Hasil untuk "data science"

J. A. Moral-Munoz, E. Herrera-Viedma, A. Santisteban-Espejo et al.

Bibliometrics has become an essential tool for assessing and analyzing the output of scientists, cooperation between universities, the effect of state-owned science funding on national research and development performance and educational efficiency, among other applications. Therefore, professionals and scientists need a range of theoretical and practical tools to measure experimental data. This review aims to provide an up-to-date review of the various tools available for conducting bibliometric and scientometric analyses, including the sources of data acquisition, performance analysis and visualization tools. The included tools were divided into three categories: general bibliometric and performance analysis, science mapping analysis, and libraries; a description of all of them is provided. A comparative analysis of the database sources support, pre-processing capabilities, analysis and visualization options were also provided in order to facilitate its understanding. Although there are numerous bibliometric databases to obtain data for bibliometric and scientometric analysis, they have been developed for a different purpose. The number of exportable records is between 500 and 50,000 and the coverage of the different science fields is unequal in each database. Concerning the analyzed tools, Bibliometrix contains the more extensive set of techniques and suitable for practitioners through Biblioshiny. VOSviewer has a fantastic visualization and is capable of loading and exporting information from many sources. SciMAT is the tool with a powerful pre-processing and export capability. In views of the variability of features, the users need to decide the desired analysis output and chose the option that better fits into their aims.

Emily M. Bender, Alexander Koller

The success of the large neural language models on many NLP tasks is exciting. However, we find that these successes sometimes lead to hype in which these models are being described as “understanding” language or capturing “meaning”. In this position paper, we argue that a system trained only on form has a priori no way to learn meaning. In keeping with the ACL 2020 theme of “Taking Stock of Where We’ve Been and Where We’re Going”, we argue that a clear understanding of the distinction between form and meaning will help guide the field towards better science around natural language understanding.

K. Choudhary, Brian L. DeCost, Chi Chen et al.

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

Agustí Verde Parera, Xavier Costa

Presentacio sobre l'Oficina de Proteccio de Dades Personals de la UAB i la politica Open Science. Va formar part de la conferencia "Les politiques d'Open Data / Open Acces: Implicacions a la recerca" orientada a investigadors i gestors de projectes europeus que va tenir lloc el 20 de setembre de 2018 a la Universitat Autonoma de Barcelona

S. Fortunato, Carl T. Bergstrom, K. Börner et al.

Chaomei Chen

Abstract Purpose We present a systematic review of the literature concerning major aspects of science mapping to serve two primary purposes: First, to demonstrate the use of a science mapping approach to perform the review so that researchers may apply the procedure to the review of a scientific domain of their own interest, and second, to identify major areas of research activities concerning science mapping, intellectual milestones in the development of key specialties, evolutionary stages of major specialties involved, and the dynamics of transitions from one specialty to another. Design/methodology/approach We first introduce a theoretical framework of the evolution of a scientific specialty. Then we demonstrate a generic search strategy that can be used to construct a representative dataset of bibliographic records of a domain of research. Next, progressively synthesized co-citation networks are constructed and visualized to aid visual analytic studies of the domain’s structural and dynamic patterns and trends. Finally, trajectories of citations made by particular types of authors and articles are presented to illustrate the predictive potential of the analytic approach. Findings The evolution of the science mapping research involves the development of a number of interrelated specialties. Four major specialties are discussed in detail in terms of four evolutionary stages: conceptualization, tool construction, application, and codification. Underlying connections between major specialties are also explored. The predictive analysis demonstrates citations trajectories of potentially transformative contributions. Research limitations The systematic review is primarily guided by citation patterns in the dataset retrieved from the literature. The scope of the data is limited by the source of the retrieval, i.e. the Web of Science, and the composite query used. An iterative query refinement is possible if one would like to improve the data quality, although the current approach serves our purpose adequately. More in-depth analyses of each specialty would be more revealing by incorporating additional methods such as citation context analysis and studies of other aspects of scholarly publications. Practical implications The underlying analytic process of science mapping serves many practical needs, notably bibliometric mapping, knowledge domain visualization, and visualization of scientific literature. In order to master such a complex process of science mapping, researchers often need to develop a diverse set of skills and knowledge that may span multiple disciplines. The approach demonstrated in this article provides a generic method for conducting a systematic review. Originality/value Incorporating the evolutionary stages of a specialty into the visual analytic study of a research domain is innovative. It provides a systematic methodology for researchers to achieve a good understanding of how scientific fields evolve, to recognize potentially insightful patterns from visually encoded signs, and to synthesize various information so as to capture the state of the art of the domain.

Asaph Azaria, A. Ekblaw, Thiago Vieira et al.

Xiaogang Li, Dawei Zhang, Zhiyong Liu et al.

Yogesh L. Simmhan, Beth Plale, Dennis Gannon

I. Grossmann, M. Feinberg, D. C. Parker et al.

Careful bias management and data fidelity are key Advances in artificial intelligence (AI), particularly large language models (LLMs), are substantially affecting social science research. These transformer-based machine-learning models pretrained on vast amounts of text data are increasingly capable of simulating human-like responses and behaviors (1, 2), offering opportunities to test theories and hypotheses about human behavior at great scale and speed. This presents urgent challenges: How can social science research practices be adapted, even reinvented, to harness the power of foundational AI? And how can this be done while ensuring transparent and replicable research?

A. Jaffe, Gaétan de Rassenfosse

The last 2 decades have witnessed a dramatic increase in the use of patent citation data in social science research. Facilitated by digitization of the patent data and increasing computing power, a community of practice has grown up that has developed methods for using these data to: measure attributes of innovations such as impact and originality; to trace flows of knowledge across individuals, institutions and regions; and to map innovation networks. The objective of this article is threefold. First, it takes stock of these main uses. Second, it discusses 4 pitfalls associated with patent citation data, related to office, time and technology, examiner, and strategic effects. Third, it highlights gaps in our understanding and offers directions for future research.

S. Nelms, S. Nelms, C. Coombes et al.

Growing evidence suggests that anthropogenic litter, particularly plastic, represents a highly pervasive and persistent threat to global marine ecosystems. Multinational research is progressing to characterise its sources, distribution and abundance so that interventions aimed at reducing future inputs and clearing extant litter can be developed. Citizen science projects, whereby members of the public gather information, offer a low-cost method of collecting large volumes of data with considerable temporal and spatial coverage. Furthermore, such projects raise awareness of environmental issues and can lead to positive changes in behaviours and attitudes. We present data collected over a decade (2005-2014 inclusive) by Marine Conservation Society (MCS) volunteers during beach litter surveys carried along the British coastline, with the aim of increasing knowledge on the composition, spatial distribution and temporal trends of coastal debris. Unlike many citizen science projects, the MCS beach litter survey programme gathers information on the number of volunteers, duration of surveys and distances covered. This comprehensive information provides an opportunity to standardise data for variation in sampling effort among surveys, enhancing the value of outputs and robustness of findings. We found that plastic is the main constituent of anthropogenic litter on British beaches and the majority of traceable items originate from land-based sources, such as public littering. We identify the coast of the Western English Channel and Celtic Sea as experiencing the highest relative litter levels. Increasing trends over the 10-year time period were detected for a number of individual item categories, yet no statistically significant change in total (effort-corrected) litter was detected. We discuss the limitations of the dataset and make recommendations for future work. The study demonstrates the value of citizen science data in providing insights that would otherwise not be possible due to logistical and financial constraints of running government-funded sampling programmes on such large scales.

Eleni Domzaridou, Ben Lacey, Naomi Allen et al.

Objectives To develop a resource that maps health outcomes across coding schemas in linked administrative data in UK Biobank, addressing the challenge of identifying equivalent outcomes from multiple sources. Our approach minimised the loss of clinical detail, a common limitation in such efforts, to enhance its utility for health research. Methods UK Biobank is a prospective cohort study of ~500,000 adults, recruited between 2006-10, with follow up for health outcomes through linkage with administrative health data. Clinical coding schemas include Read Version 2 (Read2) and Clinical Terms Version 3 (CTV3) from primary care, and International Classification of Diseases (ICD) 9th and 10th editions (ICD-9 and ICD-10) from secondary care, cancer registries and death records; self-reported conditions were also reported at recruitment. We reviewed existing mapping resources and, with clinical support, mapped clinical codes in different schemas to 4-digit ICD-10 to provide detailed clinical information using a single internationally-recognised schema. Results We processed data from 230,096 participants with primary care records, 442,267 with secondary care records, 40,447 with death records, and 397,063 with self-reported data. We successfully mapped to 81% of Read2 codes (N = 12,448), 93% of CTV3 (24,188), 92% of ICD-9 (3,060), and 100% of self-reported (509) to ICD-10 codes. Although existing resources frequently allowed a single code to be mapped to a single ICD-10 code (94% of the mapped codes for Read2, 58% of CTV3, and 79% of ICD-9), the remaining codes require extensive clinical review, which is ongoing. The conversion increased the granularity of health outcomes by 5.8 times from 2,006 3-digit ICD-10 codes to 11,625 4-digit ICD-10 codes. The most common ICD-10 codes included those related to musculoskeletal diseases (24%). Conclusion The increased granularity of ICD coding enhances the research potential of UK Biobank data, enabling precise outcome definitions and detailed comparisons with other healthcare datasets. The enhanced mappings revealed underrepresented and nuanced outcomes, improving subtyping of conditions, and supporting robust comparisons with external datasets using internationally recognised coding standards.

Soheil Shahbazi, Saharnaz Esmaeili, Anahita Moscowchi et al.

Background. The current study aimed to systematically review the existing evidence on potential links between gene polymorphisms and the occurrence of peri-implant mucositis (PIM) or peri-implantitis (PI). Methods. The electronic search was executed through six databases in November 2022: PubMed, Embase, Google Scholar, Scopus, Cochrane CENTRAL, and Web of Science. The search sought studies delving into the possible association of gene polymorphisms with PIM or PI. To showcase the effect size, odds ratios along with 95% confidence intervals were used. The meta-analysis was performed on polymorphisms/alleles reported in at least two studies. Results. The initial search yielded 2162 results, which were reduced to 1327 following deduplication. After evaluating titles, abstracts, and full texts, 30 studies were deemed suitable for inclusion. Forty-nine gene polymorphisms were examined among 50 PIM patients, 1603 PI patients, and 2407 healthy controls spanning seven ethnicities. The meta-analysis showed that IL-1α -889 (95% CI: 1.070‒2.850, OR=1.746, P=0.026), IL-1β+3954 (95% CI: 1.265‒2.851, OR=1.899, P=0.002), and OPG -3618 (95% CI: 1.158‒2.983, OR=1.859, P=0.010) gene polymorphisms significantly differed between healthy controls and PI patients. However, IL-1β -511, IL-6 -174, OPG -3617, and TNF-α -308 gene polymorphisms did not significantly alter PI risk. Due to insufficient data, performing a meta-analysis on PIM was not feasible. Conclusion. The findings suggest that IL-1α -889, IL-1β+3954, and OPG -3618 gene polymorphisms are associated with the predisposition to PI. However, further research among diverse populations is warranted to draw more definitive conclusions.

Abdulrahman Mirzakhani, Sayyad Darvishi

<p style="text-align: left;"><strong>Abstract:</strong></p> <p style="text-align: left;">Increasing organizational productivity by focusing on effectiveness along with the satisfaction of service recipients of service organizations is an inevitable necessity. The present study is an attempt to investigate the impact of knowledge management dimensions on organizational effectiveness in the field of police crime prevention, considering the mediating role of employees' spiritual intelligence. This study is quantitative in terms of data, applied in terms of objective, and correlational in nature. The statistical population of this research consisted of level one and two managers of Strategic Studies Center, Police Science Research Institute, Amin University and Prevention Police in 2022. Based on stratified and simple random sampling, the sample size included 103 participants. The collected data were analyzed by structural equation method using SPSS and Lisrel software. The findings of the research show that knowledge management dimensions have a direct effect of 67% and indirect effect of 48% through the spiritual intelligence of employees on organizational effectiveness. The direct effect of employees' spiritual intelligence on organizational effectiveness is 56%. Also, the dimensions of knowledge management predict 73% of changes in employees' spiritual intelligence. As a result, strengthening the variables of creation, distribution and application of knowledge in the direction of organizational effectiveness should be given serious attention. In addition, the spiritual intelligence of employees as a mediating variable should be strengthened since by strengthening the indicators of spiritual intelligence, the indirect effect of knowledge management dimensions on the organizational effectiveness of the police in the field of crime prevention can be increased.</p> <p style="text-align: left;"><strong>Key Words:</strong> organizational effectiveness, organizational knowledge, police organization, spiritual intelligence</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;"><strong>1.Introduction</strong></p> <p style="text-align: left;">Understanding the implications of the dimensions and indicators of knowledge management and spiritual intelligence on organizational effectiveness can be valuable for officials and managers who seek to improve and strengthen performance. However, the necessity of investigating the knowledge management, spiritual intelligence and organizational effectiveness of the police, especially in the field of crime prevention, can be seen as a response to the current environmental conditions and the needs of managers and commanders. On the other hand, increasing the effectiveness of the organization in order to improve the performance of the employees requires nobility and understanding of the direct and indirect effect of the knowledge management and spiritual intelligence components and indicators on the effectiveness of the organization. In fact, by improving the knowledge management and spiritual intelligence indicators, the organizational effectiveness of the police can be improved. In order to achieve organizational goals, including crime prevention, the present research tries to determine the dimensions of the direct and indirect effect of knowledge management through spiritual intelligence as a mediator on the organizational effectiveness of the police in crime prevention.</p> <ol style="text-align: left;" start="2"> <li><strong>Literature Review</strong></li> </ol> <p style="text-align: left;">The present research, which is conducted with the aim of knowing the impact of knowledge management dimensions on organizational effectiveness in&nbsp; the police crime prevention with the mediating role of employees' spiritual intelligence, is based on the dimensions of knowledge management, defined by Bhatt (2001) who considers knowledge management as the process of creating, presenting, distributing and applying&nbsp; knowledge, and spiritual intelligence of Wellman who emphasizes the seven dimensions of spiritual intelligence, including mastery, mindfulness, extrasensory perception, unity, intelligence, trauma, and childhood spirituality, as well as the effectiveness of Robbins (2008) including quality, education development, motivation and flexibility.</p> <p style="text-align: left;"><strong>3.Methodology</strong></p> <p style="text-align: left;">This study is quantitative in terms of data, applied in terms of objective, and correlational in nature. The statistical population of this research consisted of level one and two managers of the Strategic Studies Center, Research Institute of Police Sciences and Social Order, Amin University of Police Sciences and Prevention Police in 2022, including 140 participants. The sampling method was based on stratified and simple random sampling method. According to the formula for determining the sample size, 103 participants constituted the sample of the study. Hypotheses testing was conducted using mean tests to analyze the data and calculate the population mean and standard deviation. Additionally, a structural equation model was employed in order to perform multivariate regression, factor analysis, path analysis, and to assess the causal relationship among variables. Also, to measure hidden variables measurable and obvious indicators were used. The data was analyzed using SPSS and Lisrel software.</p> <p style="text-align: left;"><strong>4.Result</strong></p> <p style="text-align: left;">The research data and the results obtained through path analysis show that the dimensions of knowledge management not only have a significant direct effect on organizational effectiveness, but also have a greater and stronger effect on spiritual intelligence and that investing through spiritual intelligence has a double effect of 88% directly and indirectly on organizational effectiveness. For this reason, the third and fourth hypotheses of the research were also confirmed.</p> <p style="text-align: left;"><strong>5.Conclusion</strong></p> <p style="text-align: left;">The significant effect of knowledge management dimensions on organizational effectiveness has been confirmed in the conducted research. Also, in this research, the effect of knowledge management on organizational effectiveness in crime prevention, and more importantly, the significant large effect of organizational structure on spiritual intelligence have been confirmed. Furthermore, the indirect effect of knowledge management through spiritual intelligence on organizational effectiveness shows that the mediating variable, in addition to the direct effect on organizational effectiveness in the field of crime prevention, also indirectly affects the dimensions which in turn facilitates the management of organizational effectiveness knowledge. Therefore, it is possible to restore and develop the indicators of creation, presentation, distribution and use throughout the organization, especially within the executive layers of the police, and at the same time, consider the indicators of spiritual intelligence including mastery, concern, extrasensory perception and unity which is derived from the nature of humans, in order to increase the intensity of the direct and indirect effect of knowledge management on organizational effectiveness. It should be mentioned that, based on the the findings of the present research, organizational knowledge helps to strengthen spiritual intelligence.</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p>

George P Balchin, Anina Schuller, Isabella di Stefano et al.

Shark predator assemblages play an important role in the top-down processes that are vital to marine ecosystem functioning. Spatiotemporal partitioning of sharks due to seasonal movements or population changes may have significant consequences for the top-down effects, depending on the level of functional redundancy in the assemblage. However, long-term, co-occurrence data for sharks is hard to obtain and often lacking. Here we use citizen science data collected by professional scuba guides over seven years to model the seasonal and across-year temporal dynamics, and intraguild and trophic co-occurrence interactions, for an assemblage of six shark top predators (Carcharhinus leucas, Carcharhinus obscurus, Carcharhinus limbatus, Carcharias taurus, Sphyrna lewini, and Galeocerdo cuvier). The presence of all six study species were clearly seasonal and, in most cases, exhibited positive long-term trends across years. The seasonalities observed, combined with temporal co-occurrence analysis, suggests that dietary redundancy but temporal complementarity exists amongst the top predator assemblage. The study shows citizen science data collected by professional non-scientists is a cost-effective method for monitoring top predators and may be able to highlight potential predator-prey interactions worthy of further investigation.

Tatiana Chakravorti, Sai Koneru, Sarah Rajtmajer

In the past decade, open science and science of science communities have initiated innovative efforts to address concerns about the reproducibility and replicability of published scientific research. In some respects, these efforts have been successful, yet there are still many pockets of researchers with little to no familiarity with these concerns, subsequent responses, or best practices for engaging in reproducible, replicable, and reliable scholarship. In this study, we surveyed 452 professors from universities across the USA and India to understand perspectives on scientific processes and identify key points for intervention. Our findings reveal both national and disciplinary gaps in attention to reproducibility and transparency in science, aggravated by incentive misalignment and resource constraints. We suggest that solutions addressing scientific integrity should be culturally-centered, where definitions of culture should include both regional and domain-specific elements. This study examines research cultures in India and the USA across a diverse range of social science and engineering disciplines. The universities included in the study were carefully selected to represent various regions of each country and reflect institutions across different ranking levels, ensuring a broad and representative sample. While the findings provide valuable insights into the research environments of India and the USA, their applicability is limited to these two countries and respective disciplines. The survey relies on self-reported data, which can be subject to biases, e.g., social desirability or recall bias. Future research will expand the scope to include additional countries, allowing for a more comprehensive comparison of global research cultures. Additionally, we aim to investigate how regional, institutional, and disciplinary factors influence research practices and collaboration across borders, providing a deeper understanding of international academic environments.

Meijia Zhang, Junzheng Li, Xiyuan Zheng

Abstract Hashing has been extensively utilized in cross-modal retrieval due to its high efficiency in handling large-scale, high-dimensional data. However, most existing cross-modal hashing methods operate as offline learning models, which learn hash codes in a batch-based manner and prove to be inefficient for streaming data. Recently, several online cross-modal hashing methods have been proposed to address the streaming data scenario. Nevertheless, these methods fail to fully leverage the semantic information and accurately optimize hashing in a discrete fashion. As a result, both the accuracy and efficiency of online cross-modal hashing methods are not ideal. To address these issues, this paper introduces the Semantic Embedding-based Online Cross-modal Hashing (SEOCH) method, which integrates semantic information exploitation and online learning into a unified framework. To exploit the semantic information, we map the semantic labels to a latent semantic space and construct a semantic similarity matrix to preserve the similarity between new data and existing data in the Hamming space. Moreover, we employ a discrete optimization strategy to enhance the efficiency of cross-modal retrieval for online hashing. Through extensive experiments on two publicly available multi-label datasets, we demonstrate the superiority of the SEOCH method.

Qonita Rachmah, Prasenjit Mondal, Hai Phung et al.

Abstract Objective: Numerous studies have examined the relationship between overweight/obesity and iron deficiency anaemia (IDA) across diverse population groups, but a definitive link has not been clearly determined. This systematic review examined the association between overweight/obesity and IDA in women of reproductive age (WRA). Design: The initial search was performed in the CINAHL, Embase, MEDLINE, SCOPUS and Web of Science databases. The studies included should report at least one Fe status with/without an inflammatory marker, using the BMI to define overweight/obesity. Only baseline data were extracted for longitudinal studies. Setting: Global. Participant: Pregnant or non-pregnant women aged 18–50 years. Results: In total, twenty-seven papers were included (twelve addressing pregnant women and fifteen addressing non-pregnant women). Overall, most of the studies reported no association between overweight/obesity and Hb concentration. However, a positive association was reported more frequently in pregnant women. The association between overweight/obesity and serum ferritin concentrations was mixed. Most of the studies on non-pregnant women reported a positive association. Only a few studies measured hepcidin and inflammatory markers, and the majority revealed an increased level among overweight/obese WRA. Among pregnant women, overweight/obesity was positively associated with anaemia and IDA but negatively associated with iron deficiency (ID). Meanwhile, overweight/obese non-pregnant women were positively associated with anaemia, ID and IDA. Conclusions: Overweight/obesity was associated with a decreased prevalence of anaemia and IDA but an increased prevalence of ID, while its association with several Fe markers was inconclusive. Further studies integrating the assessment of various Fe markers, inflammatory markers and hepcidin are needed.

Kangsan Kim, Geumbee Kim, Jiwon Yoo et al.

As the penetration of electric vehicles (EVs) increases, an understanding of EV operation characteristics becomes crucial in various aspects, e.g., grid stability and battery degradation. This can be achieved through analyzing large amounts of EV operation data; however, the variability in EV data according to the user complicates unified data analysis and identification of representative patterns. In this research, a framework that captures EV charging characteristics in terms of charge–discharge area is proposed using actual field data. In order to illustrate EV operation characteristics in a unified format, an individual EV operation profile is modeled by the probability distribution of the charging start and end states of charge (SoCs).Then, hierarchical clustering analysis is employed to derive representative charging profiles. Using large amounts of real-world, vehicle-specific EV data in South Korea, the analysis results reveal that EV charging characteristics in terms of the battery charge–discharge area can be summarized into seven representative profiles.