Search

Digital heritage portal interfaces are generally similar to digital library and search engine interfaces in displaying search results as a list of brief metadata records. The knowledge organization and search result display of these systems are item-centric, with little support for identifying relationships between items. This paper proposes a knowledge graph system and visualization interface as a promising solution for digital heritage systems to support users in browsing related items, understanding the relationships between items, and synthesizing a narrative on an issue. The paper discusses design issues for the knowledge graph, graph database, and graph visualization, and offers recommendations based on the authors' experience in developing three knowledge graph systems for archive and digital humanities resources: the Zubir Said personal archive collection at the Nanyang Academy of Fine Arts, Singapore; Singapore Pioneers social network; and Polyglot Medicine knowledge graph of Asian traditional and herbal medicine. Lessons learned from a small user study are incorporated in the discussion. [ABSTRACT FROM AUTHOR]

To study library guides, as published on Springshare's LibGuides platform, new approaches are needed to expand the scope of the research, ensure comprehensiveness of data collection, and reduce bias for content analysis. Computational methods can be utilized to conduct a nuanced and thorough evaluation that critically assesses the resources promoted in library guides. Web-based library guides are curated by librarians to provide easy access to high-quality information and resources in a variety of formats to support the research needs of their users. Recent scholarship considers library guides as valuable resources and as de facto publications, highlighting the need for critical study. In this article, the authors present a novel model for comprehensively gathering data about a specific genre of books from individual LibGuide pages and applying computational methods to explore the resultant data. Beginning with a pre-selected list of 159 books, we programmatically queried the titles using the LibGuides Community search engine. After cleaning and filtering the resultant data, we compiled a list of 20,484 book references (of which 6,212 are unique) on 1,529 LibGuide pages. By testing against inclusion and exclusion criteria to ensure relevancy, we identified a total of 281 titles relevant to our topic. To gain insights for future study, citation analysis metrics are presented to reveal patterns of frequency, co-occurrence, and bibliographic coupling of books promoted in LibGuides. This proof-of-concept could be adopted for a variety of applications, including assessment of collections, public services, critical librarianship, and other complex questions to enable a richer and more thorough understanding of the information landscape of LibGuides. [ABSTRACT FROM AUTHOR]

This study discusses the importance of the DSpace open-source software that supports numerous digital libraries and repositories around the world. With the release of DSpace version 7, a natural question that arises is whether the new version offers enough new functionalities to motivate system administrators to upgrade. This paper briefly describes the most important changes, including new features and bug fixes, included in DSpace 7.4 and prior minor versions. The next parts of this paper explore our estimate that there are several thousand DSpace-based systems globally that will likely have to be upgraded in the near future. The main reason for this need is that older versions of DSpace (including 5.x) have reached the end of their developer support period or are reaching it in mid-2023. Based on our own upgrade experience, we propose suggestions and recommendations on migrating from the previous DSpace 6.3-based environment to the new one in a case study that concludes this article. [ABSTRACT FROM AUTHOR]

Many institutions face low deposit rates with their institutional repositories despite investing substantial resources in implementing and supporting these systems. Deposit rates are higher in IRs that offer mediated deposits; however, this can be a time and labor intensive process. This article describes a method for copying open access articles and corresponding descriptive metadata from open repositories for archiving in an institutional repository using Beautiful Soup and Selenium as web scraping tools. This method quickly added hundreds of articles to an IR without relying on faculty participation or consulting publisher policies, increasing repository downloads and usage. [ABSTRACT FROM AUTHOR]

The ownership of MARC bibliographic data has been an issue between OCLC and other companies in the marketplace. Two lawsuits are discussed between OCLC and Clarivate and SkyRiver. The "WorldCat Rights and Responsibilities for the OCLC Cooperative" provides a basis for many library contracts and how OCLC lays claim to bibliographic data. The "ICOLC Statement on the Metadata Rights of Libraries" is used as a general framework for discussing issues surrounding who owns MARC records and how they can be used or re-used. Most librarians are interested in free and open use of MARC records whether or not they may have passed through the OCLC system at some point. [ABSTRACT FROM AUTHOR]

Molecular methods are currently some of the best-suited technologies for implementation in insect monitoring. However, the field is developing rapidly and lacks agreement on methodology or community standards. To apply DNA-based methods in large-scale monitoring, and to gain insight across commensurate data, we need easy-to-implement standards that improve data comparability. Here, we provide three recommendations for how to improve and harmonize efforts in biodiversity assessment and monitoring via metabarcoding: (i) we should adopt the use of synthetic spike-ins, which will act as positive controls and internal standards; (ii) we should consider using several markers through a multiplex polymerase chain reaction (PCR) approach; and (iii) we should commit to the publication and transparency of all protocol-associated metadata in a standardized fashion. For (i), we provide a ready-to-use recipe for synthetic cytochrome c oxidase spike-ins, which enable between-sample comparisons. For (ii), we propose two gene regions for the implementation of multiplex PCR approaches, thereby achieving a more comprehensive community description. For (iii), we offer guidelines for transparent and unified reporting of field, wet-laboratory and dry-laboratory procedures, as a key to making comparisons between studies. Together, we feel that these three advances will result in joint quality and calibration standards rather than the current laboratory-specific proof of concepts. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'. [ABSTRACT FROM AUTHOR]

Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal insects—from sensor development and field deployment to workflows for data processing and publishing. Sensors comprise a light to attract insects, a camera for collecting images and a computer for scheduling, data storage and processing. Metadata is important to describe sampling schedules that balance the capture of relevant ecological information against power and data storage limitations. Large data volumes of images from automated systems necessitate scalable and effective data processing. We describe computer vision approaches for the detection, tracking and classification of insects, including models built from existing aggregations of labelled insect images. Data from automated camera systems necessitate approaches that account for inherent biases. We advocate models that explicitly correct for bias in species occurrence or abundance estimates resulting from the imperfect detection of species or individuals present during sampling occasions. We propose ten priorities towards a step-change in automated monitoring of nocturnal insects, a vital task in the face of rapid biodiversity loss from global threats. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'. [ABSTRACT FROM AUTHOR]

Undercounting is a critical issue in migration statistics, resulting in bias. This typically arises from insufficient reporting requirements and problems with enforcing such requirements. The main sources of information on undercounting are the metadata accompanying official statistics and expert opinions. However, metadata and arbitrary expert opinions may be limited by overlooking important details in migration data shared by various countries. This includes potential oversight of changes in methodologies, definitions, or retrospective updates to the data following censuses. This work presents a methodological solution with three objectives to address undercounting in international migration data. First, we provide an overview of available metadata and expert opinions on undercounting in European migration flows. Secondly, we propose a novel data-driven approach that incorporates year-specific and duration-of-stay-adjusted classifications. The proposed methodological solution relies on comparisons of flows in the same direction reported by a given country with high-quality data reported by another set of countries. We use bilateral migration data provided by Eurostat, United Nations, and selected national statistical institutes. Duration-of-stay correction coefficients are derived through an optimization model or borrowed from the literature. Metadata and expert opinion scores can also be integrated to classify undercounting. Finally, we provide a dynamic classification of undercounting for thirty-two European countries (2002–21), accessible through an online Shiny application, offering flexibility and adaptability. The findings highlight significant undercounting in new European Union Member States, particularly Bulgaria, Latvia, and Romania. Interestingly, other European countries, including those presumed to maintain reliable population statistics, also exhibit notable periods of undercounting. [ABSTRACT FROM AUTHOR]

Queer history and queer bibliography have taught us that names matter. This paper uses queer history and methodology to rethink nomenclature related to the early modern conception of the family printing dynasty and to show how heteronormative assumptions manifest in metadata and other forms of bibliographic description. It asserts that classification and the creation of metadata have never been neutral acts. Drawing on radical challenges to systems of knowledge organization made by librarians from the 1970s onwards, it suggests that such systems can and should restructure around new ideas of family that take into account queer lives, histories, and language. For the early modern period, this means acknowledging dynastic structures that were frequently nonnormative, deviating from the traditional business inheritance from father to son. To demonstrate the shortcomings of current metadata practices and the potential for reassessment, this paper utilizes three case studies related to the vague use of the terms "widow" and "heir" in seventeenth- and eighteenth-century French, Flemish, and Dutch imprints. It presents practical solutions in making metadata more accurate, including a new perspective on the print workshop as a space of collaboration, an expansion in roles expressed within a record, and increased emphasis on interoperability and open linked data. Rethinking systems of power—and acknowledging the labor that cataloging and metadata creation entail—allow for a queer bibliography that acknowledges the messiness of identity and legacy but is also precise and accurate. [ABSTRACT FROM AUTHOR]

This essay is occupied with attempts to provide alternative bibliographic infrastructures for marginalized communities and discusses the possibilities of queer metadata. First, I provide a definitional and literature review focused on the principles and purposes of the field of knowledge organization. Next, I introduce the Homosaurus as an example of a queer alternative to standard cataloging and classification structures. I draw from discussions on imagined records and impossible archival imaginaries in the archival studies field in order to propose the concepts of "metadatic imaginaries" and "impossible metadatic imaginaries." The essay closes with considerations about the implications for queer bibliography. [ABSTRACT FROM AUTHOR]

Background: In today's landscape of data management, the importance of knowledge graphs and ontologies is escalating as critical mechanisms aligned with the FAIR Guiding Principles—ensuring data and metadata are Findable, Accessible, Interoperable, and Reusable. We discuss three challenges that may hinder the effective exploitation of the full potential of FAIR knowledge graphs. Results: We introduce "semantic units" as a conceptual solution, although currently exemplified only in a limited prototype. Semantic units structure a knowledge graph into identifiable and semantically meaningful subgraphs by adding another layer of triples on top of the conventional data layer. Semantic units and their subgraphs are represented by their own resource that instantiates a corresponding semantic unit class. We distinguish statement and compound units as basic categories of semantic units. A statement unit is the smallest, independent proposition that is semantically meaningful for a human reader. Depending on the relation of its underlying proposition, it consists of one or more triples. Organizing a knowledge graph into statement units results in a partition of the graph, with each triple belonging to exactly one statement unit. A compound unit, on the other hand, is a semantically meaningful collection of statement and compound units that form larger subgraphs. Some semantic units organize the graph into different levels of representational granularity, others orthogonally into different types of granularity trees or different frames of reference, structuring and organizing the knowledge graph into partially overlapping, partially enclosed subgraphs, each of which can be referenced by its own resource. Conclusions: Semantic units, applicable in RDF/OWL and labeled property graphs, offer support for making statements about statements and facilitate graph-alignment, subgraph-matching, knowledge graph profiling, and for management of access restrictions to sensitive data. Additionally, we argue that organizing the graph into semantic units promotes the differentiation of ontological and discursive information, and that it also supports the differentiation of multiple frames of reference within the graph. [ABSTRACT FROM AUTHOR]

Background: The selection of data elements is a decisive task within the development of a health registry. Having the right metadata is crucial for answering the particular research questions. Furthermore, the set of data elements determines the registries' readiness of interoperability and data reusability to a major extent. Six health registries shared and published their metadata within a German funding initiative. As one step in the direction of a common set of data elements, a selection of those metadata was evaluated with regard to their appropriateness for a broader usage. Methods: Each registry was asked to contribute a 10%-selection of their data elements to an evaluation sample. The survey was set up with the online survey tool „LimeSurvey Cloud". The registries and an accompanying project participated in the survey with one vote for each project. The data elements were offered in content groups along with the question of whether the data element is appropriate for health registries on a broader scale. The question could be answered using a Likert scale with five options. Furthermore, "no answer" was allowed. The level of agreement was assessed using weighted Cohen's kappa and Kendall's coefficient of concordance. Results: The evaluation sample consisted of 269 data elements. With a grade of "perhaps recommendable" or higher in the mean, 169 data elements were selected. These data elements belong preferably to groups' demography, education/occupation, medication, and nutrition. Half of the registries lost significance compared with their percentage of data elements in the evaluation sample, one remained stable. The level of concordance was adequate. Conclusions: The survey revealed a set of 169 data elements recommended for health registries. When developing a registry, this set could be valuable help in selecting the metadata appropriate to answer the registry's research questions. However, due to the high specificity of research questions, data elements beyond this set will be needed to cover the whole range of interests of a register. A broader discussion and subsequent surveys are needed to establish a common set of data elements on an international scale. [ABSTRACT FROM AUTHOR]

At the second stage of China Spallation Neutron Source (CSNS-II), it is predicted that 2 PB raw experimental data will be produced annually from twenty instruments. Scientific computing puts forward higher requirements for data sharing, utilization, retrieval, analysis efficiency, and security. However, the existing data management system (DMS) based on ICAT has several limitations including poor scalability of metadata database, imperfect data-management lifecycle and inflexible API. To ensure the accuracy, usability, scalability and efficiency of CSNS-II experimental data, a new scientific data management system is therefore designed based on the DOMAS framework developed by the Computing Center of IHEP. The data acquisition, transmission, storage and service systems are re-designed and tailored specifically for CSNS-II. Upon its completion, the new DMS will overcome the existing challenges and offer functions such as online display, search functionality and rapid download capabilities for metadata, raw data and analyzed data; flexible and user-friendly authorization; and data lifecycle management. Ultimately, the implementation of the new Data Management System (DMS) is expected to enhance the efficiency of experimental data analysis, propelling CSNS-II to achieve international advanced standards. Furthermore, it aims to reinforce self-reliance and technological strength in the field of science and technology at a high level in China. The development and deployment of the new DMS begin at the end of 2023. [ABSTRACT FROM AUTHOR]

Edge computing provides higher computational power and lower transmission latency by offloading tasks to nearby edge nodes with available computational resources to meet the requirements of time-sensitive tasks and computationally complex tasks. Resource allocation schemes are essential to this process. To allocate resources effectively, it is necessary to attach metadata to a task to indicate what kind of resources are needed and how many computation resources are required. However, these metadata are sensitive and can be exposed to eavesdroppers, which can lead to privacy breaches. In addition, edge nodes are vulnerable to corruption because of their limited cybersecurity defenses. Attackers can easily obtain end-device privacy through unprotected metadata or corrupted edge nodes. To address this problem, we propose a metadata privacy resource allocation scheme that uses searchable encryption to protect metadata privacy and zero-knowledge proofs to resist semi-malicious edge nodes. We have formally proven that our proposed scheme satisfies the required security concepts and experimentally demonstrated the effectiveness of the scheme. [ABSTRACT FROM AUTHOR]

Background: Major advances in sequencing technologies and the sharing of data and metadata in science have resulted in a wealth of publicly available datasets. However, working with and especially curating public omics datasets remains challenging despite these efforts. While a growing number of initiatives aim to re-use previous results, these present limitations that often lead to the need for further in-house curation and processing. Results: Here, we present the Omics Dataset Curation Toolkit (OMD Curation Toolkit), a python3 package designed to accompany and guide the researcher during the curation process of metadata and fastq files of public omics datasets. This workflow provides a standardized framework with multiple capabilities (collection, control check, treatment and integration) to facilitate the arduous task of curating public sequencing data projects. While centered on the European Nucleotide Archive (ENA), the majority of the provided tools are generic and can be used to curate datasets from different sources. Conclusions: Thus, it offers valuable tools for the in-house curation previously needed to re-use public omics data. Due to its workflow structure and capabilities, it can be easily used and benefit investigators in developing novel omics meta-analyses based on sequencing data. [ABSTRACT FROM AUTHOR]

The article focuses on examining the impact of presenting evidence from peers on crowdsourced truthfulness assessments. Topics include investigating how presenting evidence affects crowd workers' judgments, the quality of judgments with and without peer evidence, and the influence of peers' political orientation on judgment quality.

This article introduces a new kind of histogram-based representation for univariate random variables, named the phistogram because of its perceptual qualities. The technique relies on shifted groupings of data, creating a color-gradient zone that evidences the uncertainty from smoothing and highlights sampling issues. In this way, the phistogram offers a deep and visually appealing perspective on the finite sample peculiarities, being capable of depicting the underlying distribution as well, thus, becoming an useful complement to histograms and other statistical summaries. Although not limited to it, the present construction is derived from the equal-area histogram, a variant that differs conceptually from the traditional one. As such a distinction is not greatly emphasized in the literature, the graphical fundamentals are described in detail, and an alternative terminology is proposed to separate some concepts. Additionally, a compact notation is adopted to integrate the representation's metadata into the graphic itself. [ABSTRACT FROM AUTHOR]

We present Strokes2Surface, an offline geometry reconstruction pipeline that recovers well‐connected curve networks from imprecise 4D sketches to bridge concept design and digital modeling stages in architectural design. The input to our pipeline consists of 3D strokes' polyline vertices and their timestamps as the 4th dimension, along with additional metadata recorded throughout sketching. Inspired by architectural sketching practices, our pipeline combines a classifier and two clustering models to achieve its goal. First, with a set of extracted hand‐engineered features from the sketch, the classifier recognizes the type of individual strokes between those depicting boundaries (Shape strokes) and those depicting enclosed areas (Scribble strokes). Next, the two clustering models parse strokes of each type into distinct groups, each representing an individual edge or face of the intended architectural object. Curve networks are then formed through topology recovery of consolidated Shape clusters and surfaced using Scribble clusters guiding the cycle discovery. Our evaluation is threefold: We confirm the usability of the Strokes2Surface pipeline in architectural design use cases via a user study, we validate our choice of features via statistical analysis and ablation studies on our collected dataset, and we compare our outputs against a range of reconstructions computed using alternative methods. [ABSTRACT FROM AUTHOR]

Estimating fabric mechanical properties is crucial to create realistic digital twins. Existing methods typically require testing physical fabric samples with expensive devices or cumbersome capture setups. In this work, we propose a method to estimate fabric mechanics just from known manufacturer metadata such as the fabric family, the density, the composition, and the thickness. Further, to alleviate the need to know the fabric family –which might be ambiguous or unknown for nonspecialists–we propose an end‐to‐end neural method that works with planar images of the textile as input. We evaluate our methods using extensive tests that include the industry standard Cusick and demonstrate that both of them produce drapes that strongly correlate with the ground truth estimates provided by lab equipment. Our method is the first to propose such a simple capture method for mechanical properties outperforming other methods that require testing the fabric in specific setups. [ABSTRACT FROM AUTHOR]

Internet image collections containing photos captured by crowds of photographers show promise for enabling digital exploration of large‐scale tourist landmarks. However, prior works focus primarily on geometric reconstruction and visualization, neglecting the key role of language in providing a semantic interface for navigation and fine‐grained understanding. In more constrained 3D domains, recent methods have leveraged modern vision‐and‐language models as a strong prior of 2D visual semantics. While these models display an excellent understanding of broad visual semantics, they struggle with unconstrained photo collections depicting such tourist landmarks, as they lack expert knowledge of the architectural domain and fail to exploit the geometric consistency of images capturing multiple views of such scenes. In this work, we present a localization system that connects neural representations of scenes depicting large‐scale landmarks with text describing a semantic region within the scene, by harnessing the power of SOTA vision‐and‐language models with adaptations for understanding landmark scene semantics. To bolster such models with fine‐grained knowledge, we leverage large‐scale Internet data containing images of similar landmarks along with weakly‐related textual information. Our approach is built upon the premise that images physically grounded in space can provide a powerful supervision signal for localizing new concepts, whose semantics may be unlocked from Internet textual metadata with large language models. We use correspondences between views of scenes to bootstrap spatial understanding of these semantics, providing guidance for 3D‐compatible segmentation that ultimately lifts to a volumetric scene representation. To evaluate our method, we present a new benchmark dataset containing large‐scale scenes with ground‐truth segmentations for multiple semantic concepts. Our results show that HaLo‐NeRF can accurately localize a variety of semantic concepts related to architectural landmarks, surpassing the results of other 3D models as well as strong 2D segmentation baselines. Our code and data are publicly available at https://tau‐vailab.github.io/HaLo‐NeRF/. [ABSTRACT FROM AUTHOR]

Objective: This proof-of-concept study was conducted to establish the feasibility of compiling Federal Interagency Traumatic Brain Injury Research (FITBIR) data pertaining to depression and suicide risk, with the secondary goal of improving understanding regarding these outcomes. FITBIR is a national repository of participant-level traumatic brain injury (TBI) data designed to address methodological limitations (e.g., small sample size, heterogeneity of injuries). Method: FITBIR studies with TBI severity and measures related to depression and suicidal ideation were identified. Data were harmonized across relevant studies and grouped to identify "probable depression" and suicidal ideation, resulting in a large, combined sample. Rates of probable depression and suicidal ideation were described across the available studies, considering the influence of demographic and/or injury-related factors on outcomes. Results: Cross-sectional studies meeting criteria included four studies with depression outcomes and two with suicidal ideation outcomes. Two studies reported data appropriate for comparative analyses on depression. Combined results suggested that approximately 71% of participants were categorized as having probable depression. Participants with a history of mild TBI had 2.54 greater odds of probable depression (95% confidence interval [1.93, 3.34]) than those without a history of TBI. Conclusions: Methods, harmonization code, and meta-databases related to TBI, probable depression, and suicidal ideation are now publicly available on the FITBIR website. Even with limited data, harmonization of FITBIR studies can serve as the basis for ongoing TBI and mental health research. Analyses will be more robust in the future as more studies with relevant outcome data are added to the FITBIR database. Impact and Implications: This study demonstrates the feasibility of harmonizing participant-level data from Federal Interagency Traumatic Brain Injury Research (FITBIR) into a single meta-database. Participants with mild traumatic brain injury (TBI) had greater odds of meeting criteria for probable depression than those without TBI. Methodological products including harmonization and data-analysis code and the TBI depression meta-data set have been made publicly available through the FITIBIR website. [ABSTRACT FROM AUTHOR]

A homogenized daily mean temperature series from 1915 to 2021 at Beijing Observatory (BO) has been developed. A thorough investigation of observation records and historical metadata was carried out to identify specific non‐climatic biases. The inhomogeneities were detected and adjusted with the optimally selected reference stations using a statistical reduction methodology. The results indicated three types of non‐climatic biases in temperature records: the first was the relocation of BO from suburban to urban, which caused positive shifts in temperature records, especially for wintertime; the second arose from different methods for calculating daily mean temperature, which caused different sign biases varying with months; and the last was caused by the transition from manual to automatic measurements with site‐specific biases. The corresponding adjustments due to three type biases ranged from −1.13 to 0.63, −0.29 to 0.23 and −0.13 to 0.00°C, respectively. The new homogenized annual mean temperature series showed a warming trend of 0.199°C/decade during 1915–2021. The trend was more pronounced in winter than in the other three seasons. The warming trend in the new series is greater than those in the previous homogenized series (0.136–0.177°C/decade), primarily due to the more effective adjustment associated with the site relocation, particularly for more urban locations. [ABSTRACT FROM AUTHOR]

The interplanetary File system (IPFS) provides data communication using plaintext over distributed and decentralized systems. Up till now, the security of data has mostly been established using keys. To facilitate classified data communication within a Closed User Group (CUG), services of IPFS private swarm are required to render additional content encryption. Currently, there is no inherent security built into IPFS. This paper presents an application DMaya on IPFS to provide keyless encryption on IPFS based on the Quasigroup-based Secret Sharing Scheme (QSS). IPFS is used as a storage medium, irrespective of the nature of data. Data security in decentralized mode with IPFS is provided with DMaya. The classified data of all types (i.e. video data, audio data, text data, and image data) when subjected to DMaya application, are fragmented into smaller fragments then processed by the probabilistic Quasigroup-based Secret Sharing (QSS) Scheme. DMaya keyless encryption generates the metadata tag file at the source node. The recipient node within the same private IPFS swarm, on receipt of metadata tag file reconstructs the original data with DMaya application. [ABSTRACT FROM AUTHOR]

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since late 2019 represented an unprecedented public health emergency, which included a need to fully understand coronavirus disease 2019 (COVID-19) across all ages and populations. In response, the US National Institute of Allergy and Infectious Diseases (NIAID) rapidly funded epidemiology studies that monitored COVID-19. However, the diversity and breadth of the populations studied in NIAID-funded COVID-19 observational cohorts were not easy to extrapolate because of siloed approaches to collect and report data within NIAID. Here, we describe the effort to develop a harmonized cohort-study reporting tool that includes common epidemiologic data elements as well as NIAID priorities. We report its implementation to analyze metadata from 58 COVID-19 cohort studies funded from February 2020 to June 2021, and we visualize key metadata, including geographic distribution, study duration, participant demographic characteristics, sample types collected, and scientific priorities addressed. A bibliographic analysis highlights the scientific publications and citations across these funded studies and demonstrates their enormous impact on the COVID-19 field. These analyses highlight how common data elements and reporting tools can assist funding agencies to capture the landscape and potential gaps during public health responses and how they can assist in decision making. [ABSTRACT FROM AUTHOR]

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design. [ABSTRACT FROM AUTHOR]

Research data sharing has become an expected component of scientific research and scholarly publishing practice over the last few decades, due in part to requirements for federally funded research. As part of a larger effort to better understand the workflows and costs of public access to research data, this project conducted a high-level analysis of where academic research data is most frequently shared. To do this, we leveraged the DataCite and Crossref application programming interfaces (APIs) in search of Publisher field elements demonstrating which data repositories were utilized by researchers from six academic research institutions between 2012–2022. In addition, we also ran a preliminary analysis of the quality of the metadata associated with these published datasets, comparing the extent to which information was missing from metadata fields deemed important for public access to research data. Results show that the top 10 publishers accounted for 89.0% to 99.8% of the datasets connected with the institutions in our study. Known data repositories, including institutional data repositories hosted by those institutions, were initially lacking from our sample due to varying metadata standards and practices. We conclude that the metadata quality landscape for published research datasets is uneven; key information, such as author affiliation, is often incomplete or missing from source data repositories and aggregators. To enhance the findability, interoperability, accessibility, and reusability (FAIRness) of research data, we provide a set of concrete recommendations that repositories and data authors can take to improve scholarly metadata associated with shared datasets. [ABSTRACT FROM AUTHOR]

AbstractDiscussions surrounding digital libraries and their metadata have become less robust than before, given that creating and hosting digital collections have become the norm for most cultural heritage institutions over the last 20 years. Consequently, there are fewer discussions of how the characteristics of digital collections and their metadata have changed over time. This article showcases the evolution of digital collections and their metadata at the University of Illinois Urbana-Champaign (UIUC) Library in the last 20 years. It discusses the growth of its collections and their characteristics, examines historical changes in the use of metadata elements, and explores responses to the changing nature of digitized and born-digital materials. Based on a large-scale data analysis of the digital collections and their metadata housed in UIUC Digital Library, the paper also examines the challenges and opportunities of the curation and management of digital collections and digital libraries in the future. [ABSTRACT FROM AUTHOR]

Accurate medical image segmentation can effectively assist disease diagnosis and treatment. While neural networks were often applied to solve the segmentation problem in recent computer-aided diagnosis, the metadata of patients was usually neglected. Motivated by this, we propose a medical image segmentation and diagnosis framework that takes advantage of both the image and the patient’s metadata, such as gender and age. We present MMY-NET: a new multi-modal network for simultaneous tumor segmentation and diagnosis exploiting patient metadata. Our architecture consists of three parts: a visual encoder, a text encoder, and a decoder with a self-attention block. Specifically, we design a text preprocessing block to embed metadata effectively, and the image features and text embedding features are then fused on several layers between the two encoders. Moreover, Interlaced Sparse Self-Attention is added to the decoder to further boost the performance. We apply our algorithm on 1 private dataset (ZJU2), and 1 private dataset (LISHUI) for zero-shot validation. Results show that our algorithm combined with metadata outperforms its counterpart without metadata by a large margin for basal cell carcinoma segmentation (14.3 % improvement of IoU and 8.5 % of Dice on the ZJU2 dataset, and 7.1 % IoU on the LIZHUI validation dataset). Additionally, we applied MMY-Net to 1 public segmentation dataset to demonstrate its general segmentation capability. MMY-Net outperforms the state-of-the-art methods on the GlaS dataset. [ABSTRACT FROM AUTHOR]

Objective: Wikipedia is the most frequently accessed online health information resource and is well positioned as a valuable tool for public health communication and knowledge translation. The authors aimed to explore their institution's health and medical research reach by analyzing its presence in Wikipedia articles. Methods: In October 2022, a comprehensive database search was constructed in PubMed to retrieve clinical evidence syntheses published by at least one author affiliated with McMaster University from 2017 to 2022, inclusive. Altmetric Explorer was queried using PubMed Identifiers and article titles to access metadata and Wikipedia citation data. 3,582 health evidence syntheses from at least one McMaster University affiliated author were analyzed. Results: Six percent (n=219) of health evidence syntheses from the authors' institution were cited 568 times in 524 unique Wikipedia articles across 28 different language editions. 45% of citations appeared in English Wikipedia, suggesting a broad global reach for the institutions' research outputs. When adjusted for open access publications, 8% of McMaster University's health evidence syntheses appear in Wikipedia. Conclusion: Altmetric Explorer is a valuable tool for exploring the reach of an institution's research outputs. Isolating Altmetric data to focus on Wikipedia citations has value for any institution wishing to gain more insight into the global, community-level reach of its contributions to the latest health and medical evidence. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to adjust Thesis-type properties on Schema.org using metadata models and standards (MS) (Bibframe, electronic thesis and dissertations [ETD]-MS, Common European Research Information Format [CERIF] and Dublin Core [DC]) to enrich the Thesis-type properties for better description and processing on the Web. Design/methodology/approach: This study is applied, descriptive analysis in nature and is based on content analysis in terms of method. The research population consisted of elements and attributes of the metadata model and standards (Bibframe, ETD-MS, CERIF and DC) and Thesis-type properties in the Schema.org. The data collection tool was a researcher-made checklist, and the data collection method was structured observation. Findings: The results show that the 65 Thesis-type properties and the two levels of Thing and CreativeWork as its parents on Schema.org that corresponds to the elements and attributes of related models and standards. In addition, 12 properties are special to the Thesis type for better comprehensive description and processing, and 27 properties are added to the CreativeWork type. Practical implications: Enrichment and expansion of Thesis-type properties on Schema.org is one of the practical applications of the present study, which have enabled more comprehensive description and processing and increased access points and visibility for ETDs in the environment Web and digital libraries. Originality/value: This study has offered some new Thesis type properties and CreativeWork levels on Schema.org. To the best of the authors' knowledge, this is the first time this issue is investigated. [ABSTRACT FROM AUTHOR]

The widespread adoption of cryoEM technologies for structural biology has pushed the discipline to new frontiers. A significant worldwide effort has refined the single‐particle analysis (SPA) workflow into a reasonably standardized procedure. Significant investments of development time have been made, particularly in sample preparation, microscope data‐collection efficiency, pipeline analyses and data archiving. The widespread adoption of specific commercial microscopes, software for controlling them and best practices developed at facilities worldwide has also begun to establish a degree of standardization to data structures coming from the SPA workflow. There is opportunity to capitalize on this moment in the maturation of the field, to capture metadata from SPA experiments and correlate the metadata with experimental outcomes, which is presented here in a set of programs called EMinsight. This tool aims to prototype the framework and types of analyses that could lead to new insights into optimal microscope configurations as well as to define methods for metadata capture to assist with the archiving of cryoEM SPA data. It is also envisaged that this tool will be useful to microscope operators and facilities looking to rapidly generate reports on SPA data‐collection and screening sessions. [ABSTRACT FROM AUTHOR]

With the field of technology has witnessed rapid advancements, attracting an ever-growing community of researchers dedicated to developing theories and techniques. This paper proposes an innovative ICRM (Intelligent Citation Recommendation Mechanism), designed to automate the process of suggesting the appropriate number of citations for individual brackets within a document. The proposed ICRM comprises three phases: Coarse-grained Weighted Bag of Word (WCBW), Fine-grained SciBERT (FSB) and Citation Adjustment phases. Firstly, the WCBW phase employs TF-IDF to extract keywords from both target and candidate documents, forming vectors that capture word significance along with metadata like authorship, keywords, and titles. It aims to identify relevant papers from a database, serving as initial candidates for each bracket. Secondly, the FSB phase employs the SciBERT model to assess the similarity between candidate documents and the local context around brackets, enhancing the precision of recommendations. It refines this selection by analyzing candidate-document relationships within the proximity of the brackets. Lastly, the Citation Adjustment phase tackles overlapping citations and ensures that recommended citation numbers align with user-defined criteria, resolving issues of imbalance. The simulation results demonstrate that the proposed ICRM outperforms existing models significantly in terms of precision, recall and F1-score. [ABSTRACT FROM AUTHOR]

Libraries at academic institutions have been involved in research data management services (RDMS) for more than ten years. Institutions have adapted their service models in response to funder, journal, and federal mandates that have consequently increased RDMS demand. However, institutions that hope to start or grow their services may have difficulty extrapolating from the published literature, as few studies recount RDMS development strategies. [ABSTRACT FROM AUTHOR]

In our generation, there is an undoubted rise in the use of social media and specifically photo and video sharing platforms. These sites have proved their ability to yield rich data sets through the users' interaction which can be used to perform a data‐driven evaluation of capabilities. Nevertheless, this study reveals the lack of suitable data sets in photo and video sharing platforms and evaluation processes across them. In this way, our first contribution is the creation of one of the largest labelled data sets in Flickr with the multimodal data which has been open sourced as part of this contribution. It incorporates multimodal data, combining information from various sources such as user profiles, photo metadata, and crowdsourced features. Predicated on these data, we explored machine learning models and concluded that it is feasible to properly predict whether a user is a professional photographer or not based on self‐reported occupation labels and several feature representations out of the user, photo and crowdsourced sets. We also examined the relationship between the aesthetics and technical quality of a picture and the social activity of that picture. Finally, we depicted which characteristics differentiate professional photographers from non‐professionals. As far as we know, the results presented in this work represent an important novelty for identifying expertise in the domain of photography, which researchers from various domains can utilise for related applications. [ABSTRACT FROM AUTHOR]

Objective: The peripheral B cell compartment is heavily disturbed in systemic lupus erythematosus (SLE), but whether B cells develop aberrantly in the bone marrow (BM) is largely unknown. Methods: We performed single‐cell RNA/B cell receptor (BCR) sequencing and immune profiling of BM B cells and classified patients with SLE into two groups: early B cell (Pro‐B and Pre‐B) normal (EBnor) and EB defective/low (EBlo) groups. Results: The SLE‐EBlo group exhibited more severe disease activity and proinflammatory status, overaction of type I interferon signaling and metabolic pathways within the B cell compartment, and aberrant BCR repertoires compared with the SLE‐EBnor group. Moreover, in one patient with SLE who was initially classified in the SLE‐EBlo group, early B cell deficiency and associated abnormalities were largely rectified in a second BM sample at the remission phase. Conclusion: In summary, this study suggests that early B cell loss in BM defines a unique pathological state in a subset of patients with SLE that may play an active role in the dysregulated autoimmune responses. [ABSTRACT FROM AUTHOR]

This article introduces the CELI corpus, a new learner corpus of written Italian consisting of ca. 600,000 tokens, evenly distributed among CEFR (Common European Framework of Reference for Languages) proficiency levels B1, B2, C1 and C2. The collected texts derive from the language certification exams administered by the University for Foreigners of Perugia all around the world. The corpus contains rich metadata pertaining to text-related and learner-related variables. It expands the domain of learner corpora by being, among other things, both freely available online to the research community, and by focusing on a target language other than English. The article also presents and evaluates the POS-tagging procedure, thus contributing to best practices in learner corpus annotation. [ABSTRACT FROM AUTHOR]

Objectives: Ancient human dental calculus is a unique, nonrenewable biological resource encapsulating key information about the diets, lifestyles, and health conditions of past individuals and populations. With compounding calls its destructive analysis, it is imperative to refine the ways in which the scientific community documents, samples, and analyzes dental calculus so as to maximize its utility to the public and scientific community. Materials and Methods: Our research team conducted an IRB‐approved survey of dental calculus researchers with diverse academic backgrounds, research foci, and analytical specializations. Results: This survey reveals variation in how metadata is collected and utilized across different subdisciplines and highlights how these differences have profound implications for dental calculus research. Moreover, the survey suggests the need for more communication between those who excavate, curate, and analyze biomolecular data from dental calculus. Discussion: Challenges in cross‐disciplinary communication limit researchers' ability to effectively utilize samples in rigorous and reproducible ways. Specifically, the lack of standardized skeletal and dental metadata recording and contamination avoidance procedures hinder downstream anthropological applications, as well as the pursuit of broader paleodemographic and paleoepidemiological inquiries that rely on more complete information about the individuals sampled. To provide a path forward toward more ethical and standardized dental calculus sampling and documentation approaches, we review the current methods by which skeletal and dental metadata are recorded. We also describe trends in sampling and contamination‐control approaches. Finally, we use that information to suggest new guidelines for ancient dental calculus documentation and sampling strategies that will improve research practices in the future. [ABSTRACT FROM AUTHOR]

Metadata is vital for information storage and retrieval from a database or repository. In the case of Research Data Repositories (RDRs), metadata can be a potent tool for describing and identifying data. Further, producing the metadata is indispensable for fostering data reuse. A filtered view of the registry of research data repositories, re3data.org, depicts no uniform patterns or standards for metadata in the case of RDRs, and the metadata elements and practices differ from RDR to RDR. The present study describes the features of a select number of RDRs and analyzes their metadata practices: Harvard Dataverse, Dryad, Figshare, Zenodo, and the Open Science Framework (OSF). It further examines the total number of metadata elements, common metadata elements, required metadata elements, and item-level metadata. Results indicate that even though Harvard Dataverse has the most metadata elements, Dryad provides rich metadata concerning item level. This study suggests a common metadata framework, richer metadata elements, and more features to make the research data's interoperability possible from one RDR to another. [ABSTRACT FROM AUTHOR]

To address the lack of standardized metadata in the historic dress and costume field and increase the searchability and discoverability of online fashion collections, a university collection adopted Costume Core, a metadata schema with controlled vocabulary for fashion artifacts, to develop the digital collection and to assess and improve the usability of the schema. This paper presents a case study delving into the process, benefits, and limitations of using Costume Core to catalog fashion artifacts. It includes a discussion on converting handwritten and typewritten metadata from physical catalog cards into a digital text format using Optical Character Recognition (OCR) technology. Costume Core provided a fundamental framework for digitizing and cataloging the university fashion collection while ensuring consistency in the terminology used to describe artifacts in the collection. Nevertheless, there is room for improvement for Costume Core, particularly by expanding the schema by adding controlled terms to increase the accuracy of terms chosen to describe fashion artifacts. Therefore, work is underway to increase its usability, thus promoting its adoption among other fashion collections. [ABSTRACT FROM AUTHOR]

As part of a multi-faceted research project examining user engagement with various types of descriptive metadata to improve metadata services, Utah State University Libraries Cataloging and Metadata Services unit investigated user search behavior in library catalog (MARC) records, Encoded Archival Description (EAD) finding aids, and most recently in digital collection metadata. The authors used web log analysis to determine how users interacted with CONTENTdm, categories of search terms used, and where search terms were found in a record. Key findings included that navigation through CONTENTdm using clickable queries (links) is a prominent user search pattern, dates are an important faceting tool and date ranges as a clickable link are heavily used, users demonstrated a more engaged research pattern when searching with geographic terms, and subject and transcription metadata fields match user search terms at a significant rate and are likely to be high drivers of search results. [ABSTRACT FROM AUTHOR]

Why was the British Parliament so late in broadcasting its debates? Scholars have made recommendations on parliamentary communication, analysed its effects, and described the debates and arguments on broadcasting parliament. But who was making these arguments, and what role did parliamentarians' identities play in these debates? We show the crucial role that partisanship—but also the distinctions between government and opposition, senior and junior, and urban and rural MPs—played in Westminster's debates on broadcasting itself. We do so by applying our new method of 'structural collocation analysis' to all 3965 debate utterances on broadcasting parliament between 1935 and 2014—rather than merely the eleven official debates on broadcasting parliament studied thus far—comparing utterances by subgroups of MPs using metadata that we added to the digitised proceedings. We focus on issue ownership, discursive differences and MPs' reflections on broadcasting parliament. [ABSTRACT FROM AUTHOR]

Geoscientific models have rapidly developed in recent decades as effective tools to understand the past, perceive the present, and predict the future. However, with the increasing number of models available, discovering suitable ones and applying them properly in problem‐solving situations has become more challenging. Existing materials describing geoscientific models (e.g., articles, manuals, handbooks, metadata documents, and web pages) are scattered and varied in structure and content. To help model users from different disciplinary backgrounds find, access, implement, and reuse models more conveniently, we propose an open knowledge framework for geoscientific models. The knowledge framework includes three levels: a resource level for indicating where to find a model, a connection level for indicating what materials are related to a model, and an application level for indicating how the model is applied. Through such a three‐level framework, model users can collaboratively provide descriptive information for a model, link different materials to a model (e.g., data, references, and tools), and contribute experiences regarding model application in practical cases (as reusable solutions). Thus, a web‐based community can be formed to facilitate the better use of geoscientific models. This article introduces the Open Geographic Modeling and Simulation System (OpenGMS) as the implementation of this open knowledge framework. Case studies are given to showcase the effectiveness and capability of the proposed framework. [ABSTRACT FROM AUTHOR]

Materials related to Japanese military "comfort women" in Korea are managed by several institutions. Each digital archive has their own metadata schema and management policies. So far, a standard or a common guideline for describing digital records is not formalized. We propose a Japanese military "comfort women" knowledge graph to semantically interlink the digital records from distributed digital archives. To build a Japanese military "comfort women" knowledge graph, digital records and descriptive metadata were collected from existing digital archives. A list of metadata was defined by analyzing commonly used properties and a knowledge model designed by reusing standard vocabularies. Knowledge was constructed by interlinking the collected records, external data sources, and enriching data. The knowledge graph was evaluated using the FAIR data maturity model. [ABSTRACT FROM AUTHOR]

As microscopy diversifies and becomes ever more complex, the problem of quantification of microscopy images has emerged as a major roadblock for many researchers. All researchers must face certain challenges in turning microscopy images into answers, independent of their scientific question and the images they have generated. Challenges may arise at many stages throughout the analysis process, including handling of the image files, image pre‐processing, object finding, or measurement, and statistical analysis. While the exact solution required for each obstacle will be problem‐specific, by keeping analysis in mind, optimizing data quality, understanding tools and tradeoffs, breaking workflows and data sets into chunks, talking to experts, and thoroughly documenting what has been done, analysts at any experience level can learn to overcome these challenges and create better and easier image analyses. [ABSTRACT FROM AUTHOR]

Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age groups. Their estimation, however, is generally time and effort consuming and model-driven strategies to quantify the contacts are often needed. In this article we focus on household contact matrices, describing the contacts among the members of a family and develop a parametric model to describe them. This model combines demographic and easily quantifiable survey-based data and is tested on high resolution proximity data collected in two sites in South Africa. Given its simplicity and interpretability, we expect our method to be easily applied to other contexts as well and we identify relevant questions that need to be addressed during the data collection procedure. [ABSTRACT FROM AUTHOR]