spp.). We provide an overview and report on the construction of the first blueberry crop ontology and the 178 traits and methods included within. Researchers of Vaccinium species—such as other blueberry species, cranberry, lingonberry, and bilberry— can use the described crop ontology to collect phenotypic data of greater quality and consistency, interoperability, and computer readability. Crop ontologies, as a shared data language, benefit the entire worldwide research community by enabling collaborative meta-analyses that can be used with genomic data for quantitative trait loci, genome-wide association studies, and genomic selection analysis. [ABSTRACT FROM AUTHOR]

Yeasts in the subphylum Saccharomycotina are found across the globe in disparate ecosystems. A major aim of yeast research is to understand the diversity and evolution of ecological traits, such as carbon metabolic breadth, insect association, and cactophily. This includes studying aspects of ecological traits like genetic architecture or association with other phenotypic traits. Genomic resources in the Saccharomycotina have grown rapidly. Ecological data, however, are still limited for many species, especially those only known from species descriptions where usually only a limited number of strains are studied. Moreover, ecological information is recorded in natural language format limiting high throughput computational analysis. To address these limitations, we developed an ontological framework for the analysis of yeast ecology. A total of 1,088 yeast strains were added to the Ontology of Yeast Environments (OYE) and analyzed in a machine‐learning framework to connect genotype to ecology. This framework is flexible and can be extended to additional isolates, species, or environmental sequencing data. Widespread adoption of OYE would greatly aid the study of macroecology in the Saccharomycotina subphylum. Summary: Ontological frameworks allow high throughput analysis of ecological data.We established a formal Ontology of Yeast Environments.The Ontology of Yeast Environments describes isolation environments for 1088 strains.Coupled with genomic data, analysis of the ontology reveals gene‐environment associations. [ABSTRACT FROM AUTHOR]

Introduction: Recent regulations from United States Government agencies reshape the screening of synthetic nucleic acids. These take a step away from categorizing hazard on the basis of "bad" taxa and invoke the function of the sequence in pathogenesis or intoxication. Ascertaining functions related to pathogenesis and distinguishing these from other molecular abilities that are unproblematic is not simple. Some have suggested that this information can be readily obtained from existing databases of pathogens. Objectives: We evaluate how virulence factors are described in current databases of pathogens and their adequacy for biothreat data science. We discuss limitations of how virulence factors have been conceived and propose using the sequence of concern (SoC) term to distinguish sequences with biothreat from those without. We discuss ways in which databases of SoCs might be implemented for research and regulatory purposes. We describe ongoing work improving functional descriptions of SoCs. Methods: We assess the adequacy of descriptions of virulence factors in pathogen databases following extensive engagement with the literature in microbial pathogenesis. Results/Conclusions: Descriptions of virulence factors in pathogen databases are inadequate for understanding biothreats. Many are not biothreats and would not be concerning if transferred to another pathogen. New gene ontology terms have been authored, and those specific to pathogenic viral processes are being generalized to make them relevant to other pathogenic taxa. This allows better understanding by humans and better recognition by machines. A database of annotated functions of SoCs could benefit the evolving biosecurity regulatory framework in the United States. [ABSTRACT FROM AUTHOR]

Introduction: Medical terminologies and code systems, which play a vital role in the health domain, are rarely static but undergo changes as knowledge and terminology evolves. This includes addition, deletion and relabeling of terms, and, if terms are organized hierarchically, changing their position. Tracking these changes may become important if one uses multiple versions of the same terminology and interoperability is desired. Method: We propose a new method for automatic change tracking between terminology versions. It consists of a declarative import pipeline, which translates source terminologies into a common data model. We then use semantic and lexical change detection algorithms. They produce an ontology-based representation of terminology changes, which can be queried using semantic query languages. Results: The method proves accurate in detecting additions, deletions, relocations and renaming of terms. In cases where inter-version term mapping information is provided by the publisher, we were able to highly enhance the ability to differentiate between simple additions/deletions and refinements/consolidation of terms. Conclusion: The method proves effective for semi-automatic change handling if term refinements and consolidation are relevant and for automatic change detection if additional mapping information is available. [ABSTRACT FROM AUTHOR]

Breeding programs around the world continually collect data on large numbers of individuals. To be able to combine data collected across regions, years, and experiments, research communities develop standard operating procedures for data collection and measurement. One such method is a crop ontology, or a standardized vocabulary for collecting data on commonly measured traits. The ontology is also computer readable to facilitate the use of data management systems such as databases. Blueberry breeders and researchers across the United States have come together to develop the first standardized crop ontology in blueberry (Vaccinium spp.). We provide an overview and report on the construction of the first blueberry crop ontology and the 178 traits and methods included within. Researchers of Vaccinium species—such as other blueberry species, cranberry, lingonberry, and bilberry—can use the described crop ontology to collect phenotypic data of greater quality and consistency, interoperability, and computer readability. Crop ontologies, as a shared data language, benefit the entire worldwide research community by enabling collaborative meta-analyses that can be used with genomic data for quantitative trait loci, genome-wide association studies, and genomic selection analysis.

One Digital Health (ODH) merges the Digital Health and One Health approaches to create a comprehensive framework for future health ecosystems. In this rapidly evolving field, a standardized vocabulary is not just a convenience, but a necessity to ensure efficient communication. This research proposes the development of a "One Digital Health-Unified Terminology" (ODH-UT) to facilitate communication among researchers and practitioners in Digital Health and One Health, addressing this crucial need. [ABSTRACT FROM AUTHOR]

The dynamic relationship among survey instruments and study entities like questionnaires, variables, questions, and response formats evolve in Social Sciences surveys. Researchers may need to modify variable attributes such as labels or names, question-wording, or response scales when reusing variables in survey design. Therefore, explaining these relations across different waves and studies is necessary to track how variables relate to each other. Although standards like Data Documentation Initiative -- Lifecycle (DDI-LC) and DataCite model these relationships, these frameworks fall short of capturing the complexity of variable relationships. The DDI Alliance Controlled Vocabulary for Commonality Type employs codes--such as 'identical,' 'some,' and 'none'--to outline shifts in entities like variables; however, this approach is insufficient for disambiguating these relationships since they do not differentiate the variable attributes subject to change. We introduce the GESIS Controlled Vocabulary (CV) for Variables in Social Sciences Research Data to bridge this gap. This CV is designed to enhance semantic interoperability across various organizations and systems. Establishing explicit relationships facilitates harmonization across different study waves and enriches data reuse. This enhancement supports advanced search and browse functionalities. The CV, published via the CESSDA vocabulary manager, seeks to forge a semantically rich, interconnected knowledge graph specifically tailored for Social Science Research. This endeavour aligns with the FAIR data principles, aiming to foster a more integrated and accessible research landscape. [ABSTRACT FROM AUTHOR]

The aim of the current research is to identify and draw the existing relationships between the concepts in the field of children and young adults and the design of the ontology using knowledge representation tools. In this research, the conceptual design of the ontology was done using the Methontology method, and based on the steps of this methodology its taxonomy structure was adapted from Dewey’s Decimal Classification, and to extract the dictionary of words the entries of the ASKA thesaurus (Thesaurus of Kanoon-e Parvaresh-e Fekri Koodakan va Nojavanan) and children’s subject headings have been used. ISO 25964 standard was used in order to re-engineer the thesaurus and subject headings and turn them into the ontology. All thesaurus concepts and subject headings were considered as ontology classes and thesaurus terms as class labels. Definitions, domain notes, and other notes and information became descriptions. Hierarchical relations were considered as general hierarchical relations in ontology and were represented by subclass principle. Dependent relationships that indicate non-hierarchical relationships were defined by the researcher as semantic relationships between two concepts of ontology. The tool used for formalization, extracting the conceptual structure and coding and creating the ontology is Protégé software version 5.5.0. During the process of creating this ontology, the software outputs were evaluated by experts in the field. After identifying the basic concepts and the relationships between them, a conceptual structure was presented based on the findings of the previous two stages with an ontological approach. The results show that the ontology of children and young adults in thirteen main classes is formed and four types of Annotation Properties are used in it. This ontology includes 44 types of Object Properties and 20 types of data Properties and 305 examples. The formal and content validity of the conceptual structure of this ontology was confirmed by experts in the field of children and adolescents using the Delphi technique. In the ontology evaluation stage, in order to reject or confirm the authenticity of the work and the validity of the ontology, Felice’s Kappa coefficient was used, and because in the five components of the research, Felice’s kappa coefficient was almost a number close to 1, this indicates a greater agreement between the evaluators and shows that the ontology has good reliability. According to the findings of the research, it can be stated that children’s thesaurus and subject headings are suitable tools for collecting ontological concepts and terms. Also, the ontology of children and young adults can be one of the useful and efficient tools of knowledge representation in this field. This essential tool can be a basis for the expansion and development of future terms and concepts of this field, and by using this ontology in knowledge-based systems, it is possible to improve retrieval systems, automatic reasoning processes, designing intelligent systems and knowledge engineering in the field of children and young adults. [ABSTRACT FROM AUTHOR]

This study investigated coded data retrieved from clinical dashboards, which are decision-support tools that include a graphical display of clinical progress and clinical activities. Data were extracted from clinical dashboards representing 256 youth (M age = 11.9) from 128 practitioners who were trained in the Managing and Adapting Practice (MAP) system (Chorpita & Daleiden in BF Chorpita EL Daleiden 2014 Structuring the collaboration of science and service in pursuit of a shared vision. 43(2):323 338. 2014, Chorpita & Daleiden in BF Chorpita EL Daleiden 2018 Coordinated strategic action: Aspiring to wisdom in mental health service systems. 25(4):e12264. 2018) in 55 agencies across 5 regional mental health systems. Practitioners labeled up to 35 fields (i.e., descriptions of clinical activities), with the options of drawing from a controlled vocabulary or writing in a client-specific activity. Practitioners then noted when certain activities occurred during the episode of care. Fields from the extracted data were coded and reliability was assessed for Field Type, Practice Element Type, Target Area, and Audience (e.g., Caregiver Psychoeducation: Anxiety would be coded as Field Type = Practice Element; Practice Element Type = Psychoeducation; Target Area = Anxiety; Audience = Caregiver). Coders demonstrated moderate to almost perfect interrater reliability. On average, practitioners recorded two activities per session, and clients had 10 unique activities across all their sessions. Results from multilevel models showed that clinical activity characteristics and sessions accounted for the most variance in the occurrence, recurrence, and co-occurrence of clinical activities, with relatively less variance accounted for by practitioners, clients, and regional systems. Findings are consistent with patterns of practice reported in other studies and suggest that clinical dashboards may be a useful source of clinical information. More generally, the use of a controlled vocabulary for clinical activities appears to increase the retrievability and actionability of healthcare information and thus sets the stage for advancing the utility of clinical documentation. [ABSTRACT FROM AUTHOR]

Importance The Observational Health Data Sciences and Informatics (OHDSI) is the largest distributed data network in the world encompassing more than 331 data sources with 2.1 billion patient records across 34 countries. It enables large-scale observational research through standardizing the data into a common data model (CDM) (Observational Medical Outcomes Partnership [OMOP] CDM) and requires a comprehensive, efficient, and reliable ontology system to support data harmonization. Materials and methods We created the OHDSI Standardized Vocabularies—a common reference ontology mandatory to all data sites in the network. It comprises imported and de novo -generated ontologies containing concepts and relationships between them, and the praxis of converting the source data to the OMOP CDM based on these. It enables harmonization through assigned domains according to clinical categories, comprehensive coverage of entities within each domain, support for commonly used international coding schemes, and standardization of semantically equivalent concepts. Results The OHDSI Standardized Vocabularies comprise over 10 million concepts from 136 vocabularies. They are used by hundreds of groups and several large data networks. More than 8600 users have performed 50 000 downloads of the system. This open-source resource has proven to address an impediment of large-scale observational research—the dependence on the context of source data representation. With that, it has enabled efficient phenotyping, covariate construction, patient-level prediction, population-level estimation, and standard reporting. Discussion and conclusion OHDSI has made available a comprehensive, open vocabulary system that is unmatched in its ability to support global observational research. We encourage researchers to exploit it and contribute their use cases to this dynamic resource. [ABSTRACT FROM AUTHOR]

The controlled vocabularies of five major health-related databases are explored in order to present a partial listing of standardized subject headings for various concepts relating to groups of marginalized persons. Having easy access to these terms could make searching for health information about marginalized persons more efficient for the health information specialist. Persons doing such research can sometimes perceive official vocabulary as being demeaning, outdated, demoralizing, or misleading. Some examples of searching for information concerning marginalized person are shown as well as an Appendix of controlled vocabulary terms specific to the five biomedical databases studied. [ABSTRACT FROM AUTHOR]

Standardised medical terminologies are used to ensure accurate and consistent communication of information and to facilitate data exchange. Currently, many terminologies are only available in English, which hinders international research and automated processing of medical data. Natural language processing (NLP) and Machine Translation (MT) methods can be used to automatically translate these terms. This scoping review examines the research on automated translation of standardised medical terminology. A search was performed in PubMed and Web of Science and results were screened for eligibility by title and abstract as well as full text screening. In addition to bibliographic data, the following data items were considered: 'terminology considered', 'terms considered', 'source language', 'target language', 'translation type', 'NLP technique', 'NLP system', 'machine translation system', 'data source' and 'translation quality'. The results showed that the most frequently translated terminology is SNOMED CT (39.1%), followed by MeSH (13%), ICD (13%) and UMLS (8.7%). The most common source language is English (55.9%), and the most common target language is German (41.2%). Translation methods are often based on Statistical Machine Translation (SMT) (41.7%) and, more recently, Neural Machine Translation (NMT) (30.6%), but can also be combined with various MT methods. Commercial translators such as Google Translate (36.4%) and automatic validation methods such as BLEU (22.2%) are frequently used tools for translation and subsequent validation. ● Need for machine translation in healthcare. ● Role of NLP in medical terminology translation. ● Evaluation of machine translation approaches. [ABSTRACT FROM AUTHOR]

Integration of data on coin finds into the ARIADNE portal presents a number of challenges, partly related to the use of the Getty AAT as a controlled vocabulary, in particular its incomplete coverage and hierarchical structure. Further problems arise from the fact that the majority of the data are being provided not from primarily numismatic projects and institutions, but rather from disparate archaeological resources that integrate a wide range of artefacts and records. As a result, they often focus less on the peculiarities of using the AAT for coin finds and the difficulties that arise from its use. This article illustrates how this can lead to quite disparate and inconsistent mappings of data to the ARIADNE portal. Potential solutions such as aligning the AAT to the established vocabulary of Nomisma.org, or even implementing the latter in the portal, as well as implementing a standard mapping for coin finds, are discussed. Also addressed are the possibilities for complex, granular searches using the SPARQL endpoint in the ARIADNElab Virtual Research Area.

The Museum of Cultural History (MCH) at the University of Oslo, Norway, has undertaken a series of infrastructure projects with the aim of improving the standardisation of archaeological data and increasing data integration at both a national and international level. This builds on decades of earlier work and includes a revision of shared National database systems (unimus), integration of previously disparate data types and spatial data (ADED), and more recently the development of a 3D publishing platform (BItFROST). These projects feed into broader aims of large-scale data integration as part of the European-wide ARIADNE Research Infrastructure. This article provides an overview of the history and development of these systems in Norway and takes a look at some of the roads still ahead.

Medical ontologies are mostly available in English. This presents a language barrier that is a limitation in research and automated processing of patient data. The manual translation of ontologies is complex and time-consuming. However, there are commercial translation tools that have shown promising results in the field of medical terminology translation. The aim of this study is to translate selected terms of the Human Phenotype Ontology (HPO) from English into German using commercial translators. Six medical experts evaluated the translation candidates in an iterative process. The results show commercial translators, with DeepL in the lead, provide translations that are positively evaluated by experts. With a broader study scope and additional optimization techniques, commercial translators could support and facilitate the process of translating medical ontologies. [ABSTRACT FROM AUTHOR]

Objective Identifying consumer health informatics (CHI) literature is challenging. To recommend strategies to improve discoverability, we aimed to characterize controlled vocabulary and author terminology applied to a subset of CHI literature on wearable technologies. Materials and Methods To retrieve articles from PubMed that addressed patient/consumer engagement with wearables, we developed a search strategy of textwords and Medical Subject Headings (MeSH). To refine our methodology, we used a random sample of 200 articles from 2016 to 2018. A descriptive analysis of articles (N  = 2522) from 2019 identified 308 (12.2%) CHI-related articles, for which we characterized their assigned terminology. We visualized the 100 most frequent terms assigned to the articles from MeSH, author keywords, CINAHL, and Engineering Databases (Compendex and Inspec together). We assessed the overlap of CHI terms among sources and evaluated terms related to consumer engagement. Results The 308 articles were published in 181 journals, more in health journals (82%) than informatics (11%). Only 44% were indexed with the MeSH term "wearable electronic devices." Author keywords were common (91%) but rarely represented consumer engagement with device data, eg, self-monitoring (n  = 12, 0.7%) or self-management (n  = 9, 0.5%). Only 10 articles (3%) had terminology from all sources (authors, PubMed, CINAHL, Compendex, and Inspec). Discussion Our main finding was that consumer engagement was not well represented in health and engineering database thesauri. Conclusions Authors of CHI studies should indicate consumer/patient engagement and the specific technology investigated in titles, abstracts, and author keywords to facilitate discovery by readers and expand vocabularies and indexing. [ABSTRACT FROM AUTHOR]

This research seeks to contribute to efforts to standardize metadata across the costume and fashion domain by adding new metadata elements and controlled vocabularies to Costume Core. Expanding the metadata schema could increase the searchability and discoverability of fashion collections. To expand Costume Core, we used vocabulary from pre-trained Natural Language Processing (NLP) models to identify potential new descriptors from a conceptual latent space provided by a technique known as word embeddings. We also pulled from controlled vocabularies shared by fashion collection personnel from across the United States via online surveys. [ABSTRACT FROM AUTHOR]

Core datasets are the composition of essential data items for a certain research scope. As they state commonalities between heterogeneous data collections, they serve as a basis for cross-site and cross-disease research. Therefore, researchers at the national and international levels have addressed the problem of missing core datasets. The German Center for Lung Research (DZL) comprises five sites and eight disease areas and aims to gain further scientific knowledge by continuously promoting collaborations. In this study, we elaborated a methodology for defining core datasets in the field of lung health science. Additionally, through support of domain experts, we have utilized our method and compiled core datasets for each DZL disease area and a general core dataset for lung research. All included data items were annotated with metadata and where possible they were assigned references to international classification systems. Our findings will support future scientific collaborations and meaningful data collections. [ABSTRACT FROM AUTHOR]

This project addresses the information actions in the information regime of the Laboratory of Intellectual Technologies Project - LTi from the perspective of information retrieval. Our purpose is to contribute to academic training in undergraduate and graduate courses at the Federal University of Paraíba. It is in this social and cultural space that the subjects who share a way of life act - the academic way of life within the Information Science community - and where domains, strata and modalities of information actions are intertwined, from their formative and relational, coordination, innovation, creation and application of theoretical models, emphasizing its mediation characteristic through the availability of virtual information artifacts and services. LTi's main product is the LTi Virtual Portal. Created concurrently with the project, the LTi Portal had its architecture and graphic design modified in 2019. In this process, the retrieval of information from the original Portal files (Memory) was not fully transferred to the Current Portal, so that the user can come having difficulty finding information that is available on the Memory Portal. It is necessary to retrieve the contents of the LTi Memória Portal, verifying if they are available in the new Portal, and create search and information retrieval consultation mechanisms, based on information actions, facilitating access to the contents for users. Therefore, the present project proposes to rescue the original functionality of the organization of the files and, also, to organize them, according to the information actions, as semantic trails for retrieving the information available in the files of the LTi Portal. This research intends to present a proposal for a controlled word for Portal LTi, approaching Portal LTi from the perspective of organizing its content, with a view to better retrieving the information contained in the files made available on its pages. [ABSTRACT FROM AUTHOR]

Established over three decades ago, the controlled vocabulary of Medical Subject Headings (MeSH) has great potential to be a documental source to enlighten how Health Sciences incorporate overtime the relevant themes for their knowledge and practices. This paper aims to categorize and discuss some notions on the term environment that are present in this controlled vocabulary, using as its thread the environmental crisis discussed in the Geography area. This is a qualitative, exploratory, documental research. Data was gathered from the MeSH website, in the sections of free search and previous editions from 1999 to 2020. As a result, we created four categories on environment notions: ecological, scalar, work and architectonic. The results associated to the discussions on the environmental crisis in Geography indicated that there are conceptual gaps in the controlled vocabulary of MeSH regarding health and environment. We point out the need to extrapolate the ecological equilibrium/environmental imbalance and environmental management/environment design approaches, also taking into consideration the territorial approach. [ABSTRACT FROM AUTHOR]

Information has become the most powerful tools which keeps us updated and is necessary for modern existence. To cope up with the need of the information seekers, the process of searching, creation and location as well as dissemination of information is also evolving. On one hand flexible searching is preferred by the users and on the other hand controlled vocabulary is universally accepted standard. Tags constitute the core of the text with those terms which are usually not obtainable from controlled vocabulary. This study examines the similarities and dissimilarities between Library Thing tags and OCLC FAST subject heading list. For collecting the data, some of the popular literatures of William Shakespeare were selected. The analysis shows the numbers of tags in Library Things are more in comparison to the OCLC Fast subject headings and 92 percent of the tags were found relevant. The study also shows that 'William Shakespeare' is the focal point for all the data gathered, but on the other hand 'Shakespeare' is not a preferred term in OCLC FAST subject heading. [ABSTRACT FROM AUTHOR]

Industry-specific translation is one of the rapidly developing and highly demanded sectors in Kazakhstan. This paper discusses the theoretical and methodological issues of compiling a controlled multilingual vocabulary or thesaurus for the purposes of industry-specific translation. The proposed multilingual thesaurus addresses the gap of existing online dictionaries with the lack of ability to translate directly from English into Kazakh, and provides relevant equivalents for mining and metal terms in three languages: Kazakh, English, and Russian. The study is interdisciplinary and combines methods of linguistic analysis, machine learning, ontological and corpus-based studies that allow an exhaustive analysis, generalization, comparison, systematization, classification, and formalization of the mining industry terminology through a multilingual parallel corpus based on the Zthez international technical platform. The controlled multilingual thesaurus is designed to promote intercultural communication of professionals and translators in the mining industry. Besides it enables the foundation to be built for a Kazakh language corpus, unifying and systematizing Kazakh industry-specific terms in a multilingual way.

The longstanding absence of common terminology across the Architecture, Engineering, and Construction (AEC) industry results in communication barriers and hinders smooth collaboration among professionals across these disciplines. To address this challenge, the potential of a crowdsourced methodology was investigated in this paper to assist in improving terminological consensus using an online platform: Yet Another Metadata Zoo (YAMZ). Participants from the academic form-finding community were engaged to interact using YAMZ. Definitions, comments, and votes were collected and analyzed to understand their quantitative and qualitative relationships. The results indicate that a crowdsourcing methodology can be employed in research groups to build terminological consensus and may enhance research through improved terminology production. Addressing each of these challenges could help reduce semantic ambiguity among stakeholders in AEC projects. It was concluded that a crowdsourced approach may offer a pathway for faster standards development, although a broader study involving stakeholders from the AEC field is necessary. • Crowdsourcing tool has promising applicability in the civil engineering community. • AEC industry's terminological overlaps show intersections requiring disambiguation. • Semantic disambiguation aids interoperability digital workflows and communication. • User statistics show high levels of positive and negative engagement. • Statistics regarding definitions point toward broader study. [ABSTRACT FROM AUTHOR]

Objective: A comprehensive understanding of professional and technical terms is essential to achieving practical results in multidisciplinary projects dealing with health informatics and digital health. The medical informatics multilingual ontology (MIMO) initiative has been created through international cooperation. MIMO is continuously updated and comprises over 3700 concepts in 37 languages on the Health Terminology/Ontology Portal (HeTOP). Methods: We conducted case studies to assess the feasibility and impact of integrating MIMO into real-world healthcare projects. In HosmartAI, MIMO is used to index technological tools in a dedicated marketplace and improve partners' communication. Then, in SaNuRN, MIMO supports the development of a "Catalog and Index of Digital Health Teaching Resources" (CIDHR) backing digital health resources retrieval for health and allied health students. Results: In HosmartAI, MIMO facilitates the indexation of technological tools and smooths partners' interactions. In SaNuRN within CIDHR, MIMO ensures that students and practitioners access up-to-date, multilingual, and high-quality resources to enhance their learning endeavors. Conclusion: Integrating MIMO into training in smart hospital projects allows healthcare students and experts worldwide with different mother tongues and knowledge to tackle challenges facing the health informatics and digital health landscape to find innovative solutions improving initial and continuous education., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

This poster presents the use of Interpretive Description in ontology development. The methods selected attended to the need for quality and rigour. [ABSTRACT FROM AUTHOR]

Research data management (RDM) includes people with different needs, specific scientific contexts, and diverse requirements. The description is a big challenge in the domain of RDM. Metadata plays an essential role, allowing the inclusion of essential information for the interpretation of data, enhances the reuse of data and its preservation. The establishment of metadata models can facilitate the process of description and contribute to an improvement in the quality of metadata. When we talk about image data, the task is even more difficult, as there are no explicit recommendations to guide image management. In this work, we present a proposal for a metadata model for image description. To validate the model, we followed an experiment of data description, where eleven participants described images from their research projects, using a metadata model proposed. The experiment shows that participants do not have formal practices for describing their imagery data. Yet, they provided valuable contributions and recommendations to the final definition of a metadata model for image description, to date nonexistent. We also developed controlled vocabularies for some descriptors. These vocabularies aim to improve the image description process, facilitate metadata model interpretation, and reduce the time and effort devoted to data description. [ABSTRACT FROM AUTHOR]

The need for assembled existing and new toxicity data has accelerated as the amount of chemicals introduced into commerce continues to grow and regulatory mandates require safety assessments for a greater number of chemicals. To address this evolving need, the ECOTOXicology Knowledgebase (ECOTOX) was developed starting in the 1980s and is currently the world's largest compilation of curated ecotoxicity data, providing support for assessments of chemical safety and ecological research through systematic and transparent literature review procedures. The recently released version of ECOTOX (Ver 5, www.epa.gov/ecotox) provides single‐chemical ecotoxicity data for over 12,000 chemicals and ecological species with over one million test results from over 50,000 references. Presented is an overview of ECOTOX, detailing the literature review and data curation processes within the context of current systematic review practices and discussing how recent updates improve the accessibility and reusability of data to support the assessment, management, and research of environmental chemicals. Relevant and acceptable toxicity results are identified from studies in the scientific literature, with pertinent methodological details and results extracted following well‐established controlled vocabularies and newly extracted toxicity data added quarterly to the public website. Release of ECOTOX, Ver 5, included an entirely redesigned user interface with enhanced data queries and retrieval options, visualizations to aid in data exploration, customizable outputs for export and use in external applications, and interoperability with chemical and toxicity databases and tools. This is a reliable source of curated ecological toxicity data for chemical assessments and research and continues to evolve with accessible and transparent state‐of‐the‐art practices in literature data curation and increased interoperability to other relevant resources. Environ Toxicol Chem 2022;41:1520–1539. © 2022 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA. [ABSTRACT FROM AUTHOR]

The Library of Congress Medium of Performance Thesaurus (LCMPT) and the music portions of the Library of Congress Genre/Form Terms for Library and Archival Materials (LCGFT) are long-anticipated products in a history of problem-solving approaches toward faceted access to music resources. MLA’s Cataloging and Metadata Committee has collaborated with the Library of Congress for the past several years in a multiphase endeavor to design and build out these new vocabularies. Implementation within the Anglo-American music cataloging community began in 2014, and retrospective implementation (the programmatic assignment of faceted terms to legacy metadata) is currently being studied and pursued.

Medical librarians collaborate with physicians and other healthcare professionals to improve the quality and accessibility of medical information, which includes assembling the best evidence to advance health equality through teaching and research. This column brings together brief cases highlighting the experiences and perspectives of medical librarians, educators, and healthcare professionals using their organizational, pedagogical, and information-analysis skills to advance health equality indexing. [ABSTRACT FROM AUTHOR]

The article looks back on the online workshop “Gender-sensitive indexing”, in which different perspectives of gender equality in content indexing were discussed in May 2022: on the basis of fundamental linguistic and librarianship issues, the Integrated Authority File (GND) and its rules for design and application were examined from a gender-specific perspective, as were feminist vocabularies and gender aspects in librarian training and further education. The event was intended as a kick-off; the report includes a call for further joint activities. [ABSTRACT FROM AUTHOR]

This article discusses the practical issues of compiling controlled multilingual thesauri for the purposes of industry-specific translation (IST). In the multilingual, transnational and globally connected Kazakhstan, IST is a much-needed translation service. IST is an interdisciplinary field between terminology, computational linguistics, translation theory and practice. Most of the professional guides, dictionaries and glossaries are systemized in alphabetical order and contain multiple variants for the terms searched. Therefore, there is an urgent need to create a systemized controlled multilingual thesaurus of industry-specific Kazakh, English and Russian terms in order to provide multilingual users with an interoperable and relevant term base. Controlled multilingual thesauri for industry-specific terms are the most effective tools for describing individual subject areas. They are designed to promote communication and interaction among professionals, translators and all Automated Information System users of specific fields irrespective of their location and health conditions. Unlike traditional dictionaries, controlled thesauri allow users to identify the meaning with the help of definitions and translations, relations of terms with other concepts, and broader and narrower terms. The purpose of this research is to unify and systematize industry-specific terms in Kazakh, to provide Russian and English equivalents, and to classify the terms into essential rubrics and subjects. Based on the Zthes data scheme to create a controlled multilingual thesaurus of industryspecific terms, the major rubrics have been formulated, and about 10,000 Kazakh mining and metal terms approved by the Terminological Committee of Kazakhstan have been structured.

Objectives We incorporated the Korean Electronic Data Interchange (EDI) vocabulary into Observational Medical Outcomes Partnership (OMOP) vocabulary using a semi-automated process. The goal of this study was to improve the Korean EDI as a standard medical ontology in Korea. Methods We incorporated the EDI vocabulary into OMOP vocabulary through four main steps. First, we improved the current classification of EDI domains and separated medical services into procedures and measurements. Second, each EDI concept was assigned a unique identifier and validity dates. Third, we built a vertical hierarchy between EDI concepts, fully describing child concepts through relationships and attributes and linking them to parent terms. Finally, we added an English definition for each EDI concept. We translated the Korean definitions of EDI concepts using Google.Cloud.Translation.V3, using a client library and manual translation. We evaluated the EDI using 11 auditing criteria for controlled vocabularies. Results We incorporated 313,431 concepts from the EDI to the OMOP Standardized Vocabularies. For 10 of the 11 auditing criteria, EDI showed a better quality index within the OMOP vocabulary than in the original EDI vocabulary. Conclusions The incorporation of the EDI vocabulary into the OMOP Standardized Vocabularies allows better standardization to facilitate network research. Our research provides a promising model for mapping Korean medical information into a global standard terminology system, although a comprehensive mapping of official vocabulary remains to be done in the future.

Clinical coding is the process of converting health information, which may be a combination of free text language and a clinician's interpretation of this, into a computer-readable formal language. Well-known examples of clinical coding systems include the International Classification of Diseases (ICD-10) and Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). These coding systems exist to avoid the complexities and ambiguity of human language and convey benefit to both individual clinicians and patients, but also by allowing for data analysis at the scale of entire populations. Advantages to proper clinical coding for individual hospitals or practices include audit, research, creation of decision support systems, accurate communication between teams, and to ensure hospitals receive appropriate re-numeration for their services. At the national level such coding allows for epidemiological study and the strategic allocation of health resources, whilst at the international level clinical coding allows for statistical reporting, monitoring of health inequality, and unambiguous communication between countries in a common language. [ABSTRACT FROM AUTHOR]

This article outlines the creation of computer game platform and media format Linked Open Data (LOD) controlled vocabularies by the Game Metadata and Citation Project (GAMECIP). We discuss the need for more consistent and accurate information in computer game library records, define what we mean by “platform” and “media format,” and then elaborate on our research process and issues encountered along the way. Our vocabularies were constructed with the Simple Knowledge Organization System to take advantage of its properties and hierarchical structure. After describing our LOD schema in detail, we conclude with a discussion of future work and a call for more collaboration.

Introduction: In the context of the Semantic Web, interoperability among heterogeneous ontologies is a challenge due to several factors, among which semantic ambiguity and redundancy stand out. To overcome these challenges, systems and algorithms are adopted to align different ontologies. In this study, it is understood that controlled vocabularies are a particular form of ontology. Objective: to obtain a vocabulary resulting from the alignment and fusion of the Vocabularies Scientific Domains and Scientific Areas of the Foundation for Science and Technology, - FCT, European Science Vocabulary - EuroSciVoc and United Nations Educational, Scientific and Cultural Organization - UNESCO nomenclature for fields of Science and Technology, in the Computing Sciences domain, to be used in the IViSSEM project. Methodology: literature review on systems/algorithms for ontology alignment, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - PRISMA methodology; alignment of the three vocabularies; and validation of the resulting vocabulary by means of a Delphi study. Results: we proceeded to analyze the 25 ontology alignment systems and variants that participated in at least one track of the Ontology Alignment Evaluation Initiative competition between 2018 and 2019. From these systems, Agreement Maker Light and Log Map were selected to perform the alignment of the three vocabularies, making a cut to the area of Computer Science. Conclusion: The vocabulary was obtained from Agreement Maker Light for having presented a better performance. At the end, a vocabulary with 98 terms was obtained in the Computer Science domain to be adopted by the IViSSEM project. The alignment resulted from the vocabularies used by FCT (Portugal), with the one adopted by the European Union (EuroSciVoc) and another one from the domain of Science & Technology (UNESCO). This result is beneficial to other universities and projects, as well as to FCT itself. [ABSTRACT FROM AUTHOR]

Feminist thesauri are networks of terms and concepts of women’s* and gender studies that close the gaps left by conventional authority files in the subject indexing of relevant literature. With thesaurA, the first Austrian women’s thesaurus was published in the mid-1990s. It was developed cooperatively, and since then has been used as local advancements, such as the so-called SAR-Index of Ariadne, the women* and gender documentation center of the Austrian National Library (ANL). A transition of the integrated library system at the ANL makes it necessary to migrate the vocabulary. The article sheds light on this vocabulary migration project in the con- text of feminist indexing and traces ideas on cooperative thesaurus projects regardless of the subject orientation. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ibero-Americana de Ciência da Informação is the property of Revista Ibero-Americana de Ciencia da Informacao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Texto & Contexto Enfermagem is the property of Universidade Federal de Santa Catarina, Programa de Pos-Graduacao de Enfermagem and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)