scholarly journals Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies

2020 ◽  
Vol 1 (1) ◽  
pp. 377-386 ◽  
Author(s):  
Jeroen Baas ◽  
Michiel Schotten ◽  
Andrew Plume ◽  
Grégoire Côté ◽  
Reza Karimi
Keyword(s):  
Large Scale ◽  
Science Studies ◽  
Academic Research ◽  
Research Community ◽  
Advisory Board ◽  
Quality Data ◽  
Bibliometric Data ◽  
Content Selection ◽  
Data Source ◽  
Data Elements

Scopus is among the largest curated abstract and citation databases, with a wide global and regional coverage of scientific journals, conference proceedings, and books, while ensuring only the highest quality data are indexed through rigorous content selection and re-evaluation by an independent Content Selection and Advisory Board. Additionally, extensive quality assurance processes continuously monitor and improve all data elements in Scopus. Besides enriched metadata records of scientific articles, Scopus offers comprehensive author and institution profiles, obtained from advanced profiling algorithms and manual curation, ensuring high precision and recall. The trustworthiness of Scopus has led to its use as bibliometric data source for large-scale analyses in research assessments, research landscape studies, science policy evaluations, and university rankings. Scopus data have been offered for free for selected studies by the academic research community, such as through application programming interfaces, which have led to many publications employing Scopus data to investigate topics such as researcher mobility, network visualizations, and spatial bibliometrics. In June 2019, the International Center for the Study of Research was launched, with an advisory board consisting of bibliometricians, aiming to work with the scientometric research community and offering a virtual laboratory where researchers will be able to utilize Scopus data.

Evaluating Qualitative Research

2017 ◽  
Author(s):  
Jeasik Cho
Keyword(s):  
Qualitative Research ◽  
Large Scale ◽  
Academic Research ◽  
Research Community ◽  
Assessment Tools ◽  
Journal Articles ◽  
Journal Editors ◽  
The Past ◽  
Grant Proposals

This book provides the qualitative research community with some insight on how to evaluate the quality of qualitative research. This topic has gained little attention during the past few decades. We, qualitative researchers, read journal articles, serve on masters’ and doctoral committees, and also make decisions on whether conference proposals, manuscripts, or large-scale grant proposals should be accepted or rejected. It is assumed that various perspectives or criteria, depending on various paradigms, theories, or fields of discipline, have been used in assessing the quality of qualitative research. Nonetheless, until now, no textbook has been specifically devoted to exploring theories, practices, and reflections associated with the evaluation of qualitative research. This book constructs a typology of evaluating qualitative research, examines actual information from websites and qualitative journal editors, and reflects on some challenges that are currently encountered by the qualitative research community. Many different kinds of journals’ review guidelines and available assessment tools are collected and analyzed. Consequently, core criteria that stand out among these evaluation tools are presented. Readers are invited to join the author to confidently proclaim: “Fortunately, there are commonly agreed, bold standards for evaluating the goodness of qualitative research in the academic research community. These standards are a part of what is generally called ‘scientific research.’ ”

scholarly journals Bridges and Barriers: An Exploration of Engagements of the Research Community with the OpenStreetMap Community

2022 ◽  
Vol 11 (1) ◽  
pp. 54
Author(s):  
A. Yair Grinberger ◽  
Marco Minghini ◽  
Godwin Yeboah ◽  
Levente Juhász ◽  
Peter Mooney
Keyword(s):  
Research Group ◽  
Academic Research ◽  
Research Community ◽  
Academic Community ◽  
Literature Analysis ◽  
Research Subject ◽  
Research Projects ◽  
Related Research ◽  
Data Source ◽  
Causal Structures

The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the extent and nature of engagement between the academic research community and the larger communities in OSM. An analysis of OSM-related publications from 2016 to 2019 and seven interviews conducted with members of one research group engaged in OSM-related research are described. The literature analysis seeks to uncover general engagement patterns while the interviews are used to identify possible causal structures explaining how these patterns may emerge within the context of a specific research group. Results indicate that academic papers generally show few signs of engagement and adopt data-oriented perspectives on the OSM project and product. The interviews expose that more complex perspectives and deeper engagement exist within the research group to which the interviewees belong, e.g., engaging in OSM mapping and direct interactions based on specific points-of-contact in the OSM community. Several conclusions and recommendations emerge, most notably: that every engagement with OSM includes an interpretive act which must be acknowledged and that the academic community should act to triangulate its interpretation of the data and OSM community by diversifying their engagement. This could be achieved through channels such as more direct interactions and inviting members of the OSM community to participate in the design and evaluation of research projects and programmes.

scholarly journals Promoting Successful Cognitive Aging: A Ten-Year Update

2021 ◽  
pp. 1-50
Author(s):  
Taylor J. Krivanek ◽  
Seth A. Gale ◽  
Brittany M. McFeeley ◽  
Casey M. Nicastri ◽  
Kirk R. Daffner
Keyword(s):  
Cognitive Decline ◽  
Cognitive Aging ◽  
Social Engagement ◽  
Large Scale ◽  
Science Studies ◽  
Cognitive Capacity ◽  
Quality Data ◽  
Good Time ◽  
Anticholinergic Medications ◽  
Toxic Damage

A decade has passed since we published a comprehensive review in this journal addressing the topic of promoting successful cognitive aging, making this a good time to take stock of the field. Because there have been limited large-scale, randomized controlled trials, especially following individuals from middle age to late life, some experts have questioned whether recommendations can be legitimately offered about reducing the risk of cognitive decline and dementia. Despite uncertainties, clinicians often need to at least make provisional recommendations to patients based on the highest quality data available. Converging lines of evidence from epidemiological/cohort studies, animal/basic science studies, human proof-of-concept studies, and human intervention studies can provide guidance, highlighting strategies for enhancing cognitive reserve and preventing loss of cognitive capacity. Many of the suggestions made in 2010 have been supported by additional research. Importantly, there is a growing consensus among major health organizations about recommendations to mitigate cognitive decline and promote healthy cognitive aging. Regular physical activity and treatment of cardiovascular risk factors have been supported by all of these organizations. Most organizations have also embraced cognitively stimulating activities, a heart-healthy diet, smoking cessation, and countering metabolic syndrome. Other behaviors like regular social engagement, limiting alcohol use, stress management, getting adequate sleep, avoiding anticholinergic medications, addressing sensory deficits, and protecting the brain against physical and toxic damage also have been endorsed, although less consistently. In this update, we review the evidence for each of these recommendations and offer practical advice about behavior-change techniques to help patients adopt brain-healthy behaviors.

SOVIET SCIENTIFIC PERSONAL REPRESSIVE STATE APPARATUS AS AN OBJECT OF HISTORICAL SCIENCE OF SCIENCE STUDIES

2020 ◽  
pp. 27-35
Author(s):  
Alexander Allakhverdyan
Keyword(s):  
Science Policy ◽  
Large Scale ◽  
Science Studies ◽  
Soviet Science ◽  
State Repression ◽  
Developed Country ◽  
Systemic Analysis ◽  
State Apparatus ◽  
Dramatic Practice ◽  
Main Components

Numerous studies by Russian scientists and historians of science are devoted to the state science policy in the USSR and its well-known achievements, but not enough attention is paid to the negative, socially repressed aspects of the Soviet science policy. Repressions became one of the main components of the state's scientific and personnel policy in the Stalinist era. The systemic analysis of the development of Soviet science declared in the scientific literature, limited only by its indisputably outstanding achievements, without under-standing the origins, causes and mechanisms of the repressed state apparatus that operated in the same period, sharply reduces the overall picture of the reliability of the study of Soviet science. The purpose of the study is to comprehend the diverse and dramatic practice of state repression in the system of Soviet science, because in the world history of science no other developed country has experienced such large-scale and tragic events in the functioning of the scientific society.

Getting out of the Field

2017 ◽  
Author(s):  
Jeasik Cho
Keyword(s):  
Qualitative Research ◽  
Academic Research ◽  
Scientific Research ◽  
Research Community

This chapter provides a review of the book, which explores how to conceptually understand and practically evaluate the quality of qualitative research. Despite the fact that there are few scholarly pieces regarding qualitative research, the depth and creativity that the pioneering researchers have demonstrated are profound, and the extent to which they cover not only the broad quality of qualitative research but also most of the specific qualities expected by many different kinds of qualitative research is incredible. This chapter summarizes the major topics of this book. Final remarks on this exciting, creative, but difficult topic are preceded by the following summary: Fortunately, There are commonly agreed, bold standards for evaluating the goodness of qualitative research in the academic research community. These standards are a part of what is generally called “scientific research.”

scholarly journals A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

Epidemiologia ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 315-324
Author(s):  
Juan M. Banda ◽  
Ramya Tekumalla ◽  
Guanyu Wang ◽  
Jingyuan Yu ◽  
Tuo Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Social Dynamics ◽  
Additional Data ◽  
Open Data ◽  
Data Sources ◽  
Research Projects ◽  
Research Groups ◽  
The World ◽  
Data Source

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others.

scholarly journals Mesophotic.org: a repository for scientific information on mesophotic ecosystems

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Pim Bongaerts ◽  
Gonzalo Perez-Rosales ◽  
Veronica Z Radice ◽  
Gal Eyal ◽  
Andrea Gori ◽  
...  
Keyword(s):  
Large Scale ◽  
Scientific Information ◽  
Temporal Trends ◽  
Light Availability ◽  
Research Community ◽  
Future Research ◽  
Photosynthetic Organisms ◽  
Future Research Directions ◽  
Available Information ◽  
Reduced Light

Abstract Mesophotic coral ecosystems (MCEs) and temperate mesophotic ecosystems (TMEs) occur at depths of roughly 30–150 m depth and are characterized by the presence of photosynthetic organisms despite reduced light availability. Exploration of these ecosystems dates back several decades, but our knowledge remained extremely limited until about a decade ago, when a renewed interest resulted in the establishment of a rapidly growing research community. Here, we present the ‘mesophotic.org’ database, a comprehensive and curated repository of scientific literature on mesophotic ecosystems. Through both manually curated and automatically extracted metadata, the repository facilitates rapid retrieval of available information about particular topics (e.g. taxa or geographic regions), exploration of spatial/temporal trends in research and identification of knowledge gaps. The repository can be queried to comprehensively obtain available data to address large-scale questions and guide future research directions. Overall, the ‘mesophotic.org’ repository provides an independent and open-source platform for the ever-growing research community working on MCEs and TMEs to collate and expedite our understanding of the occurrence, composition and functioning of these ecosystems. Database URL: http://mesophotic.org/

Long-Term Monitoring and Research in the Clarion-Clipperton Zone

2021 ◽  
Vol 55 (6) ◽  
pp. 16-21
Author(s):  
Laurence P. Madin
Keyword(s):  
Large Scale ◽  
Renewable Energy Sources ◽  
Academic Research ◽  
Climate Science ◽  
Polymetallic Nodules ◽  
Continuous Presence ◽  
Offshore Oil Industry ◽  
Offshore Oil ◽  
Term Monitoring

Abstract The widely recognized need for large-scale transition from fossil to renewable energy sources has led to renewed effort to obtain metals needed for battery-based electric transportation and other functions. A potential source of some of these metals is the deposits of polymetallic nodules on the deep seafloor. If mining of these deposits proceeds in the coming decade, the enterprise creates an opportunity for extensive, long-term oceanographic research in the mining locations. The need to monitor environmental effects of mining activity can best be met with a near-continuous presence of a research platform in the vicinity. The platform could be a ship or potentially a semi-submersible platform like those used in the offshore oil industry. Such a facility might be supported by a consortium of mining companies and also provide opportunities for academic research in ocean and climate science.

EdgeDIPN

2020 ◽  
Vol 14 (3) ◽  
pp. 320-328
Author(s):  
Long Guo ◽  
Lifeng Hua ◽  
Rongfei Jia ◽  
Fei Fang ◽  
Binqiang Zhao ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Attention Mechanism ◽  
Data Sources ◽  
User Intent ◽  
Multiple User ◽  
Shopping Experience ◽  
Data Source ◽  
Intent Prediction ◽  
The Right

With the rapid growth of e-commerce in recent years, e-commerce platforms are becoming a primary place for people to find, compare and ultimately purchase products. To improve online shopping experience for consumers and increase sales for sellers, it is important to understand user intent accurately and be notified of its change timely. In this way, the right information could be offered to the right person at the right time. To achieve this goal, we propose a unified deep intent prediction network, named EdgeDIPN, which is deployed at the edge, i.e., mobile device, and able to monitor multiple user intent with different granularity simultaneously in real-time. We propose to train EdgeDIPN with multi-task learning, by which EdgeDIPN can share representations between different tasks for better performance and saving edge resources in the meantime. In particular, we propose a novel task-specific attention mechanism which enables different tasks to pick out the most relevant features from different data sources. To extract the shared representations more effectively, we utilize two kinds of attention mechanisms, where the multi-level attention mechanism tries to identify the important actions within each data source and the inter-view attention mechanism learns the interactions between different data sources. In the experiments conducted on a large-scale industrial dataset, EdgeDIPN significantly outperforms the baseline solutions. Moreover, EdgeDIPN has been deployed in the operational system of Alibaba. Online A/B testing results in several business scenarios reveal the potential of monitoring user intent in real-time. To the best of our knowledge, EdgeDIPN is the first full-fledged real-time user intent understanding center deployed at the edge and serving hundreds of millions of users in a large-scale e-commerce platform.

scholarly journals Characterization and selection of Japanese electronic health record databases used as data sources for non-interventional observational studies

2021 ◽  
Author(s):  
Yumi Wakabayashi ◽  
Masamitsu Eitoku ◽  
Narufumi Suganuma
Keyword(s):  
Electronic Health Record ◽  
Observational Studies ◽  
Large Scale ◽  
Data Sources ◽  
Flow Diagram ◽  
Health Record ◽  
Medical Institutions ◽  
Data Source ◽  
Electronic Health ◽  
Using Data

Abstract Background Interventional studies are the fundamental method for obtaining answers to clinical question. However, these studies are sometimes difficult to conduct because of insufficient financial or human resources or the rarity of the disease in question. One means of addressing these issues is to conduct a non-interventional observational study using electronic health record (EHR) databases as the data source, although how best to evaluate the suitability of an EHR database when planning a study remains to be clarified. The aim of the present study is to identify and characterize the data sources that have been used for conducting non-interventional observational studies in Japan and propose a flow diagram to help researchers determine the most appropriate EHR database for their study goals. Methods We compiled a list of published articles reporting observational studies conducted in Japan by searching PubMed for relevant articles published in the last 3 years and by searching database providers’ publication lists related to studies using their databases. For each article, we reviewed the abstract and/or full text to obtain information about data source, target disease or therapeutic area, number of patients, and study design (prospective or retrospective). We then characterized the identified EHR databases. Results In Japan, non-interventional observational studies have been mostly conducted using data stored locally at individual medical institutions (713/1463) or collected from several collaborating medical institutions (351/1463). Whereas the studies conducted with large-scale integrated databases (195/1463) were mostly retrospective (68.2%), 27.2% of the single-center studies, 46.2% of the multi-center studies, and 74.4% of the post-marketing surveillance studies, identified in the present study, were conducted prospectively. Conclusions Our analysis revealed that the non-interventional observational studies were conducted using data stored local at individual medical institutions or collected from collaborating medical institutions in Japan. Disease registries, disease databases, and large-scale databases would enable researchers to conduct studies with large sample sizes to provide robust data from which strong inferences could be drawn. Using our flow diagram, researchers planning non-interventional observational studies should consider the strengths and limitations of each available database and choose the most appropriate one for their study goals. Trial registration Not applicable.

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