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Much of medical knowledge is stored in the biomedical literature, collected in archives like PubMed Central that continue to grow rapidly. A significant part of this knowledge is contained in images with limited metadata available which makes it difficult to explore the visual knowledge in the biomedical literature. Thus, extraction of metadata from visual content is important. One important piece of metadata is the type of the image, which could be one of the various medical imaging modalities such as X‐ray, computed tomography or magnetic resonance images and also of general graphs that are frequent in the literature. This study explores a late, score‐based fusion of several deep convolutional neural networks with a traditional hand‐crafted bag of visual words classifier to classify images from the biomedical literature into image types or modalities. It achieved a classification accuracy of 85.51% on the ImageCLEF 2013 modality classification task, which is better than the best visual methods in the challenge that the data were produced for, and similar compared to mixed methods that make use of both visual and textual information. It achieved similarly good results of 84.23 and 87.04% classification accuracy before and after augmentation, respectively, on the related ImageCLEF 2016 subfigure classification task. [ABSTRACT FROM AUTHOR]

Summary: Modern society depends on the use of many diverse materials. Effectively managing these materials is becoming increasingly important and complex, from the analysis of supply chains, to quantifying their environmental impacts, to understanding future resource availability. Material stocks and flows data enable such analyses, but currently exist mainly as discrete packages, with highly varied type, scope, and structure. These factors constitute a powerful barrier to holistic integration and thus universal analysis of existing and yet to be published material stocks and flows data. We present the Unified Materials Information System (UMIS) to overcome this barrier by enabling material stocks and flows data to be comprehensively integrated across space, time, materials, and data type independent of their disaggregation, without loss of information, and avoiding double counting. UMIS can therefore be applied to structure diverse material stocks and flows data and their metadata across material systems analysis methods such as material flow analysis (MFA), input‐output analysis, and life cycle assessment. UMIS uniquely labels and visualizes processes and flows in UMIS diagrams; therefore, material stocks and flows data visualized in UMIS diagrams can be individually referenced in databases and computational models. Applications of UMIS to restructure existing material stocks and flows data represented by block flow diagrams, system dynamics diagrams, Sankey diagrams, matrices, and derived using the economy‐wide MFA classification system are presented to exemplify use. UMIS advances the capabilities with which complex quantitative material systems analysis, archiving, and computation of material stocks and flows data can be performed. [ABSTRACT FROM AUTHOR]

Accurate forecasting of the arrival time and subsequent geomagnetic impacts of coronal mass ejections (CMEs) at Earth is an important objective for space weather forecasting agencies. Recently, the CME Arrival and Impact working team has made significant progress toward defining community‐agreed metrics and validation methods to assess the current state of CME modeling capabilities. This will allow the community to quantify our current capabilities and track progress in models over time. First, it is crucial that the community focuses on the collection of the necessary metadata for transparency and reproducibility of results. Concerning CME arrival and impact we have identified six different metadata types: 3‐D CME measurement, model description, model input, CME (non)arrival observation, model output data, and metrics and validation methods. Second, the working team has also identified a validation time period, where all events within the following two periods will be considered: 1 January 2011 to 31 December 2012 and January 2015 to 31 December 2015. Those two periods amount to a total of about 100 hit events at Earth and a large amount of misses. Considering a time period will remove any bias in selecting events and the event set will represent a sample set that will not be biased by user selection. Lastly, we have defined the basic metrics and skill scores that the CME Arrival and Impact working team will focus on. Key Points: We have fully defined metadata for CME arrival and impact and showed it is critical for assessmentThe validation event set will not be based on a handpicked set of events, but on two selected time periodsWe have identified metrics for CME arrival time and impact by community consensus [ABSTRACT FROM AUTHOR]

Summary: Big data technologies enable people to store, analyze, and utilize large amounts of complex data effectively. In this context, NoSQL (Not only Structured Query Language) databases have emerged as the most commonly used infrastructure for handling big Resource Description Framework data. In this paper, we present our proposal to materialize classified OWL (Web Ontology Language) ontologies in a NoSQL database. This materialization process enables the distributed storage of Resource Description Framework data by exploiting the inherent distribution of the NoSQL database nodes. Furthermore, this approach supposes the first step toward a novel approach to scalable OWL reasoning, which enables scalable Linked Data reasoning. To validate our proposal, we developed a prototype for a tool that stores an OWL ontology in a Cassandra database following our approach. Finally, we introduce our reasoning strategy to compute the ontology closure using this Cassandra database. [ABSTRACT FROM AUTHOR]

publisher‐imprint‐name Springer volume‐issue‐count 1 issue‐article‐count 0 issue‐toc‐levels 0 issue‐pricelist‐year 2018 issue‐copyright‐holder The Author(s) issue‐copyright‐year 2018 article‐contains‐esm No article‐numbering‐style Unnumbered article‐registration‐date‐year 2018 article‐registration‐date‐month 7 article‐registration‐date‐day 20 article‐toc‐levels 0 toc‐levels 0 volume‐type Regular journal‐product ArchiveJournal numbering‐style Unnumbered article‐grants‐type OpenChoice metadata‐grant OpenAccess abstract‐grant OpenAccess bodypdf‐grant OpenAccess bodyhtml‐grant OpenAccess bibliography‐grant OpenAccess esm‐grant OpenAccess online‐first false pdf‐file‐reference BodyRef/PDF/40169_2018_Article_205.pdf target‐type OnlinePDF issue‐type Regular article‐type ReviewPaper journal‐subject‐primary Medicine & Public Health journal‐subject‐secondary Medicine/Public Health, general journal‐subject‐collection Medicine --> Chemotherapy resistance of breast cancer poses a great challenge to the survival of patients. During breast cancer treatment, the development of intrinsic and acquired drug resistance tends to further induce adverse prognosis, such as metastasis. In recent years, the progress of research on cytokine‐modulated tumor microenvironment and breast cancer stem cells (BCSCs) has shed light on defining the mechanisms of drug resistance gradually. In this review, we have discussed cytokine regulation on breast cancer chemoresistance. Cytokines can affect tumor cell behavior or reprogram tumor niche through specific signaling pathways, thereby regulating the progress of drug resistance. In addition, we summarized the mutually regulatory networks between cytokines and BCSCs in mediating chemoresistance. Cytokines in the tumor microenvironment can regulate the self‐renewal and survival of BCSCs in a variety of ways, sequentially promoting chemotherapeutic resistance. Therefore, the combinational treatment of BCSC targeting and cytokine blockade may have a positive effect on the clinical treatment of breast cancer. [ABSTRACT FROM AUTHOR]

publisher‐imprint‐name Springer volume‐issue‐count 1 issue‐article‐count 0 issue‐toc‐levels 0 issue‐pricelist‐year 2018 issue‐copyright‐holder The Author(s) issue‐copyright‐year 2018 article‐contains‐esm No article‐numbering‐style Unnumbered article‐registration‐date‐year 2018 article‐registration‐date‐month 10 article‐registration‐date‐day 1 article‐toc‐levels 0 toc‐levels 0 volume‐type Regular journal‐product ArchiveJournal numbering‐style Unnumbered article‐grants‐type OpenChoice metadata‐grant OpenAccess abstract‐grant OpenAccess bodypdf‐grant OpenAccess bodyhtml‐grant OpenAccess bibliography‐grant OpenAccess esm‐grant OpenAccess online‐first false pdf‐file‐reference BodyRef/PDF/40169_2018_Article_211.pdf target‐type OnlinePDF issue‐type Regular article‐type ReviewPaper journal‐subject‐primary Medicine & Public Health journal‐subject‐secondary Medicine/Public Health, general journal‐subject‐collection Medicine --> Combination therapy is increasingly becoming the cornerstone of current day antitumor therapy. Glioblastoma multiforme is an aggressive brain tumor with a dismal median survival post diagnosis and a high rate of disease recurrence. The poor prognosis can be attributed to unique treatment limitations, which include the infiltrative nature of tumor cells, failure of anti‐glioma drugs to cross the blood–brain barrier, tumor heterogeneity and the highly metastatic and angiogenic nature of the tumor making cells resistant to chemotherapy. Combination therapy approach is being developed against glioblastoma with new innovative combination drug regimens being tested in preclinical and clinical trials. In this review, we discuss the pathophysiology of glioblastoma, diagnostic markers, therapeutic targeting strategies, current treatment limitations, novel combination therapies in the context of current treatment options and the ongoing clinical trials for glioblastoma therapy. [ABSTRACT FROM AUTHOR]

publisher‐imprint‐name Springer volume‐issue‐count 1 issue‐article‐count 0 issue‐toc‐levels 0 issue‐pricelist‐year 2018 issue‐copyright‐holder The Author(s) issue‐copyright‐year 2018 article‐contains‐esm No article‐numbering‐style Unnumbered article‐registration‐date‐year 2018 article‐registration‐date‐month 7 article‐registration‐date‐day 2 article‐toc‐levels 0 toc‐levels 0 volume‐type Regular journal‐product ArchiveJournal numbering‐style Unnumbered article‐grants‐type OpenChoice metadata‐grant OpenAccess abstract‐grant OpenAccess bodypdf‐grant OpenAccess bodyhtml‐grant OpenAccess bibliography‐grant OpenAccess esm‐grant OpenAccess online‐first false pdf‐file‐reference BodyRef/PDF/40169_2018_Article_200.pdf target‐type OnlinePDF issue‐type Regular article‐type OriginalPaper journal‐subject‐primary Medicine & Public Health journal‐subject‐secondary Medicine/Public Health, general journal‐subject‐collection Medicine --> Background: Purpose of this study is to investigate the presence and frequency of post‐traumatic stress disorder (PTSD) symptoms in post‐concussed (PC) athletes compared to a group of healthy control (HC) athletes. Research design and method: A pre and post‐test group design was used to compare a post‐concussed group to a matched healthy control group of athletes. An archival database which included PC (n = 62) and HC (n = 62) participants matched on age, years of education and gender who completed a test battery at baseline and post injury, The test battery was comprised of a neurocognitive assessment, self‐reported symptom inventory and PTSD symptom questionnaire. Post‐concussion assessment was obtained within 0–13 days post‐injury. Results: PTSD symptom scores were greater in PC post injury group (Mdn = 0) than for the HC group (Mdn = 0.0), U = 1282.0, p = 0.000, r = 0.34. A Wilcoxon Signed‐ranks test indicated that PTSD symptom scores post‐injury (Mdn = 0) were significantly higher than pre‐injury (Mdn = 0), Z = − 2.75, p = 0.000, r = 0.35. Within the PC post injury group athletes having "difficulty sleeping" was the highest reported symptom an average of 25.8% followed by "avoiding similar situations" at an average of 19.4%. "Having trouble keeping thoughts of incident out of your head" was reported at an average of 17.7% and "flashbacks" were reported at an average of 12.9%. "Nightmares" and "feeling numb and detached" were reported at an average of 8.1 and 6.5% respectively. Conclusion: Athletes who reported no PTSD symptoms prior to sports related concussion do exhibit symptoms of PTSD. Providing a PTSD symptom questionnaire may provide a more comprehensive treatment plan for PC post injury athletes who may be at risk of chronic PTSD symptoms. [ABSTRACT FROM AUTHOR]

Digitization provides a solution for documentation and preservation of nonmovable cultural heritages. Despite efforts for the preservation of cultural heritages around the world, no well‐accepted metadata schema has been developed for murals and stone cave temples, which are often high‐value heritages built in ancient times. In addition, the literature is scarce on the user‐centered evaluation of metadata schemas of this kind. This study therefore aims to offer insights on developing and evaluating a metadata schema for organizing information of these historic and complex cultural heritages. In‐depth interviews were conducted with a total of 30 users, including 18 professional and 12 public users, and interview transcripts were coded through a qualitative content analysis approach. Findings reveal the importance of specific metadata elements as perceived by the two groups of end users, which correlated with their cultural heritage information‐seeking behaviors. In addition, the issues of standardization of cataloging of cultural heritage information and interoperability among metadata schemas have been raised by users for enhancing the user experience with digital platforms of cultural heritage information. The coding schema developed in this study can serve as a framework for follow‐up evaluations of metadata schemas, contributing to the ongoing development of cultural heritage metadata. [ABSTRACT FROM AUTHOR]

In this report, we describe the initial stages of a crosscutting research effort to characterize literature reviewed across 8 different projects—each with objectives aligned toward improving student engagement in science, technology, engineering, arts, and mathematics (STEAM) fields. These projects sought to identify malleable factors (e.g., motivation, persistence) that could potentially be fostered to improve achievement motivation and build participation among historically underrepresented learners in STEAM pathways. Focusing on both the extent to which different broad and facet‐level constructs are both discussed and assessed in a diverse pool of literature, we developed a standardized reporting structure and catalogued detailed information on 236 unique references. We found that, as a proportion of the number of times constructs in the STEAM, expectancy value (EV) theory, and social emotional learning (SEL) spaces were discussed in the reviewed literature, they were assessed relatively infrequently. We also found high levels of overlap in the literature across the above 3 focal areas, highlighting both the need to document new assessments designed to support STEAM engagement and an opportunity to use them to evaluate expectancy value theory as a holistic model. Report Number: ETS RR–18‐33 [ABSTRACT FROM AUTHOR]

The Space Physics Archive Search and Extract Consortium has developed and implemented the SPASE Data Model that provides a common language for registering a wide range of Heliophysics data and other products. The Data Model enables discovery and access tools such that any researcher can obtain data easily, thereby facilitating research, including on space weather. The Data Model includes descriptions of Simulation Models and Numerical Output, pioneered by the Integrated Medium for Planetary Exploration (IMPEx) group in Europe, and subsequently adopted by the Community Coordinated Modeling Center (CCMC). The SPASE group intends to register all relevant Heliophysics data resources, including space‐, ground‐, and model‐based. Substantial progress has been made, especially for space‐based observational data and associated observatories, instruments, and display data. Legacy product registrations and access go back more than 50 years. Real‐time data will be included. The National Aeronautics and Space Administration (NASA) portion of the SPASE group has funding that assures continuity in the upkeep of the Data Model and aids with adding new products. Tools are being developed for making and editing data descriptions. Digital Object Identifiers (DOIs) for Data Products can now be included in the descriptions. The data access that SPASE facilitates is becoming more uniform, and work is progressing on Web Service access via a standard Application Programming Interface. The SPASE Data Model is stable; changes over the past 9 years were additions of terms and capabilities that are backward compatible. This paper provides a summary of the history, structure, use, and future of the SPASE Data Model. Plain Language Summary: The Heliophysics research community requires a wide variety of data from many disparate sources in order to make substantial progress. This is especially true for space weather, where a range of data and models may be relevant to any given study. The SPASE Data Model" unifies descriptions of data from observatories or simulation models using the same language to describe all products. This streamlines finding, accessing, and using the underlying variegated files, thus speeding up and improving research. This paper gives an overview of the history, structure, and use of the SPASE Data Model and gives an idea of current directions in its development. Key Points: The Heliophysics/Space Weather community has developed a general means to register, discover, access, and use data sets and other productsThe key for ease‐of‐use is the adoption of standards for data formats, metadata, and access methodsThe Space Physics Archive Search and Extract Data Model provides a stable and general standard for the requisite metadata descriptions [ABSTRACT FROM AUTHOR]

Improving technology and increasing affordability mean that camera trapping—the use of remotely triggered cameras to photograph wildlife—is becoming an increasingly common tool in the monitoring and conservation of wild populations. Each camera trap study generates a vast amount of data, which need to be processed and labeled before analysis. Traditionally, processing camera trap data has been performed manually by entering data into a spreadsheet. This is time‐consuming, prone to human error, and data management may be inconsistent between projects, hindering collaboration. Recently, several programs have become available to facilitate and quicken data processing. Here, we review available software and assess their ability to better standardize camera trap data management and facilitate data sharing and collaboration. To identify available software for camera trap data management, we used internet searches and contacted researchers and practitioners working on large camera trap projects, as well as software developers. We tested all available programs against a range of software characteristics in addition to their ability to record a suite of important data variables extracted from images. We identified and reviewed 12 available programs for the management of camera trap data. These ranged from simple software assisting with the extraction of metadata from an image, through to comprehensive programs that facilitate data entry and analysis. Many of the programs tested were developed for use on specific studies and so do not cover all possible software or data collection requirements that different projects may have. We highlight the importance of a standardized software solution for camera trap data management. This approach would allow all possible data to be collected, enabling researchers to share data and contribute to other studies, as well as facilitating multi‐project comparisons. By standardizing camera trap data collection and management in this way, future studies would be better placed to guide conservation policy on a global level. The use of camera traps in ecology and conservation is increasingly common, and studies using camera traps can generate masses of data. These data are often handled and stored differently, hindering comparison and collaboration. We reviewed 12 camera trap data management programs and advise that that a universal approach to managing, storing, and analzsing camera trap data will facilitate collaborations and the sharing of data and will be beneficial to global conservation. [ABSTRACT FROM AUTHOR]

The design and running of complex geoprocessing workflows is an increasingly common geospatial modelling and analysis task. The Business Process Model and Notation (BPMN) standard, which provides a graphical representation of a workflow, allows stakeholders to discuss the scientific conceptual approach behind this modelling while also defining a machine‐readable encoding in XML. Previous research has enabled the orchestration of Open Geospatial Consortium Web Processing Services (WPS) with a BPMN workflow engine. However, the need for direct access to predefined data inputs and outputs results in a lack of flexibility during composition of the workflow and of efficiency during execution. This article develops metadata profiling approaches, described as two possible configurations, which enable workflow management at the meta‐level through a coupling with a metadata catalogue. Specifically, a WPS profile and a BPMN profile are developed and tested using open‐source components to achieve this coupling. A case study in the context of an event mapping task applied within a big data framework and based on analysis of the Global Database of Event Language and Tone database illustrates the two different architectures. [ABSTRACT FROM AUTHOR]

A comprehensive record of research data provenance is essential for the successful curation, management, and reuse of data over time. However, creating such detailed metadata can be onerous, and there are few structured methods for doing so. In this case study of data curation in support of geobiology research conducted at Yellowstone National Park, we describe a method of “Research Process Modeling” for documenting noncomputational data provenance in a structured yet flexible way. The method combines systems analysis techniques to model research activities, the World Wide Web Consortium Provenance (PROV) ontology to illustrate relationships between data products, and simple inventory methods to account for research processes and data products. It also supports collaborative data curation between information professionals and researchers, and is therefore a significant step toward producing more useable and interpretable research data. We demonstrate how this method describes data provenance more robustly than “flat” metadata alone and fills a critical gap in the documentation of provenance for field‐based and noncomputational workflows. We discuss potential applications of this approach to other research domains. [ABSTRACT FROM AUTHOR]

Data sharing and documentation provide modern ecologists with a connection to the mythic Naturalist. In addition to describing data collection and synthesis, the data paper and its dataset/metadata provide characterizations of study sites, species, and phenomena. Data papers, along with their corresponding datasets and metadata, are crucial ecology manuscripts that - collectively - quantify descriptions of natural processes. [Extracted from the article]

This suggests that data ethics need to be included in the required study for Data Science along with machine learning, data wrangling, and linear algebra. We also note that *big* data is a moving target and that, perhaps, complexity of the data is the real story that data scientists now tackle. As a science, we believe that Data Science relates to accumulating knowledge about data and its uses (cf. [Extracted from the article]

One of the main challenges in medical image retrieval is the increasing volume of image data, which render it difficult for domain experts to find relevant information from large data sets. Effective and efficient medical image retrieval systems are required to better manage medical image information. Text‐based image retrieval (TBIR) was very successful in retrieving images with textual descriptions. Several TBIR approaches rely on models based on bag‐of‐words approaches, in which the image retrieval problem turns into one of standard text‐based information retrieval; where the meanings and values of specific medical entities in the text and metadata are ignored in the image representation and retrieval process. However, we believe that TBIR should extract specific medical entities and terms and then exploit these elements to achieve better image retrieval results. Therefore, we propose a novel reranking method based on medical‐image‐dependent features. These features are manually selected by a medical expert from imaging modalities and medical terminology. First, we represent queries and images using only medical‐image‐dependent features such as image modality and image scale. Second, we exploit the defined features in a new reranking method for medical image retrieval. Our motivation is the large influence of image modality in medical image retrieval and its impact on image‐relevance scores. To evaluate our approach, we performed a series of experiments on the medical ImageCLEF data sets from 2009 to 2013. The BM25 model, a language model, and an image‐relevance feedback model are used as baselines to evaluate our approach. The experimental results show that compared to the BM25 model, the proposed model significantly enhances image retrieval performance. We also compared our approach with other state‐of‐the‐art approaches and show that our approach performs comparably to those of the top three runs in the official ImageCLEF competition. [ABSTRACT FROM AUTHOR]

Abstract: DNA‐based techniques are increasingly used for measuring the biodiversity (species presence, identity, abundance and community composition) of terrestrial and aquatic ecosystems. While there are numerous reviews of molecular methods and bioinformatic steps, there has been little consideration of the methods used to collect samples upon which these later steps are based. This represents a critical knowledge gap, as methodologically sound field sampling is the foundation for subsequent analyses. We reviewed field sampling methods used for metabarcoding studies of both terrestrial and freshwater ecosystem biodiversity over a nearly three‐year period (n = 75). We found that 95% (n = 71) of these studies used subjective sampling methods and inappropriate field methods and/or failed to provide critical methodological information. It would be possible for researchers to replicate only 5% of the metabarcoding studies in our sample, a poorer level of reproducibility than for ecological studies in general. Our findings suggest greater attention to field sampling methods, and reporting is necessary in eDNA‐based studies of biodiversity to ensure robust outcomes and future reproducibility. Methods must be fully and accurately reported, and protocols developed that minimize subjectivity. Standardization of sampling protocols would be one way to help to improve reproducibility and have additional benefits in allowing compilation and comparison of data from across studies. [ABSTRACT FROM AUTHOR]

Social media datasets are not always completely replicable. Having to adhere to requirements of platforms such as Twitter, researchers can only release a list of unique identifiers, which others can then use to recollect the data themselves. This leads to subsets of the data no longer being available, as content can be deleted or user accounts deactivated. To quantify the long‐term impact of this in the replicability of datasets, we perform a longitudinal analysis of the persistence of 30 Twitter datasets, which include more than 147 million tweets. By recollecting Twitter datasets ranging from 0 to 4 years old by using the tweet IDs, we look at four different factors quantifying the extent to which recollected datasets resemble original ones: completeness, representativity, similarity, and changingness. Although the ratio of available tweets keeps decreasing as the dataset gets older, we find that the textual content of the recollected subset is still largely representative of the original dataset. The representativity of the metadata, however, keeps fading over time, both because the dataset shrinks and because certain metadata, such as the users' number of followers, keeps changing. Our study has important implications for researchers sharing and using publicly shared Twitter datasets in their research. [ABSTRACT FROM AUTHOR]

Key points Increasing pressure from funders to enable tracking of research outputs that result from their funding is driving the adoption of the ORCID iD. Developers of submission and peer‐review systems have built tools to gather and authenticate ORCID iDs from authors during manuscript submission. Crossref Auto‐update of author ORCID records requires authenticated iDs, but many publishers generate Crossref metadata XML from the author manuscript. eXtyles ORCID Integration Suite allows automated reconciliation and synchronization between the submission system's transmittal file and the author manuscript. [ABSTRACT FROM AUTHOR]

Abstract: Open data has a profound effect on the working environment within which information is created and shared at all levels. At the local government level, open data initiatives have resulted in higher transparency in policy, a greater engagement between decision‐makers and citizens, and have changed the culture about how data analysis and evidence are used to support local governance. This article, based on data collected through an on‐line survey, participatory workshops with data user communities in four cities (in Colombia and Spain), and interviews with Valencia good‐government office, identifies four elements for a conceptual framework to improve the re‐usability of open geographic data in cities. The essential elements defined in this research are the definition of data user communities and their needs, the creation of the community of reuse, user‐focused metadata, and reuse‐focused legal terms. The definition of these indicators provides a framework for authorities to re‐shape their current open data strategy to include data user requirements. At the end of this article, a roadmap for future research and implementation is presented, considering some reflections on the conceptual framework. [ABSTRACT FROM AUTHOR]

Summary: High‐throughput sequencing (HTS) surveys, among the most common approaches currently used in environmental microbiology, require reliable reference databases to be correctly interpreted. The EukRef Initiative (eukref.org) is a community effort to manually screen available small subunit (SSU) rRNA gene sequences and produce a public, high‐quality and informative framework of phylogeny‐based taxonomic annotations. In the context of EukRef, we present a database for the monophyletic phylum Ciliophora, one of the most complex, diverse and ubiquitous protist groups. We retrieved more than 11 500 sequences of ciliates present in GenBank (28% from identified isolates and 72% from environmental surveys). Our approach included the inference of phylogenetic trees for every ciliate lineage and produced the largest SSU rRNA tree of the phylum Ciliophora to date. We flagged approximately 750 chimeric or low‐quality sequences, improved the classification of 70% of GenBank entries and enriched environmental and literature metadata by 30%. The performance of EukRef‐Ciliophora is superior to the current SILVA database in classifying HTS reads from a global marine survey. Comprehensive outputs are publicly available to make the new tool a useful guide for non‐specialists and a quick reference for experts. [ABSTRACT FROM AUTHOR]

Person detection from vehicles hasmade rapid progress recentlywith the advent ofmultiple highquality datasets of urban and highway driving, yet no large-scale benchmark is available for the same problem in off-road or agricultural environments. Here we present the National Robotics EngineeringCenter (NREC)Agricultural Person-DetectionDataset to spur research in these environments. It consists of labeled stereo video of people in orange and apple orchards taken from two perception platforms (a tractor and a pickup truck), along with vehicle position data from Real Time Kinetic (RTK) GPS. We define a benchmark on part of the dataset that combines a total of 76k labeled person images and 19k sampled person-free images. The dataset highlights several key challenges of the domain, including varying environment, substantial occlusion by vegetation, people in motion and in nonstandard poses, and people seen from a variety of distances; metadata are included to allow targeted evaluation of each of these effects. Finally,we present baseline detection performance results for three leading approaches from urban pedestrian detection and our own convolutional neural network approach that benefits from the incorporation of additional image context.We show that the success of existing approaches on urban data does not transfer directly to this domain. [ABSTRACT FROM AUTHOR]

An institutional repository (IR) is a system for archiving digital research outputs such as scholarly papers. While using this system is a simple way to return the benefits of academic research to society, the number of papers currently archived in institutional repositories across the world is very small. We have, therefore, developed a system that can increase the number of papers archived in institutional repositories. The main aim of this system is to reduce the workload of researchers and librarians in paper registration for an IR by using external databases. As a result of our trial implementation and evaluation of the system, we found that its application resulted in a fourfold increase in the number of papers registered in a month without decreasing the working efficiency of the participating librarians. Moreover, by analyzing the log data for the system's implementation, we have acquired further knowledge related to researchers who need librarians' support in paper registration with an IR. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

X‐ray photoelectron spectroscopy (XPS) is a widely used surface analysis technique employed in fundamental research, applied research, service laboratories, and industry. Good‐quality analytical outcomes depend critically on spectral references. Many examples of XPS reference databases exist, including print editions, sets of spectral peak positions drawn from the literature, and digital archives and libraries. We report the development of a new digital XPS database comprising survey spectra and region spectra for a range of materials types, collected under a common set of analytical conditions. Each material is described using spectra collected at multiple pass energies with all photoelectron and X‐ray induced Auger transitions represented. Detailed metadata are provided for each material and each spectrum, presented using a schema that incorporates the ISO 16243 and 14976 standards and extensions developed in this work. Spectra are shared under a Creative Commons International (4.0) attribution, non‐commercial licence (CC BY‐NC) in Kratos (.dset), VAMAS (.vms), and XML (.xml) formats. It is intended that reference spectra be imported directly into XPS data analysis software packages for reference and comparison purposes, matching either the peak or transition of interest and the instrument pass energy. The database is flexible and scalable in structure and has the potential to become a core XPS reference resource. [ABSTRACT FROM AUTHOR]

Abstract: Research on the division of cognitive labor has found that adults and children as young as age 5 are able to find appropriate experts for different causal systems. However, little work has explored how children and adults decide when to seek out expert knowledge in the first place. We propose that children and adults rely (in part) on “mechanism metadata,” information about mechanism information. We argue that mechanism metadata is relatively consistent across individuals exposed to similar amounts of mechanism information, and it is applicable to a wide range of causal systems. In three experiments, we show that adults and children as young as 5 years of age have a consistent sense of the causal complexity of different causal systems, and that this sense of complexity is related to decisions about when to seek expert knowledge, but over development there is a shift in focus from procedural information to internal mechanism information. [ABSTRACT FROM AUTHOR]

Abstract: Measurements of morphological features are important for ecological studies, especially on free‐ranging wild animal species. Conventionally, specimens either dead or in captivity are used for morphometric studies, which is difficult in the case of wild species for several reasons. Capturing would be even futile when research questions are relating to issues such as prey size selection or estimation of intake rate under field conditions, where in situ morphometric measurements are inevitable. Remotely estimating morphometric features via, avian bill and head lengths are always laden with wide variances. Hence, we developed this technique for in situ measurements of animal morphology through digital photographs. This non‐invasive novel method for in situ estimation of individuals’ morphometric measurements uses digital photographs’ metadata. We extracted the metadata (field of view, focal length, subject‐distance, etc.,) in exchangeable image file format from digital images using freely available software, and the unknown sizes were estimated from each image. Cardboard (fish) models were, at first, used to estimate the accuracy of measurements comparing actual and estimated values, and the same protocol was repeated on museum specimens (bird). Finally, we checked the repeatability of this method under field conditions using free‐ranging Chickens (Gallus gallus domesticus). The results under different conditions were subjected to rigorous statistical testing. Upon comparing the actual with estimated values, obtained from three distinct types of objects (1. Cardboard model, 2. Museum specimens and 3. Live birds under field conditions), variations were found non‐significant affirming the assumption that actual value (Y) = estimated value (X) with inconsequential variance of the Y from X. Moreover, both the relative and absolute errors between the actual and estimated values were so low, indicating that this method yielded neither overestimation nor underestimation. The advantage of this non‐invasive method is that it could generate reasonably accurate morphometric measurements at a relatively low cost for routine morphometric works in field conditions. We envisage significant utility of this non‐invasive technique in different fields of science such as biology, morphology, ecology, evolution, wildlife, conservation science, agriculture, forensics and engineering design. [ABSTRACT FROM AUTHOR]

Abstract: There is a dearth of good toolkits to manage the different data formats that are associated with ecological datasets. In this paper, we describe a flexible, general‐purpose, easy‐to‐use, extensible, and open‐source toolkit that was built to manage an ecological study involving thousands of camera trap videos. ViXeN, the software package described here, can be used to view data files, including videos, images, audio files, portable document format (PDF) files, and text, in multiple formats. It can be used to annotate these data files, using metadata in the form of arbitrary user tags. The multimedia data catalogued, archived and extracted, using this software can easily be exported as a comma separated value file that can directly be used for data analysis. The software is capable of handling large datasets with up to a million files. Furthermore, ViXeN provides the option of additional customization by advanced users based on their particular requirements. We provide a case study involving more than 6,000 videos that were collected as part of a camera trap study involving mammalian carnivores to demonstrate some of the functionality of the software. [ABSTRACT FROM AUTHOR]

Cybersecurity is one of the main concerns of many organizations today, and accessibility to cybersecurity information in a timely manner is crucial to maintaining cybersecurity. Various repositories of cybersecurity-related information are publicly available on the Internet. However, users are unaware of many of them, and it is impractical for them to keep track of all of them. Cybersecurity information stored in these repositories must be able to be located and accessed by the parties who need it. To address this issue, this paper proposes a mechanism of linking, locating, and discovering various cybersecurity information to improve its accessibility in a timely manner. This mechanism allows us to locate various cybersecurity information having different schemata by generating metadata with which a list of cybersecurity information is managed. The information structure incorporated in this mechanism is unique, and it makes our mechanism flexible and extensible. The structure consists of categories and formats that are linked to each other. The mechanism can propagate information updates to minimize the risk of obsolete information. This paper also introduces a prototype of the mechanism to demonstrate its feasibility, and it analyzes the mechanism's extensibility, scalability, and information credibility. Through this study, we aim to improve the accessibility of cybersecurity information on the Internet and facilitate information sharing beyond organizational borders, with the eventual goal of creating a web of cybersecurity. [ABSTRACT FROM AUTHOR]

ABSTRACT: Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a ‘Big Data’ approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence‐only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi‐source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter‐ or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi‐source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA‐based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals. [ABSTRACT FROM AUTHOR]

We describe the intellectual and physical properties of books as manifestations, expressions, and works and assess the current indexing and metadata structure of monographs in the Book Citation Index (BKCI). Our focus is on the interrelationship of these properties in light of the Functional Requirements for Bibliographic Records (FRBR). Data pertaining to monographs were collected from the Danish PURE repository system as well as the BKCI (2005-2015) via their International Standard Book Numbers (ISBNs). Each ISBN was then matched to the same ISBN and family-related ISBNs cataloged in two additional databases: OCLC-WorldCat and Goodreads. With the retrieval of all family-related ISBNs, we were able to determine the number of monograph expressions present in the BKCI and their collective relationship to one work. Our results show that the majority of missing expressions from the BKCI are emblematic (i.e., first editions of monographs) and that both the indexing and metadata structure of this commercial database could significantly improve with the introduction of distinct expression IDs (i.e., for every distinct edition) and unifying work-related IDs. This improved metadata structure would support the collection of more accurate publication and citation counts for monographs and has implications for developing new indicators based on bibliographic levels. [ABSTRACT FROM AUTHOR]

Citations are the cornerstone of knowledge propagation and the primary means of assessing the quality of research, as well as directing investments in science. Science is increasingly becoming "data-intensive," where large volumes of data are collected and analyzed to discover complex patterns through simulations and experiments, and most scientific reference works have been replaced by online curated data sets. Yet, given a data set, there is no quantitative, consistent, and established way of knowing how it has been used over time, who contributed to its curation, what results have been yielded, or what value it has. The development of a theory and practice of data citation is fundamental for considering data as first-class research objects with the same relevance and centrality of traditional scientific products. Many works in recent years have discussed data citation from different viewpoints: illustrating why data citation is needed, defining the principles and outlining recommendations for data citation systems, and providing computational methods for addressing specific issues of data citation. The current panorama is many-faceted and an overall view that brings together diverse aspects of this topic is still missing. Therefore, this paper aims to describe the lay of the land for data citation, both from the theoretical (the why and what) and the practical (the how) angle. [ABSTRACT FROM AUTHOR]

The information sciences have traditionally been at the center of metadata-focused research. The US National Security Agency (NSA) intelligence documents revealed by Edward Snowden in June of 2013 brought the term "metadata" into the public consciousness. Surprisingly little discussion in the information sciences has since occurred on the nature and importance of metadata within networked communication systems. The collection of digital metadata impacts the ways that people experience social and technical communication. Without such metadata, networked communication cannot exist. The NSA leaks, and numerous recent hacks of corporate and government communications, point to metadata as objects of new scholarly inquiry. If we are to engage in meaningful discussions about our digital traces, or make informed decisions about new policies and technologies, it is essential to develop theoretical and empirical frameworks that account for digital metadata. This opinion paper presents 5 key sociotechnical characteristics of metadata within digital networks that would benefit from stronger engagement by the information sciences. [ABSTRACT FROM AUTHOR]

One way to facilitate Multilingual Information Access (MLIA) for digital libraries is to generate multilingual metadata records by applying Machine Translation (MT) techniques. Current online MT services are available and affordable, but are not always effective for creating multilingual metadata records. In this study, we implemented 3 different MT strategies and evaluated their performance when translating English metadata records to Chinese and Spanish. These strategies included combining MT results from 3 online MT systems (Google, Bing, and Yahoo!) with and without additional linguistic resources, such as manually-generated parallel corpora, and metadata records in the two target languages obtained from international partners. The opensource statistical MT platform Moses was applied to design and implement the three translation strategies. Human evaluation of the MT results using adequacy and fluency demonstrated that two of the strategies produced higher quality translations than individual online MT systems for both languages. Especially, adding small, manuallygenerated parallel corpora of metadata records significantly improved translation performance. Our study suggested an effective and efficient MT approach for providing multilingual services for digital collections. [ABSTRACT FROM AUTHOR]

Digital repositories must periodically check the integrity of stored objects to assure users of their correctness. Prior solutions calculate integrity metadata and require the repository to store it alongside the actual data objects. To safeguard and detect damage to this metadata, prior solutions rely on widely visible media (unaffiliated third parties) to store and provide back digests of the metadata to verify it is intact. However, they do not address recovery of the integrity metadata in case of damage or adversarial attack. We introduce IntegrityCatalog, a novel software system that can be integrated into any digital repository. It collects all integrity-related metadata in a single component and treats them as first class objects, managing both their integrity and their preservation. We introduce a treap-based persistent authenticated dictionary managing arbitrary length key/value pairs, which we use to store all integrity metadata, accessible simply by object name. Additionally, IntegrityCatalog is a distributed system that includes a network protocol that manages both corruption detection and preservation of this metadata, using administrator-selected network peers with 2 possible roles. Verifiers store and offer attestations on digests and have minimal storage requirements, while preservers efficiently synchronize a complete copy of the catalog to assist in recovery in case of a detected catalog compromise on the local system. We present our approach in developing the prototype implementation, measure its performance experimentally, and demonstrate its effectiveness in real-world situations. We believe the implementation techniques of our open-source IntegrityCatalog will be useful in the construction of next-generation digital repositories. [ABSTRACT FROM AUTHOR]

The Protein Data Bank (PDB) is one of two archival resources for experimental data central to biomedical research and education worldwide (the other key Primary Data Archive in biology being the International Nucleotide Sequence Database Collaboration). The PDB currently houses >134,000 atomic level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. It was established in 1971 as the first open-access, digital-data resource in biology, and is managed by the Worldwide Protein Data Bank partnership (wwPDB; wwpdb.org). US PDB operations are conducted by the RCSB Protein Data Bank (RCSB PDB; RCSB.org; Rutgers University and UC San Diego) and funded by NSF, NIH, and DoE. The RCSB PDB serves as the global Archive Keeper for the wwPDB. During calendar 2016, >591 million structure data files were downloaded from the PDB by Data Consumers working in every sovereign nation recognized by the United Nations. During this same period, the RCSB PDB processed >5300 new atomic level biomolecular structures plus experimental data and metadata coming into the archive from Data Depositors working in the Americas and Oceania. In addition, RCSB PDB served >1 million RCSB.org users worldwide with PDB data integrated with ∼40 external data resources providing rich structural views of fundamental biology, biomedicine, and energy sciences, and >600,000 PDB101.rcsb.org educational website users around the globe. RCSB PDB resources are described in detail together with metrics documenting the impact of access to PDB data on basic and applied research, clinical medicine, education, and the economy. [ABSTRACT FROM AUTHOR]

publisher‐imprint‐name Springer volume‐issue‐count 1 issue‐article‐count 0 issue‐toc‐levels 0 issue‐pricelist‐year 2017 issue‐copyright‐holder The Author(s) issue‐copyright‐year 2017 article‐contains‐esm No article‐numbering‐style Unnumbered article‐registration‐date‐year 2017 article‐registration‐date‐month 10 article‐registration‐date‐day 19 article‐toc‐levels 0 toc‐levels 0 volume‐type Regular journal‐product ArchiveJournal numbering‐style Unnumbered article‐grants‐type OpenChoice metadata‐grant OpenAccess abstract‐grant OpenAccess bodypdf‐grant OpenAccess bodyhtml‐grant OpenAccess bibliography‐grant OpenAccess esm‐grant OpenAccess online‐first false pdf‐file‐reference BodyRef/PDF/40169_2017_Article_171.pdf target‐type OnlinePDF issue‐type Regular article‐type OriginalPaper journal‐subject‐primary Medicine & Public Health journal‐subject‐secondary Medicine/Public Health, general journal‐subject‐collection SC11 open‐access true --> Background: Cdc42 is a member of the Rho GTPase family and functions as a molecular switch in regulating cytoskeleton remodeling and cell polarity establishment. Inactivating Cdc42 in cardiomyocytes resulted in embryonic lethality with heart developmental defects, including ventricular septum defects and thin ventricle wall syndrome. Findings: In this study, we have generated a Cdc42 cardiomyocyte knockout mouse line by crossing Cdc42/flox mice with myosin light chain 2a (MLC2a)‐Cre mice. We found that the deletion of Cdc42 in embryonic cardiomyocytes resulted in an underdeveloped right ventricle. Microarray analysis and real‐time PCR data analysis displayed that the deletion of Cdc42 decreased dHand expression level. In addition, we found evaginations in the ventricle walls of Cdc42 knockout hearts. Conclusion: We concluded that Cdc42 plays an essential role in right ventricle growth. [ABSTRACT FROM AUTHOR]

publisher‐imprint‐name Springer volume‐issue‐count 1 issue‐article‐count 0 issue‐toc‐levels 0 issue‐pricelist‐year 2017 issue‐copyright‐holder The Author(s) issue‐copyright‐year 2017 article‐contains‐esm No article‐numbering‐style Unnumbered article‐registration‐date‐year 2017 article‐registration‐date‐month 7 article‐registration‐date‐day 20 article‐toc‐levels 0 toc‐levels 0 volume‐type Regular journal‐product ArchiveJournal numbering‐style Unnumbered article‐grants‐type OpenChoice metadata‐grant OpenAccess abstract‐grant OpenAccess bodypdf‐grant OpenAccess bodyhtml‐grant OpenAccess bibliography‐grant OpenAccess esm‐grant OpenAccess online‐first false pdf‐file‐reference BodyRef/PDF/40169_2017_Article_155.pdf target‐type OnlinePDF issue‐type Regular article‐type OriginalPaper journal‐subject‐primary Medicine & Public Health journal‐subject‐secondary Medicine/Public Health, general journal‐subject‐collection SC11 --> Big Data, and in particular Electronic Health Records, provide the medical community with a great opportunity to analyze multiple pathological conditions at an unprecedented depth for many complex diseases, including diabetes. How can we infer on diabetes from large heterogeneous datasets? A possible solution is provided by invoking next‐generation computational methods and data analytics tools within systems medicine approaches. By deciphering the multi‐faceted complexity of biological systems, the potential of emerging diagnostic tools and therapeutic functions can be ultimately revealed. In diabetes, a multidimensional approach to data analysis is needed to better understand the disease conditions, trajectories and the associated comorbidities. Elucidation of multidimensionality comes from the analysis of factors such as disease phenotypes, marker types, and biological motifs while seeking to make use of multiple levels of information including genetics, omics, clinical data, and environmental and lifestyle factors. Examining the synergy between multiple dimensions represents a challenge. In such regard, the role of Big Data fuels the rise of Precision Medicine by allowing an increasing number of descriptions to be captured from individuals. Thus, data curations and analyses should be designed to deliver highly accurate predicted risk profiles and treatment recommendations. It is important to establish linkages between systems and precision medicine in order to translate their principles into clinical practice. Equivalently, to realize their full potential, the involved multiple dimensions must be able to process information ensuring inter‐exchange, reducing ambiguities and redundancies, and ultimately improving health care solutions by introducing clinical decision support systems focused on reclassified phenotypes (or digital biomarkers) and community‐driven patient stratifications. [ABSTRACT FROM AUTHOR]