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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]

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 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]

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]

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]

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]

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]

Here we present a method for using the spatial x–y coordinate of an image cropped from the cylindrical surface of digital 3D drill core images and demonstrate how this spatial metadata can be used to improve unsupervised machine learning performance. This approach is applicable to any data set with known spatial context, however, here it is used to classify 400 m of drillcore imagery into 12 distinct classes reflecting the dominant rock types and alteration features in the core. We modified two unsupervised learning models to incorporate spatial metadata and an average improvement of 25% was achieved over equivalent models that did not utilize metadata. Our semi‐supervised workflow involves unsupervised network training followed by semi‐supervised clustering where a support vector machine uses a subset of M expert labeled images to assign a pseudolabel to the entire data set. Fine‐tuning of the best performing model showed an f1 (macro average) of 90%, and its classifications were used to estimate bulk fresh and altered rock abundance downhole. Validation against the same information gathered manually by experts when the core was recovered during the Oman Drilling Project revealed that our automatically generated data sets have a significant positive correlation (Pearson's r of 0.65–0.72) to the expert generated equivalent, demonstrating that valuable geological information can be generated automatically for 400 m of core with only ∼24 hr of domain expert effort. Plain Language Summary: This work presents a novel method for using the spatial context of digital core images to improve the descriptive accuracy of unsupervised machine learning algorithms. The addition of spatial metadata improves model performance by an average of 25%, with the best performing model in this study achieving an accuracy score of 90%. The output of this model was then used to estimate the amount of fresh and altered rock within a 400 m long drill core, which was shown to be of comparable quality to the same estimations made by geologists on the cores themselves. Key Points: Use of spatial metadata improves state‐of‐the‐art unsupervised feature extractionSemi‐supervised methods using spatial metadata outperform supervised methods for the same expert labeling effortNew methods described enable the standardization of core‐logging processes and improve cross‐dataset comparisons [ABSTRACT FROM AUTHOR]

Ovarian abnormality like polycystic ovarian disease (PCOD) is one of the most common diseases among women worldwide. PCOD not only has an impact on infertility but also hurts the psychological well‐being of women affecting their quality of life. In this study, a two‐class pattern learning problem is designed for the classification of PCOD. In total, 37 clinical parameters and abdominal ultrasound images of women are collected under the proper ethical protocol. Using only clinical data, an accuracy of 93.7% is obtained using Random Forest as the classifier which is further improved to 95.54% by using a Randomized Search CV during Random Forest classification. The ultrasound images are classified using the proposed Attention‐UNet architecture and a mean Dice score of 0.945 is obtained indicating more accurate segmentation. The segmented images are passed through the state‐of‐the‐art EfficientNet B6 for the classification of PCOS and non‐PCOS and recorded an accuracy of 95.47%. Using big data architecture Pyspark, the performance is further enhanced to 96.8% and 96.3% for clinical and ultrasound images respectively along with the reduced computational speed. The results of these classifiers are then used to create metadata and a customized Artificial Neural Network is applied for the final prediction of PCOD and non‐PCOD. From the results, it can be seen that the stacking model outperformed with an accuracy of 98.12% when compared to the single classifier. Our proposed method has very good performance with less computation, contributing a new architecture to evaluate PCOD and hence helping to improve the wellness of women. [ABSTRACT FROM AUTHOR]

On this, the occasion of its 50th anniversary, we employ a quantitative analysis of the Journal of Law and Society (JLS) to chart empirically the evolution of socio‐legal studies in the United Kingdom (UK). By tracing the influence(s) of the JLS upon the development of UK socio‐legal research, not only do we demonstrate a new mode of exploring knowledge production in the field of socio‐legal studies, but we also illustrate how computational methods can augment hermeneutical approaches to mapping socio‐legal trends. Through (a blend of) three different analytical approaches – descriptive analyses of bibliographic metadata, text‐linguistic analyses of a corpus of full‐text articles, and network analyses of citation graphs – we generate comparative information about the JLS since its inception in 1974. We then employ this data to interrogate the JLS' own narratives; using predictions, ambitions, and statements of intent made by Editor‐in‐Chief Phil Thomas published either within or regarding the JLS, we present a map of the journal's role within, impact upon, and enduring contribution to UK socio‐legal studies. Finally, we discuss our results and propose future directions of the field. [ABSTRACT FROM AUTHOR]

Identifying factors that associate with more cited or higher quality research may be useful to improve science or to support research evaluation. This article reviews evidence for the existence of such factors in article text and metadata. It also reviews studies attempting to estimate article quality or predict long‐term citation counts using statistical regression or machine learning for journal articles or conference papers. Although the primary focus is on document‐level evidence, the related task of estimating the average quality scores of entire departments from bibliometric information is also considered. The review lists a huge range of factors that associate with higher quality or more cited research in some contexts (fields, years, journals) but the strength and direction of association often depends on the set of papers examined, with little systematic pattern and rarely any cause‐and‐effect evidence. The strongest patterns found include the near universal usefulness of journal citation rates, author numbers, reference properties, and international collaboration in predicting (or associating with) higher citation counts, and the greater usefulness of citation‐related information for predicting article quality in the medical, health and physical sciences than in engineering, social sciences, arts, and humanities. [ABSTRACT FROM AUTHOR]

Cryo‐electron microscopy (cryo‐EM) has witnessed radical progress in the past decade, driven by developments in hardware and software. While current software packages include processing pipelines that simplify the image‐processing workflow, they do not prioritize the in‐depth analysis of crucial metadata, limiting troubleshooting for challenging data sets. The widely used RELION software package lacks a graphical native representation of the underlying metadata. Here, two web‐based tools are introduced: relion_live.py, which offers real‐time feedback on data collection, aiding swift decision‐making during data acquisition, and relion_analyse.py, a graphical interface to represent RELION projects by plotting essential metadata including interactive data filtration and analysis. A useful script for estimating ice thickness and data quality during movie pre‐processing is also presented. These tools empower researchers to analyse data efficiently and allow informed decisions during data collection and processing. [ABSTRACT FROM AUTHOR]

Microorganisms have evolved diverse strategies to acquire the vital element nitrogen (N) from the environment. Ecological and physiological controls on the distribution of these strategies among microbes remain unclear. In this study, we examine the distribution of 10 major N acquisition strategies in taxonomically and metabolically diverse microbial genomes, including those from the Genomic Catalogue of Earth's Microbiomes dataset. We utilize a marker gene‐based approach to assess relationships between N acquisition strategy prevalence and microbial life history strategies. Our results underscore energetic costs of assimilation as a broad control on strategy distribution. The most prevalent strategies are the uptake of ammonium and simple amino acids, which have relatively low energetic costs, while energy‐intensive biological nitrogen fixation is the least common. Deviations from the energy‐based framework include the higher‐than‐expected prevalence of the assimilatory pathway for chitin, a large organic polymer. Energy availability is also important, with aerobic chemoorganotrophs and oxygenic phototrophs notably possessing ~2‐fold higher numbers of total strategies compared to anaerobic microbes. Environmental controls are evidenced by the enrichment of inorganic N assimilation strategies among free‐living taxa compared to host‐associated taxa. Physiological constraints such as pathway incompatibility add complexity to N acquisition strategy distributions. Finally, we discuss the necessity for microbially‐relevant spatiotemporal environmental metadata for improving mechanistic and prediction‐oriented analyses of genomic data. [ABSTRACT FROM AUTHOR]

Motivation: A well‐constructed nest is a key element of successful reproduction in most species of birds, and nest morphology varies widely across the class. Macroecological and macroevolutionary studies tend to group nest design into a small number of discrete categories, often based on taxonomic inference. In reality, however, many species display considerable intraspecific variation in their nest‐building behaviour, and broad‐level categories may include several functionally distinct nest types. To address this imprecision in the literature and facilitate future studies of broad‐scale variation in avian parental care, we here introduce a detailed, global comparative database of nest building in birds, together with preliminary correlations between these traits and species‐level environmental variables. Main types of variables contained: We present species‐level data for nest structure, location, height, material composition, sex of builder, building time and nest dimensions. Spatial location and grain: Global. Maps are presented at the 10 × 10 level. Time period and grain: Included species are generally extant, although we present some data for recently extinct taxa. The data were collected in 2017–2021 and was drawn from secondary sources published in 1992–2021. Major taxa and level of measurement: Partial or complete trait data is presented for 8601 species of birds, representing 36 of 36 orders and 239 of 243 families. Software format: Data have been uploaded as Supplementary Material in.csv format and are separated by species and source for all traits (Dataset S1, and Metadata) as well as summarized at the species level for the major structure and location variables (Dataset S2, and Metadata). [ABSTRACT FROM AUTHOR]

Transition to novel environments, such as groundwater colonization by surface organisms, provides an excellent research ground to study phenotypic evolution. However, interspecific comparative studies on evolution to groundwater life are few because of the challenge in assembling large ecological and molecular resources for species‐rich taxa comprised of surface and subterranean species. Here, we make available to the scientific community an operational set of working tools and resources for the Asellidae, a family of freshwater isopods containing hundreds of surface and subterranean species. First, we release the World Asellidae database (WAD) and its web application, a sustainable and FAIR solution to producing and sharing data and biological material. WAD provides access to thousands of species occurrences, specimens, DNA extracts and DNA sequences with rich metadata ensuring full scientific traceability. Second, we perform a large‐scale dated phylogenetic reconstruction of Asellidae to support phylogenetic comparative analyses. Of 424 terminal branches, we identify 34 pairs of surface and subterranean species representing independent replicates of the transition from surface water to groundwater. Third, we exemplify the usefulness of WAD for documenting phenotypic shifts associated with colonization of subterranean habitats. We provide the first phylogenetically controlled evidence that body size of males decreases relative to that of females upon groundwater colonization, suggesting competition for rare receptive females selects for smaller, more agile males in groundwater. By making these tools and resources widely accessible, we open up new opportunities for exploring how phenotypic traits evolve in response to changes in selective pressures and trade‐offs during groundwater colonization. [ABSTRACT FROM AUTHOR]

This study examines the concept of "description" and its theoretical foundations. The literature about it is surprisingly limited, and its usage is vague, sometimes even conflicting. Description should be considered in relation to other processes, such as representation, data capturing, and categorizing, which raises the question about what it means to describe something. Description is often used for any type of predication but may better be limited to predications based on observations. Research aims to establish criteria for making optimal descriptions; however, the problems involved in describing something have seldom been addressed. Specific ideals are often followed without examine their fruitfulness. This study provides evidence that description cannot be a neutral, objective activity; rather, it is a theory‐laden and interest‐based activity. In information science, description occurs in processes such as document description, descriptive metadata assignment, and information resource description. In this field, description has equally been used in conflicting ways that mostly do not evince a recognition of the value‐ and theory‐laden nature of descriptions. It is argued that descriptive activities in information science should always be based on consciously explicit considerations of the goals that descriptions are meant to serve. [ABSTRACT FROM AUTHOR]

The complementary feeding period is a critical stage of child development when micronutrient needs are high and challenging to meet. Understanding if specific micronutrient gaps exist during this period is critical for effective programming. A Comprehensive Nutrient Gap Assessment (CONGA) was conducted in seven countries in Southeast Asia to estimate gaps in micronutrients commonly lacking in the diets of children aged 6–23 months and to establish the certainty of available evidence for each identified gap. Sixty‐eight evidence sources were identified during this analysis, and 310 micronutrient‐specific data points were identified across all seven countries. Data points varied in recency, representativeness and evidence type. The CONGA methodology enabled the estimation of a gap burden rating for each micronutrient in each country, as well as a rating of their evidence certainty. Micronutrient gaps were identified in vitamin D, zinc and iron and a potential gap was identified in calcium during the complementary feeding period in the region. Evidence relevant to intake and deficiency of folate, vitamin B12, thiamine, niacin, vitamin C and vitamin B6 was limited across the region. Proven strategies to address these gaps include increasing the availability and consumption of nutrient‐dense foods, micronutrient supplementation, large‐scale fortification of staple foods and condiments and point‐of‐use fortification through multiple micronutrient powders and fortified speciality foods. More recent data on micronutrient availability, intake and deficiency is urgently needed in Southeast Asia. Key messages: Older infants and young children aged 6–23 months experience micronutrient gaps during the complementary feeding period in Southeast Asia. Synthesis of evidence compiled across seven countries in the region identified gaps in vitamin D, zinc and iron and a potential gap in calcium during this critical period.National nutrition policies and programmes should consider multiple strategies to address these micronutrient gaps.Over half of the data points relevant to nutrient deficiency and intake compiled from the seven countries are over a decade old. More recent data on micronutrient availability, intake and deficiency is urgently needed in Southeast Asia. [ABSTRACT FROM AUTHOR]

The global crisis in antimicrobial resistance continues to grow. Estimating the risks of antibiotic resistance transmission across habitats is hindered by the lack of data on mobility and habitat‐specificity. Metagenomic samples of 6092 are analyzed to delineate the unique core resistomes from human feces and seven other habitats. This is found that most resistance genes (≈85%) are transmitted between external habitats and human feces. This suggests that human feces are broadly representative of the global resistome and are potentially a hub for accumulating and disseminating resistance genes. The analysis found that resistance genes with ancient horizontal gene transfer (HGT) events have a higher efficiency of transfer across habitats, suggesting that HGT may be the main driver for forming unique but partly shared resistomes in all habitats. Importantly, the human fecal resistome is historically different and influenced by HGT and age. The most important routes of cross‐transmission of resistance are from the atmosphere, buildings, and animals to humans. These habitats should receive more attention for future prevention of antimicrobial resistance. The study will disentangle transmission routes of resistance genes between humans and other habitats in a One Health framework and can identify strategies for controlling the ongoing dissemination and antibiotic resistance. [ABSTRACT FROM AUTHOR]

The rapid increase and use of educational technologies have a significant impact on students' privacy, personal information and metadata in higher education. The past two decades have also witnessed the process where information about students is stored and handled outside premises and control of learning institutions. The personal information about students and their activity while they interact with learning management systems (LMS) and online learning tools is increasing and is stored in cloud computing platforms, software‐as‐a‐service providers and other vendors. There are reported cases where students' personal data and information have been leaked, with possible privacy violations. Although this issue affects all students, it is important to understand the perspectives of culturally diverse students on the balancing of personal data/information and the use of technology integration in higher education. The purpose of this research was to investigate diverse students' perspectives on privacy, control of personal information, confidentiality and technology integration. The study also aimed to examine the challenges and experiences of loss of control over personal data and metadata encroachment, and protection of privacy in online education. Data were collected following a qualitative research design. Forty in‐depth and semi‐structured focus‐group interviews (26 female and 24 male students) from four academic disciplines (Education, Social Sciences, Business, and Health Sciences) in a public university in the United States were obtained and analysed following a constant comparative analysis approach. Findings show evidence of fear and anxiety about data encroachment, challenges from bureaucratic procedures and lack of educational awareness, privacy concerns about LMS and social media. These results contribute to a new understanding regarding diverse students' knowledge, challenges and experiences on how to balance privacy, confidentiality and technology integration in higher education. Practitioner notesWhat is already known about this topic Considering the increasing Internet world, where new technologies and mobile computing are interwoven in the use of digital technologies and access to information, balancing students' privacy and technology integration is essential in providing students assurance of their data security and privacy.Few studies have explored diverse students' perspectives on privacy and technology integration that include control of personal information, confidentiality and technology integration. Further, there is a dearth of studies on the challenges and experiences of diverse students regarding the loss of control over personal data and metadata encroachment, and protection of privacy in online education.Although rapid digitalization sparked studies about privacy and data usage, such as the perception of privacy breaches for the purpose of COVID‐19 pandemic control, few studies have also raised privacy issues related to student data usage in higher education institutions (HEIs) in the post‐COVID‐19 context. To realise justice technology integration and data usage in HEIs, students' perspectives on privacy should be examined.What this paper adds The results show the following: fear and anxiety about data encroachment, challenges from bureaucratic procedures and lack of educational awareness, privacy concerns about LMS and social media.The result from this work also illustrates that it would be hard for students to evaluate their privacy risk due to lack of educational opportunity to balance privacy and technologies usage, and the blurred boundaries between LMS and third parties including social media in technology integration.Implications for practice and/or policy The paper identifies how the rapid increase and use of educational technologies have, in many ways, influenced diverse students' personal information and metadata in higher education.The paper makes detail recommendations on how HEIs can address the issue of balancing privacy and technology integration as an essential strategy by providing students assurance of their data security and privacy. [ABSTRACT FROM AUTHOR]

This contribution presents the concept and implementation of a catalog (i.e., a structured collection) of dynamical system models, relevant to control theory. The key features of the catalog are: (a) a combination of human‐readable model documentation with executable code; (b) semantic metadata for each model plus a web platform to provide SPARQL search interface; and (c) model data and supporting software based on open source repositories and open for extension and improvement. [ABSTRACT FROM AUTHOR]

This technical report is aimed at guiding the reporting of data on analytical test results, and related metadata, to EFSA in the context of the activities for the surveillance and monitoring of African Swine Fever. The objective is to explain in detail the individual data elements that are included in the EFSA Standard Sample Description version 2 (SSD2) data model. The guidance is intended to support the reporting countries in data transmission using eXtensible Markup Language (XML) data file transfer through the Data Collection Framework (DCF) according to the protocol described in the EFSA Guidance on Data Exchange version 2 (GDE2). The data elements are explained, including information about data type, list of allowed terms and associated business rules. Instructions about how to report common sampling schemes are also provided to ensure harmonised reporting among countries. [ABSTRACT FROM AUTHOR]

New daily minimum temperature (TN), maximum temperature (TX) and precipitation amount (PPT) database CADTEP (CAtalan Daily TEmperature and Precipitation data set) has been developed for Catalonia, Spain. The source dataset consists of the available climate records from Catalonia provided by the State Meteorology Agency of Spain (AEMET) and the Catalan Meteorological Service (SMC). We selected the long and fairly complete records and created further long series by merging the records of nearby stations. Finally, 26 TN, 26 TX and 72 PPT time series covering the period 1950–2021 have been accepted for CADTEP from the several hundreds of, but mostly much shorter time series. This database has sufficiently dense time series to reach accurate estimates of regional climate variability. CADTEP time series were subjected to thorough quality control and time series homogenization. In the quality control, many shorter series were still in use. Both in quality control and time series homogenization, several series surrounding Catalonia, but close to the borders, were also considered to achieve a higher data accuracy in CADTEP. The homogenization was performed with ACMANTv5.1. In this new version of ACMANT, metadata dates pointing on likely occurrences of nonclimatic changes (breaks) are contemplated in the homogenization as sure break positions. Finally, we examined the trend and variability of TN, TX and PPT over 1950–2021 using CADTEP. Differences between the use of homogenized and raw data, as well as between the inclusion and exclusion of metadata use in the homogenization procedure were controlled. The most important conclusions are related to the trend analysis, namely the speed of the warming of summer TX is faster than in other seasons, faster than the warming of TN in general, and the triple of the mean global warming speed. [ABSTRACT FROM AUTHOR]

Natural language processing techniques can be used to analyze the linguistic content of a document to extract missing pieces of metadata. However, accurate metadata extraction may not depend solely on the linguistics, but also on structural problems such as extremely large documents, unordered multi‐file documents, and inconsistency in manually labeled metadata. In this work, we start from two standard machine learning solutions to extract pieces of metadata from Environmental Impact Statements, environmental policy documents that are regularly produced under the US National Environmental Policy Act of 1969. We present a series of experiments where we evaluate how these standard approaches are affected by different issues derived from real‐world data. We find that metadata extraction can be strongly influenced by nonlinguistic factors such as document length and volume ordering and that the standard machine learning solutions often do not scale well to long documents. We demonstrate how such solutions can be better adapted to these scenarios, and conclude with suggestions for other NLP practitioners cataloging large document collections. [ABSTRACT FROM AUTHOR]

Invasive species threaten native biota, putting fragile ecosystems at risk and having a large‐scale impact on primary industries. Growing trade networks and the popularity of personal travel make incursions a more frequent risk, one only compounded by global climate change. With increasing publication of whole‐genome sequences lies an opportunity for cross‐species assessment of invasive potential. However, the degree to which published sequences are accompanied by satisfactory spatiotemporal data is unclear. We assessed the metadata associated with 199 whole‐genome assemblies of 89 invasive terrestrial invertebrate species and found that only 38% of these were derived from field‐collected samples. Seventy‐six assemblies (38%) reported an ‘undescribed’ sample origin and, while further examination of associated literature closed this gap to 23.6%, an absence of spatial data remained for 47 of the total assemblies. Of the 76 assemblies that were ultimately determined to be field‐collected, associated metadata relevant for invasion studies was predominantly lacking: only 35% (27 assemblies) provided granular location data, and 33% (n = 25) lacked sufficient collection date information. Our results support recent calls for standardized metadata in genome sequencing data submissions, highlighting the impact of missing metadata on current research in invasion biology (and likely other fields). Notably, large‐scale consortia tended to provide the most complete metadata submissions in our analysis—such cross‐institutional collaborations can foster a culture of increased adherence to improved metadata submission standards and a standard of metadata stewardship that enables reuse of genomes in invasion science. [ABSTRACT FROM AUTHOR]

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome‐scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data‐sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever. [ABSTRACT FROM AUTHOR]

Data collection in process industry yields a variety of data types. To maintain the knowledge about the data and to enable finding and reusing them (FAIR data), a common description with metadata is necessary. In the project KEEN, ProMetaS – the Process Engineering/Industry Metadata Schema – was developed. It defines various metadata categories adhering to available metadata standards. In this article, ProMetaS, its implementation into the KEEN data platform, and its application in two use cases is described. [ABSTRACT FROM AUTHOR]

As more and more software teams use online issue tracking systems to collaborate on software projects, the accurate assignment of new issues to the most suitable contributors may have significant impact on the success of the project. As a result, several research efforts have been directed towards automating this process to save considerable time and effort. However, most approaches focus mainly on software bugs and employ models that do not sufficiently take into account the semantics and the non‐textual metadata of issues and/or produce models that may require manual tuning. A methodology that extracts both textual and non‐textual features from different types of issues is designed, providing a Jira dataset that involves not only bugs but also new features, issues related to documentation, patches, etc. Moreover, the semantics of issue text are effectively captured by employing a topic modelling technique that is optimised using the assignment result. Finally, this methodology aggregates probabilities from a set of individual models to provide the final assignment. Upon evaluating this approach in an automated issue assignment setting using a dataset of Jira issues, the authors conclude that it can be effective for automated issue assignment. [ABSTRACT FROM AUTHOR]

This paper focuses on data science in digital cultural heritage in Brazil, where there is a lack of systematized information and curated databases for the integrated organization of documentary knowledge. Thus, the aim was to systematically map the different forms of information organization and representation applied to objects from collections belonging to institutions affiliated with the federal government's Special Department of Culture. This diagnosis is then used to discuss the requirements of devising strategies that favor a better data science information infrastructure to reuse information on Brazil's cultural heritage. Content analysis was used to identify analytical categories and obtain a broader understanding of the documentary sources of these institutions in order to extract, analyze, and interpret the data involved. A total of 215 hyperlinks that can be considered cultural collections of the institutions studied were identified, representing 2,537,921 cultural heritage items. The results show that the online publication of Brazil's digital cultural heritage is limited in terms of technology, copyright licensing, and established information organization practices. This paper provides a conceptual and analytical view to discuss the requirements for formulating strategies aimed at building a data science information infrastructure of Brazilian digital cultural collections that serves as future projects. [ABSTRACT FROM AUTHOR]

The analysis of genomic data can be an intimidating process, particularly for researchers who are not experienced programmers. Commonly used analyses are spread across many programs, each requiring their own specific input formats, and so data must often be repeatedly reorganized and transformed into new formats. Analyses often require splitting data according to metadata variables such as population or family, which can be challenging to manage in large data sets. Here, we introduce snpR, a user‐friendly data analysis package in R for processing SNP genomic data. snpR is designed to automate data subsetting and analyses across categorical metadata while also streamlining repeated analyses by integrating approaches contained in many different packages in a single ecosystem. snpR facilitates iterative and efficient analyses centred on a single R object for an entire analysis pipeline. see also the Perspective by L. Dutoit and G. A. McCulloch [ABSTRACT FROM AUTHOR]

A modular research data management toolbox based on the programming language Python, the widely used computing platform Jupyter Notebook, the standardized data exchange format for analytical data (AnIML) and the generic repository Dataverse has been established and applied to analyze small‐angle X‐ray scattering (SAXS) data according to the FAIR data principles (findable, accessible, interoperable and reusable). The SAS‐tools library is a community‐driven effort to develop tools for data acquisition, analysis, visualization and publishing of SAXS data. Metadata from the experiment and the results of data analysis are stored as an AnIML document using the novel Python‐native pyAnIML API. The AnIML document, measured raw data and plots resulting from the analysis are combined into an archive in OMEX format and uploaded to Dataverse using the novel easyDataverse API, which makes each data set accessible via a unique DOI and searchable via a structured metadata block. SAS‐tools is applied to study the effects of alkyl chain length and counterions on the phase diagrams of alkyltrimethylammonium surfactants in order to demonstrate the feasibility and usefulness of a scalable data management workflow for experiments in physical chemistry. [ABSTRACT FROM AUTHOR]

Knowledge proximity refers to the strength of association between any two entities in a structural form that embodies certain aspects of a knowledge base. In this work, we operationalize knowledge proximity within the context of the US Patent Database (knowledge base) using a knowledge graph (structural form) named "PatNet" built using patent metadata, including citations, inventors, assignees, and domain classifications. We train various graph embedding models using PatNet to obtain the embeddings of entities and relations. The cosine similarity between the corresponding (or transformed) embeddings of entities denotes the knowledge proximity between these. We compare the embedding models in terms of their performances in predicting target entities and explaining domain expansion profiles of inventors and assignees. We then apply the embeddings of the best‐preferred model to associate homogeneous (e.g., patent–patent) and heterogeneous (e.g., inventor–assignee) pairs of entities. [ABSTRACT FROM AUTHOR]

Systematic reviews are vital instruments for researchers to understand broad trends in a field and synthesize evidence on the effectiveness of interventions in addressing specific issues. The quality of a systematic review depends critically on having comprehensively surveyed all relevant literature on the review topic. In addition to database searching, handsearching is an important supplementary technique that helps increase the likelihood of identifying all relevant studies in a literature search. Traditional handsearching requires reviewers to manually browse through a curated list of field‐specific journals and conference proceedings to find articles relevant to the review topic. This manual process is not only time‐consuming, laborious, costly, and error‐prone due to human fatigue, but it also lacks replicability due to its cumbersome manual nature. To address these issues, this paper presents a free and open‐source Python package and an accompanying web‐app, Paperfetcher, to automate the retrieval of article metadata for handsearching. With Paperfetcher's assistance, researchers can retrieve article metadata from designated journals within a specified time frame in just a few clicks. In addition to handsearching, it also incorporates a beta version of citation searching in both forward and backward directions. Paperfetcher has an easy‐to‐use interface, which allows researchers to download the metadata of retrieved studies as a list of DOIs or as an RIS file to facilitate seamless import into systematic review screening software. To the best of our knowledge, Paperfetcher is the first tool to automate handsearching with high usability and a multi‐disciplinary focus. [ABSTRACT FROM AUTHOR]

Background: Digital radiography (DR) still presentsmany challenges and could have complex imaging acquisition and processing patterns in a clinical practice hindering quality standardization. Purpose: This technical note aims to report the 4-year experience with utilizing a custom DICOM metadata analytics program in clinical DR at a large institution. Methods: Thirty-eight DR systems of three vendors at multiple locations were configured to automatically send clinical DICOM images to a DICOM receiver.A suite of custom MATLAB programs was established to extract and store public and private header data weekly. Specific use cases are provided for systematic image acquisition investigation, image processing harmonization, exposure index (EI) longitudinal monitoring and EI target optimization. Results: For systematic acquisition investigation, an example of adult lumbar spine exam analysis was provided with statistics on manual acquisition versus the use of automatic exposure control (AEC, including AEC dose level, active cell, and backup timer), grid usage, and collimation for various projections. For processing harmonization, up to 12.6% of protocols were revealed to have processing parameter differences in an example of a mobile radiography fleet. In addition, inconsistent use of a post-acquisition image size function was also demonstrated, which resulted in anatomy size display variations. Bimonthly monitoring of median EI values showed expected trends, including changes after an AEC dose level adjustment for adult posterior-anterior chest imaging on a scanner system. An example of adult axillary shoulder EI target refinement was shared using the median value, eµ, based on the lognormal EI data distribution after parsing down to acquisitions with appropriate techniques. Conclusions: This analytics program enables systematic analysis of image acquisition and processing details. The information provides invaluable insights into real practice patterns, which can support data-driven quality standardization and optimization. [ABSTRACT FROM AUTHOR]

Aim: Species occurrence records are essential to understanding Earth's biodiversity and addressing global environmental issues, but do not always reflect actual locations of occurrence. Certain geographical coordinates are assigned repeatedly to thousands of observation/collection records. This may result from imperfect data management and georeferencing practices, and can greatly bias the inferred distribution of biodiversity and associated environmental conditions. Nonetheless, these 'biodiverse' coordinates are often overlooked in taxon‐centric studies, as they are identifiable only in aggregate across taxa and datasets, and it is difficult to determine their true circumstance without in‐depth, focused investigation. Here we assess highly recurring coordinates in biodiversity data to determine artificial hotspots of occurrences. Location: Global. Taxon: Land plants, birds, mammals, insects. Methods: We identified highly recurring coordinates across plant, bird, insect and mammal records in the Global Biodiversity Information Facility, the largest aggregator of biodiversity data. We determined which are likely artificial hotspots by examining metadata from over 40 million records, assessing spatial distributions of associated datasets, contacting data managers and reviewing literature. These results were compiled into the Artificial Hotspot Occurrence Inventory (AHOI). Results: Artificial biodiversity hotspots generally comprised geopolitical and grid centroids. The associated uncertainty ranged from several square kilometres to millions. Such artificial biodiversity hotspots were most prevalent in plant records. For instance, over 100,000 plant occurrence records were assigned the centroid coordinates of Brazil, and points that have at least 1000 associated occurrences comprised over 9 million records. In contrast, highly recurring coordinates in animal data more often reflected actual sites of observation. Main conclusions AHOI can be used to (i) improve accuracy of biodiversity assessments; (ii) estimate uncertainty associated with records from artificial hotspots and make informed decisions on whether to include them in scientific studies; and (iii) identify problems in biodiversity informatics workflows and priorities for improvement. [ABSTRACT FROM AUTHOR]

The Kakioka Magnetic Observatory (KMO) of the Japan Meteorological Agency (JMA) made atmospheric electric field observations at Kakioka and Memambetsu beginning in 1929 and 1949, respectively, and ending in February 2021 and December 2010, respectively. The digital numerical data are available on the KMO website, although not all observation periods are covered. In this article, we introduce the available datasets and summarize the metadata regarding the observations, such as measurement instruments, maintenance methods and data processing. [ABSTRACT FROM AUTHOR]

The Kakioka Magnetic Observatory (KMO) of the Japan Meteorological Agency (JMA) made geoelectric field observations at Kakioka, Memambetsu and Kanoya from 1932, 1949 and 1948, respectively, until February 2021, when observations at all three sites were terminated. The digital numerical data are available on the KMO website, although not all observation periods are covered. In this article, we introduce the available datasets and summarize the metadata regarding the observations, such as the electrodes, recording system, maintenance methods and data processing. [ABSTRACT FROM AUTHOR]

Historical materials contain descriptions of various events involved in natural processes and human societies (such as weather, earthquakes, volcanic eruptions, harvests, market prices, and famines). They have been used for studies in diverse fields, including natural sciences (such as seismology, climatology, and astronomy), social sciences, and humanities. Hence, researchers have made various efforts, such as identifying and obtaining the materials, reading handwritten characters and transcribing them into digital texts, standardizing formats, extracting descriptions of relevant phenomena, and constructing integrated datasets, to use documentary information. Because scientists, other than historians, find it quite challenging even to ascertain where to find appropriate research materials, the Rekiske Development Group has, therefore, developed a system called Rekiske to facilitate interdisciplinary sharing of information available from historical materials. Rekiske is designed for sharing bibliographic and scientific information of historical materials, along with researchers' experience and knowledge, through interdisciplinary collaboration. Rekiske can assist researchers in identifying and obtaining useful historical materials for research purposes. It also facilitates collaboration among experts to share their expertise and knowledge of historical information, materials, and recent studies. Using Rekiske, we register various types of information on historical materials regarding weather or earthquakes considered in geoscience research to utilize researchers' experiences and to produce new knowledge through interdisciplinary collaborations. The developed system is designed to be used as a metadata portal and pathfinder to promote and preserve historical data and facilitate an understanding of the spatiotemporal connection between nature and human society. We have applied Rekiske to historical climatic studies and discuss its usage, benefits, usability, and other remaining issues. [ABSTRACT FROM AUTHOR]

The Environmental Data Initiative (EDI) is a trustworthy, stable data repository, and data management support organization for the environmental scientist. In a bottom‐up community process, EDI was built with the premise that freely and easily available data are necessary to advance the understanding of complex environmental processes and change, to improve transparency of research results, and to democratize ecological research. EDI provides tools and support that allow the environmental researcher to easily integrate data publishing into the research workflow. Almost ten years since going into production, we analyze metadata to provide a general description of EDI's collection of data and its data management philosophy and placement in the repository landscape. We discuss how comprehensive metadata and the repository infrastructure lead to highly findable, accessible, interoperable, and reusable (FAIR) data by evaluating compliance with specific community proposed FAIR criteria. Finally, we review measures and patterns of data (re)use, assuring that EDI is fulfilling its stated premise. [ABSTRACT FROM AUTHOR]

The number of smartwatch users has been rapidly increasing in recent years. A smartwatch is a wearable device that collects various types of data using sensors and provides basic functions, such as healthcare‐related measurements and audio recording. In this study, we proposed the forensic authentication method for audio recordings from the Voice Recording application in the Samsung Galaxy Watch4 series. First, a total of 240 audio recordings from each of the four different models, paired with four different smartphones for synchronization via Bluetooth, were collected and verified. To analyze the characteristics of smartwatch audio recordings, we examined the transition of the audio latency, writable audio bandwidth, timestamps, and file structure between those generated in the smartwatches and those edited using the Voice Recording application of the paired smartphones. In addition, the devices with the audio recordings were examined via the Android Debug Bridge (ADB) tool and compared with the timestamps stored in the file system. The experimental results showed that the audio latency, writable audio bandwidth, and file structure of audio recordings generated by smartwatches differed from those generated by smartphones. Additionally, by analyzing the file structure, audio recordings can be classified as unmanipulated, manipulation has been attempted, or manipulated. Finally, we can forensically authenticate the audio recordings generated by the Voice Recorder application in the Samsung Galaxy Watch4 series by accessing the smartwatches and analyzing the timestamps related to the audio recordings in the file system. [ABSTRACT FROM AUTHOR]

This study examines trends in open access article processing charges (APCs) from 2011 to 2021, building on a 2011 study by Solomon and Björk. Two methods are employed, a modified replica and a status update of the 2011 journals. Data are drawn from multiple sources and datasets are available as open data. Most journals do not charge APCs; this has not changed. The global average per‐journal APC increased slightly, from 906 to 958 USD, while the per‐article average increased from 904 to 1,626 USD, indicating that authors choose to publish in more expensive journals. Publisher size, type, impact metrics and subject affect charging tendencies, average APC, and pricing trends. Half the journals from the 2011 sample are no longer listed in DOAJ in 2021, due to ceased publication or publisher de‐listing. Conclusions include a caution about the potential of the APC model to increase costs beyond inflation. The university sector may be the most promising approach to economically sustainable no‐fee OA journals. Universities publish many OA journals, nearly half of OA articles, tend not to charge APCs and when APCs are charged, the prices are very low on average. [ABSTRACT FROM AUTHOR]

An integrated metadata schema was created to promote interoperability and to characterize historically collected geoscience data. The metadata standard describes the steps taken to develop a switching‐across methodology that allows geoscience metadata standards (ISO 19115, CSDGM, ANZLIC and INSPIRE) to communicate with one another. We also demonstrated a real example of one of the switching‐across that was created. A representative metadata schema was created using items from harmonization standards that might be optimally mapped. Semantic interoperability allows users to access equivalent classes across several metadata standards in a uniform and consistent rule. It also tries to provide fundamental aspects that might characterize acquisition information to enhance data reuse and current metadata standards for data preservation and distribution. [ABSTRACT FROM AUTHOR]