What Are Some of the Best Big Data Analytics Visualization Tools?
Big Data in Social Research
Sources of Big data in Healthcare.
(PDF) RESEARCH IN BIG DATA -AN OVERVIEW
What is Big Data and Machine Learning
VIDEO
How to Build an AI Research Agent using No-Code Platform
Synthetic data might contribute to even more biases in AI #artificialinteligence #technology
TELUS Feedlot
TELUS Feedlot Services
Large-Scale Qualitative Research Webinar
Should you dump your large caps? #financialplanning #investment #investingsimplified
COMMENTS
A review of big data and medical research
In this descriptive review, we highlight the roles of big data, the changing research paradigm, and easy access to research participation via the Internet fueled by the need for quick answers. Universally, data volume has increased, with the collection rate doubling every 40 months, ever since the 1980s. 4 The big data age, starting in 2002 ...
Benefits and challenges of Big Data in healthcare: an overview of the
A specific definition of what Big Data means for health research was proposed by the Health Directorate of the Directorate-General for Research and Innovation of the European Commission: Big Data in health encompasses high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to ...
Big Data Research
About the journal. The journal aims to promote and communicate advances in big data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic. The journal will accept papers on foundational aspects in …. View full aims & scope.
15 years of Big Data: a systematic literature review
Over the past 15 years, Big Data has emerged as a foundational pillar providing support to an extensive range of different scientific fields, from medicine and healthcare [] to engineering [], finance and marketing [3,4,5], politics [], social networks analysis [7, 8], and telecommunications [], to cite only a few examples.This 15-year period has witnessed a significant increase in research ...
Scientific Research and Big Data
Research on big data analysis thus sheds light on elements of the research process that cannot be fully controlled, rationalised or even considered through recourse to formal tools. One such element is the work required to present empirical data in a machine-readable format that is compatible with the software and analytic tools at hand. Data ...
Home page
The Journal of Big Data publishes open-access original research on data science and data analytics. Deep learning algorithms and all applications of big data are welcomed. Survey papers and case studies are also considered. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture ...
Full article: Big data for scientific research and discovery
Big data for scientific research and discovery. With data volumes expanding beyond the Petabyte and Exabyte levels across many scientific disciplines, the role of big data for scientific research is becoming increasingly apparent: the massive data processing has become valuable for scientific research. The term big data is not only a buzzword ...
Articles
The burden of gastric cancer (GC) should be further clarified worldwide, and helped us to understand the current situation of GC. Zenghong Wu, Kun Zhang, Weijun Wang, Mengke Fan and Rong Lin. Journal of Big Data 2024 11 :51. Research Published on: 13 April 2024.
Big data in digital healthcare: lessons learnt and ...
Big Data initiatives in the United Kingdom. The UK Biobank is a prospective cohort initiative that is composed of individuals between the ages of 40 and 69 before disease onset (Allen et al. 2012 ...
Eleven tips for working with large data sets
Visualize the information. As data sets get bigger, new wrinkles emerge, says Titus Brown, a bioinformatician at the University of California, Davis. "At each stage, you're going to be ...
Moving back to the future of big data-driven research: reflecting on
Today, sociological research faces a widely datafied world, where (big) data analytics are profoundly changing the paradigm of knowledge production, as Facebook, Twitter, Google and others produce ...
Big Data Research
Read the latest articles of Big Data Research at ScienceDirect.com, Elsevier's leading platform of peer-reviewed scholarly literature
Big Data in Academic Research: Challenges, Pitfalls, and ...
Big Data results are hard to generalize, and working with Big Data may raise new ethical problems, even while obviating old ethical concerns. Nonetheless, Big Data offer many opportunities, allowing researchers to study previously inaccessible problems, with previously inconceivable sources of data. Although Big Data overcome some of the ...
The impact of big data on research methods in information science
Research methods are roadmaps, techniques, and procedures employed in a study to collect data, process data, analyze data, yield findings, and draw a conclusion to achieve the research aims. To a large degree the availability, nature, and size of a dataset can affect the selection of the research methods, even the research topics.
What are the threats and potentials of big data for qualitative research?
The use of big data is similarly encumbered by established institutional protocols and issues of ownership, human relationships, and new implications for research ethics that are only beginning to be understood. The issue of open access to, or sharing of data is one that has become contentious.
Significance and Challenges of Big Data Research
We then identify from different perspectives the significance and opportunities that big data brings to us. Next, we present representative big data initiatives all over the world. We describe the grand challenges (namely, data complexity, computational complexity, and system complexity), as well as possible solutions to address these challenges.
Big data: what it can and cannot achieve
What can 'big data' in mental health really achieve? Increasingly new resources are being created with exciting possibilities in terms of the potential application to mental health research in the UK (McIntosh et al., 2016).However, as we have highlighted, large scale electronic data resources have existed for many decades in other settings.
Big data preprocessing: methods and prospects
The massive growth in the scale of data has been observed in recent years being a key factor of the Big Data scenario. Big Data can be defined as high volume, velocity and variety of data that require a new high-performance processing. Addressing big data is a challenging and time-demanding task that requires a large computational infrastructure to ensure successful data processing and analysis.
The Impact of Big Data Research on Practice, Policy, and Cancer Care
The concept of "big data" research—the aggregation and analysis of biologic, clinical, administrative, and other data sources to drive new advances in biomedical knowledge—has been embraced by the cancer research enterprise. Although much of the conversation has concentrated on the amalgamation of basic biologic data (e.g., genomics, metabolomics, tumor tissue), new opportunities to ...
Big Data and Communication Research
Big data research is much more widespread in the commercial sector and in government and other organizations, where it is used for practical purposes—social engineering, if you like. The main effect, in the United States, Europe, and elsewhere, is that consumer marketing becomes more effective. Another main area of application is public ...
A big data driven vegetation disease and pest region identification
The model utilized a large amount of big data for training, achieving a recall rate of 98.42 % on multispectral datasets, and an overall classification accuracy of 99.04 %. After optimizing the residual network, the overall accuracy of identifying vegetation pest and disease areas has been further improved to 99.77 %, and the recall rate has ...
A brief survey on big data: technologies, terminologies and data
Big data has become the latest and eminent research topic because of its widespread application and use across various domains. According to the report presented by Gartner in 2013, big data holds a prominent position among innovative technologies and has been listed among the leading trend technologies from 2013 to 2018" [].Big data is characterized as an assortment of enormous databases ...
How to Integrate Cloud, Data, and AI Technologies
Summary. Building a strong, flexible "digital core" that integrates cloud, data, and AI technologies to serve as an interconnected foundation for your company is the key to future growth.
Big Data Application in Biomedical Research and Health Care: A
Abstract. Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day ...
Artificial Intelligence: Glossary
A language model that utilizes large amounts of text-based training data to build associations between different text snippets. See also: language model, neural networks, training data; Machine Learning. A category of algorithms that focus on identifying and incorporating trends from training data and making predictions for new data.
McKinsey technology trends outlook 2024
To assess the development of each technology trend, our team collected data on five tangible measures of activity: search engine queries, news publications, patents, research publications, and investment. For each measure, we used a defined set of data sources to find occurrences of keywords associated with each of the 15 trends, screened those occurrences for valid mentions of activity, and ...
Community Engagement Workshop: A Discussion of NIH Common Fund Data
The National Institutes of Health (NIH) Common Fund cultivates large, publicly available biomedical and behavioral datasets. These data sets are used by the research and medical community to make new discoveries or generate new hypotheses. The Common Fund is hosting a Community Engagement Workshop that offers a collaborative environment where leaders from diverse scientific backgrounds can ...
Striking costs of infertility point to importance of IVF access and
Big data on infertility treatments This prompted Persson and Polyakova, along with their collaborators — Sarah Bögl , a former SIEPR predoctoral research fellow who is now a PhD student in economics, and Jasmin Moshfegh , a recent PhD graduate in health policy — to turn to administrative, population-wide data from Sweden to fill in some ...
Research Data Analyst (Hybrid)
Department of Radiology at Stanford University is seeking a Research Data Analyst 1 to manage, analyze, and extract insights from large amounts of medical imaging datasets. The candidate will be working in the Integrative Biomedical Imaging Informatics (IBIIS) Division of the Department of Radiology, working in collaboration with the Stanford ...
1. The partisanship and ideology of American voters
The partisan identification of registered voters is now evenly split between the two major parties: 49% of registered voters are Democrats or lean to the Democratic Party, and a nearly identical share - 48% - are Republicans or lean to the Republican Party. The partisan balance has tightened in recent years following a clear edge in Democratic Party affiliation during the last administration.
IMAGES
VIDEO
COMMENTS
In this descriptive review, we highlight the roles of big data, the changing research paradigm, and easy access to research participation via the Internet fueled by the need for quick answers. Universally, data volume has increased, with the collection rate doubling every 40 months, ever since the 1980s. 4 The big data age, starting in 2002 ...
A specific definition of what Big Data means for health research was proposed by the Health Directorate of the Directorate-General for Research and Innovation of the European Commission: Big Data in health encompasses high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to ...
About the journal. The journal aims to promote and communicate advances in big data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic. The journal will accept papers on foundational aspects in …. View full aims & scope.
Over the past 15 years, Big Data has emerged as a foundational pillar providing support to an extensive range of different scientific fields, from medicine and healthcare [] to engineering [], finance and marketing [3,4,5], politics [], social networks analysis [7, 8], and telecommunications [], to cite only a few examples.This 15-year period has witnessed a significant increase in research ...
Research on big data analysis thus sheds light on elements of the research process that cannot be fully controlled, rationalised or even considered through recourse to formal tools. One such element is the work required to present empirical data in a machine-readable format that is compatible with the software and analytic tools at hand. Data ...
The Journal of Big Data publishes open-access original research on data science and data analytics. Deep learning algorithms and all applications of big data are welcomed. Survey papers and case studies are also considered. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture ...
Big data for scientific research and discovery. With data volumes expanding beyond the Petabyte and Exabyte levels across many scientific disciplines, the role of big data for scientific research is becoming increasingly apparent: the massive data processing has become valuable for scientific research. The term big data is not only a buzzword ...
The burden of gastric cancer (GC) should be further clarified worldwide, and helped us to understand the current situation of GC. Zenghong Wu, Kun Zhang, Weijun Wang, Mengke Fan and Rong Lin. Journal of Big Data 2024 11 :51. Research Published on: 13 April 2024.
Big Data initiatives in the United Kingdom. The UK Biobank is a prospective cohort initiative that is composed of individuals between the ages of 40 and 69 before disease onset (Allen et al. 2012 ...
Visualize the information. As data sets get bigger, new wrinkles emerge, says Titus Brown, a bioinformatician at the University of California, Davis. "At each stage, you're going to be ...
Today, sociological research faces a widely datafied world, where (big) data analytics are profoundly changing the paradigm of knowledge production, as Facebook, Twitter, Google and others produce ...
Read the latest articles of Big Data Research at ScienceDirect.com, Elsevier's leading platform of peer-reviewed scholarly literature
Big Data results are hard to generalize, and working with Big Data may raise new ethical problems, even while obviating old ethical concerns. Nonetheless, Big Data offer many opportunities, allowing researchers to study previously inaccessible problems, with previously inconceivable sources of data. Although Big Data overcome some of the ...
Research methods are roadmaps, techniques, and procedures employed in a study to collect data, process data, analyze data, yield findings, and draw a conclusion to achieve the research aims. To a large degree the availability, nature, and size of a dataset can affect the selection of the research methods, even the research topics.
The use of big data is similarly encumbered by established institutional protocols and issues of ownership, human relationships, and new implications for research ethics that are only beginning to be understood. The issue of open access to, or sharing of data is one that has become contentious.
We then identify from different perspectives the significance and opportunities that big data brings to us. Next, we present representative big data initiatives all over the world. We describe the grand challenges (namely, data complexity, computational complexity, and system complexity), as well as possible solutions to address these challenges.
What can 'big data' in mental health really achieve? Increasingly new resources are being created with exciting possibilities in terms of the potential application to mental health research in the UK (McIntosh et al., 2016).However, as we have highlighted, large scale electronic data resources have existed for many decades in other settings.
The massive growth in the scale of data has been observed in recent years being a key factor of the Big Data scenario. Big Data can be defined as high volume, velocity and variety of data that require a new high-performance processing. Addressing big data is a challenging and time-demanding task that requires a large computational infrastructure to ensure successful data processing and analysis.
The concept of "big data" research—the aggregation and analysis of biologic, clinical, administrative, and other data sources to drive new advances in biomedical knowledge—has been embraced by the cancer research enterprise. Although much of the conversation has concentrated on the amalgamation of basic biologic data (e.g., genomics, metabolomics, tumor tissue), new opportunities to ...
Big data research is much more widespread in the commercial sector and in government and other organizations, where it is used for practical purposes—social engineering, if you like. The main effect, in the United States, Europe, and elsewhere, is that consumer marketing becomes more effective. Another main area of application is public ...
The model utilized a large amount of big data for training, achieving a recall rate of 98.42 % on multispectral datasets, and an overall classification accuracy of 99.04 %. After optimizing the residual network, the overall accuracy of identifying vegetation pest and disease areas has been further improved to 99.77 %, and the recall rate has ...
Big data has become the latest and eminent research topic because of its widespread application and use across various domains. According to the report presented by Gartner in 2013, big data holds a prominent position among innovative technologies and has been listed among the leading trend technologies from 2013 to 2018" [].Big data is characterized as an assortment of enormous databases ...
Summary. Building a strong, flexible "digital core" that integrates cloud, data, and AI technologies to serve as an interconnected foundation for your company is the key to future growth.
Abstract. Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day ...
A language model that utilizes large amounts of text-based training data to build associations between different text snippets. See also: language model, neural networks, training data; Machine Learning. A category of algorithms that focus on identifying and incorporating trends from training data and making predictions for new data.
To assess the development of each technology trend, our team collected data on five tangible measures of activity: search engine queries, news publications, patents, research publications, and investment. For each measure, we used a defined set of data sources to find occurrences of keywords associated with each of the 15 trends, screened those occurrences for valid mentions of activity, and ...
The National Institutes of Health (NIH) Common Fund cultivates large, publicly available biomedical and behavioral datasets. These data sets are used by the research and medical community to make new discoveries or generate new hypotheses. The Common Fund is hosting a Community Engagement Workshop that offers a collaborative environment where leaders from diverse scientific backgrounds can ...
Big data on infertility treatments This prompted Persson and Polyakova, along with their collaborators — Sarah Bögl , a former SIEPR predoctoral research fellow who is now a PhD student in economics, and Jasmin Moshfegh , a recent PhD graduate in health policy — to turn to administrative, population-wide data from Sweden to fill in some ...
Department of Radiology at Stanford University is seeking a Research Data Analyst 1 to manage, analyze, and extract insights from large amounts of medical imaging datasets. The candidate will be working in the Integrative Biomedical Imaging Informatics (IBIIS) Division of the Department of Radiology, working in collaboration with the Stanford ...
The partisan identification of registered voters is now evenly split between the two major parties: 49% of registered voters are Democrats or lean to the Democratic Party, and a nearly identical share - 48% - are Republicans or lean to the Republican Party. The partisan balance has tightened in recent years following a clear edge in Democratic Party affiliation during the last administration.