14 Most popular August 2016 data science articles to read
(PDF) Research on Data Science, Data Analytics and Big Data
Top 10 Must-Read Data Science Research Papers in 2022
(PDF) International Journal of Data Science and Advanced Analytics
VIDEO
Data Science as Interdisciplinary Research
Data Science Research Methods: Causality and selection
Data Science at Michigan Tech
Data Science Research Jobs For Masters Or PhD Preferred
"Learn data science the best way possible with Datacamp" #data #datascience
BEST DATA SCIENCE ARTICLES WEBSITE
COMMENTS
Harvard Data Science Review
As an open access platform of the Harvard Data Science Initiative, Harvard Data Science Review (HDSR) features foundational thinking, research milestones, educational innovations, and major applications, with a primary emphasis on reproducibility, replicability, and readability.We aim to publish content that helps define and shape data science as a scientifically rigorous and globally ...
data science Latest Research Papers
Data Science . Information Use . Regulatory Compliance . Future Research . Public And Private . Social Good . Public And Private Sector . Effective Use. AbstractThe appetite for effective use of information assets has been steadily rising in both public and private sector organisations.
The role of data science in healthcare advancements: applications
The data generated generally are retained for a shorter duration, and thus, extensive research into produced data is neglected. However, advancements in data science in the field of healthcare attempt to ensure better management of data and provide enhanced patient care [20-23].
Data Science Articles
The articles we have listed below were compiled and written by data science professors, experts, and practitioners within the field as well as based on professional research of the industry and related trends, opportunities, and projections.
Top 10 Must-Read Data Science Research Papers in 2022
VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS. The research paper is written by- James Duncan, RushKapoor, Abhineet Agarwal, Chandan Singh, Bin Yu. This research paper is more of a journal of open-source software than a study paper.
Data science: a game changer for science and innovation
This paper shows data science's potential for disruptive innovation in science, industry, policy, and people's lives. We present how data science impacts science and society at large in the coming years, including ethical problems in managing human behavior data and considering the quantitative expectations of data science economic impact. We introduce concepts such as open science and e ...
Ten Research Challenge Areas in Data Science
Abstract. To drive progress in the field of data science, we propose 10 challenge areas for the research community to pursue. Since data science is broad, with methods drawing from computer science, statistics, and other disciplines, and with applications appearing in all sectors, these challenge areas speak to the breadth of issues spanning ...
Latest stories published on Towards Data Science
Part 4 — Towards Mamba State Space Models for…. Read more…. 434. 8 responses. Read the latest stories published by Towards Data Science. Your home for data science. A Medium publication sharing concepts, ideas and codes.
69901 PDFs
Data science combines the power of computer science and applications, modeling, statistics, engineering, economy and analytics. Whereas a... | Explore the latest full-text research PDFs, articles ...
Full article: Data Science in Science: A New Journal with a Radically
Data Science in Science is founded as an open access international journal that publishes original research, letters, and reviews at the intersection of Science and Data Science. Its aim is to advance: New ideas for experimental and observational data-driven learning and discovery that help address fundamental questions at the frontiers of ...
Articles
The CODATA Data Science Journal is a peer-reviewed, open access, electronic journal, publishing papers on the management, dissemination, use and reuse of research data and databases across all research domains, including science, technology, the humanities and the arts. The scope of the journal includes descriptions of data systems, their implementations and their publication, applications ...
Innovations in Data Science Research for Future Computing Era
Please select the appropriate Collection title "Innovations in Data Science Research for Future Computing Era" from the dropdown menu. Articles will undergo the journal's standard peer-review process and are subject to all the journal's standard policies. Articles will be added to the Collection as they are published.
Education Data Science: Past, Present, Future
Its application to more strained regions and populations (at scale) seems especially promising for education data science research going forward. Critique of Machine Learning Predictions. Were scholars to look at typical computer science outlets for data science articles, they would find a prevalence of machine learning models and efforts to ...
Five Key Trends in AI and Data Science for 2024
5. Data, analytics, and AI leaders are becoming less independent. This past year, we began to notice that increasing numbers of organizations were cutting back on the proliferation of technology and data "chiefs," including chief data and analytics officers (and sometimes chief AI officers).
Data Science and Analytics: An Overview from Data-Driven Smart
This research contributes to the creation of a research vector on the role of data science in central banking. In , the authors provide an overview and tutorial on the data-driven design of intelligent wireless networks. The authors in provide a thorough understanding of computational optimal transport with application to data science.
Data Science and Management
Data Science and Management (DSM) is a peer-reviewed open access journal for original research articles, review articles and technical reports related to all aspects of data science and its application in the field of business, economics, finance, operations, engineering, healthcare, transportation, agriculture, energy, environment, sports, and ...
Data, measurement and empirical methods in the science of science
Three major developments have encouraged rapid advances in the science of science. The first is in data 9: modern databases include millions of research articles, grant proposals, patents and more ...
6 Papers Every Modern Data Scientist Must Read
This paper, released in early 2021 by OpenAI, is probably one of the greatest revolutions in zero-shot classification algorithms, presenting a novel model known as Contrastive Language-Image Pre-Training, or CLIP for short. CLIP was trained over a massive dataset of 400 million pairs of images and their corresponding captions, and has learnt to ...
Data Science Methodologies: Current Challenges and Future Approaches
data science research activities, along the implications of dif-ferent methods for executing industry and business projects. At present, data science is a young field and conveys the impres-Preprint submitted to Big Data Research - Elsevier January 6, 2020 arXiv:2106.07287v2 [cs.LG] 14 Jan 2022
Scientific Data
Scientific Data is an open access journal dedicated to data, publishing descriptions of research datasets and articles on research data sharing from all areas ...
Ten Research Challenge Areas in Data Science
We then describe each of the 10 challenge areas. The goal of this article is to start a discussion on what could constitute a basis for a research agenda in data science, while recognizing that the field of data science is still evolving. Keywords: artificial intelligence, causal reasoning, computing systems, data life cycle, deep learning ...
Data science and decision analytics
In this special volume of Annals of Operations Research, the research papers seek to integrate methods and concepts between operations research, data science, and decision analytics.The decision-making capabilities of operations research methods can enhance the learning and representation of patterns and structure in data science.
New data science tool greatly speeds up molecular analysis of our
A research team led by scientists at the University of California, Riverside, has developed a computational workflow for analyzing large data sets in the field of metabolomics, the study of small molecules found within cells, biofluids, tissues, and entire ecosystems. Most recently, the team applied ...
Research articles
A comprehensive dataset of pattern electroretinograms for ocular electrophysiology research. Itziar Fernández. Rubén Cuadrado-Asensio. Rosa M. Coco-Martín. Data Descriptor Open Access 18 Sept 2024.
Open Data
Open Data is a strategy for incorporating research data into the permanent scientific record by releasing it under an Open Access license. Whether data is deposited in a purpose-built repository or published as Supporting Information alongside a research article, Open Data practices ensure that data remains accessible and discoverable.
A comprehensive assessment approach for multiscale regional economic
Zhang and Pfoser (2019) demonstrated the utility of OSM-POI data, especially its temporal aspects (change sets), in urban science research by analyzing the POIs of coffee shops in Manhattan, highlighting the accuracy, coverage, and trend value of POI data. Feldmeyer (2020) used the attribute values of OSM data to generate four socio-economic ...
[2409.12722] LLM-Measure: Generating Valid, Consistent, and
The increasing use of text as data in social science research necessitates the development of valid, consistent, reproducible, and efficient methods for generating text-based concept measures. This paper presents a novel method that leverages the internal hidden states of large language models (LLMs) to generate these concept measures. Specifically, the proposed method learns a concept vector ...
When we talk about Big Data, What do we really mean? Toward a more
1 Department of Governance and Innovation, Campus Fryslan, University of Groningen, Leeuwarden, Netherlands; 2 Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, Netherlands; Despite the lack of consensus on an official definition of Big Data, research and studies have continued to progress based on this "no consensus ...
The use of bibliometrics in nursing science: Topics, data sources and
2.4. Data availability. The 129 articles analysed are listed in the Annex. They are referred to throughout the article by means of numbers in brackets. In addition, the data resulting from this research are freely available in comma‐separated values (CSV) format (Borrego & Mezquita, 2023). For each article, the dataset includes the topic of ...
2024 Hollander Distinguished Lecture: Reasoning from Data in Science
Robert E. Kass, the Maurice Falk University Professor of Statistics and Computational Neuroscience in the Department of Statistics and Data Science, the Machine Learning Department, and the Neuroscience Institute at Carnegie Mellon University, will present "Reasoning from Data in Science" at 11 a.m. in Duxbury Hall Room 214.
IMAGES
VIDEO
COMMENTS
As an open access platform of the Harvard Data Science Initiative, Harvard Data Science Review (HDSR) features foundational thinking, research milestones, educational innovations, and major applications, with a primary emphasis on reproducibility, replicability, and readability.We aim to publish content that helps define and shape data science as a scientifically rigorous and globally ...
Data Science . Information Use . Regulatory Compliance . Future Research . Public And Private . Social Good . Public And Private Sector . Effective Use. AbstractThe appetite for effective use of information assets has been steadily rising in both public and private sector organisations.
The data generated generally are retained for a shorter duration, and thus, extensive research into produced data is neglected. However, advancements in data science in the field of healthcare attempt to ensure better management of data and provide enhanced patient care [20-23].
The articles we have listed below were compiled and written by data science professors, experts, and practitioners within the field as well as based on professional research of the industry and related trends, opportunities, and projections.
VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS. The research paper is written by- James Duncan, RushKapoor, Abhineet Agarwal, Chandan Singh, Bin Yu. This research paper is more of a journal of open-source software than a study paper.
This paper shows data science's potential for disruptive innovation in science, industry, policy, and people's lives. We present how data science impacts science and society at large in the coming years, including ethical problems in managing human behavior data and considering the quantitative expectations of data science economic impact. We introduce concepts such as open science and e ...
Abstract. To drive progress in the field of data science, we propose 10 challenge areas for the research community to pursue. Since data science is broad, with methods drawing from computer science, statistics, and other disciplines, and with applications appearing in all sectors, these challenge areas speak to the breadth of issues spanning ...
Part 4 — Towards Mamba State Space Models for…. Read more…. 434. 8 responses. Read the latest stories published by Towards Data Science. Your home for data science. A Medium publication sharing concepts, ideas and codes.
Data science combines the power of computer science and applications, modeling, statistics, engineering, economy and analytics. Whereas a... | Explore the latest full-text research PDFs, articles ...
Data Science in Science is founded as an open access international journal that publishes original research, letters, and reviews at the intersection of Science and Data Science. Its aim is to advance: New ideas for experimental and observational data-driven learning and discovery that help address fundamental questions at the frontiers of ...
The CODATA Data Science Journal is a peer-reviewed, open access, electronic journal, publishing papers on the management, dissemination, use and reuse of research data and databases across all research domains, including science, technology, the humanities and the arts. The scope of the journal includes descriptions of data systems, their implementations and their publication, applications ...
Please select the appropriate Collection title "Innovations in Data Science Research for Future Computing Era" from the dropdown menu. Articles will undergo the journal's standard peer-review process and are subject to all the journal's standard policies. Articles will be added to the Collection as they are published.
Its application to more strained regions and populations (at scale) seems especially promising for education data science research going forward. Critique of Machine Learning Predictions. Were scholars to look at typical computer science outlets for data science articles, they would find a prevalence of machine learning models and efforts to ...
5. Data, analytics, and AI leaders are becoming less independent. This past year, we began to notice that increasing numbers of organizations were cutting back on the proliferation of technology and data "chiefs," including chief data and analytics officers (and sometimes chief AI officers).
This research contributes to the creation of a research vector on the role of data science in central banking. In , the authors provide an overview and tutorial on the data-driven design of intelligent wireless networks. The authors in provide a thorough understanding of computational optimal transport with application to data science.
Data Science and Management (DSM) is a peer-reviewed open access journal for original research articles, review articles and technical reports related to all aspects of data science and its application in the field of business, economics, finance, operations, engineering, healthcare, transportation, agriculture, energy, environment, sports, and ...
Three major developments have encouraged rapid advances in the science of science. The first is in data 9: modern databases include millions of research articles, grant proposals, patents and more ...
This paper, released in early 2021 by OpenAI, is probably one of the greatest revolutions in zero-shot classification algorithms, presenting a novel model known as Contrastive Language-Image Pre-Training, or CLIP for short. CLIP was trained over a massive dataset of 400 million pairs of images and their corresponding captions, and has learnt to ...
data science research activities, along the implications of dif-ferent methods for executing industry and business projects. At present, data science is a young field and conveys the impres-Preprint submitted to Big Data Research - Elsevier January 6, 2020 arXiv:2106.07287v2 [cs.LG] 14 Jan 2022
Scientific Data is an open access journal dedicated to data, publishing descriptions of research datasets and articles on research data sharing from all areas ...
We then describe each of the 10 challenge areas. The goal of this article is to start a discussion on what could constitute a basis for a research agenda in data science, while recognizing that the field of data science is still evolving. Keywords: artificial intelligence, causal reasoning, computing systems, data life cycle, deep learning ...
In this special volume of Annals of Operations Research, the research papers seek to integrate methods and concepts between operations research, data science, and decision analytics.The decision-making capabilities of operations research methods can enhance the learning and representation of patterns and structure in data science.
A research team led by scientists at the University of California, Riverside, has developed a computational workflow for analyzing large data sets in the field of metabolomics, the study of small molecules found within cells, biofluids, tissues, and entire ecosystems. Most recently, the team applied ...
A comprehensive dataset of pattern electroretinograms for ocular electrophysiology research. Itziar Fernández. Rubén Cuadrado-Asensio. Rosa M. Coco-Martín. Data Descriptor Open Access 18 Sept 2024.
Open Data is a strategy for incorporating research data into the permanent scientific record by releasing it under an Open Access license. Whether data is deposited in a purpose-built repository or published as Supporting Information alongside a research article, Open Data practices ensure that data remains accessible and discoverable.
Zhang and Pfoser (2019) demonstrated the utility of OSM-POI data, especially its temporal aspects (change sets), in urban science research by analyzing the POIs of coffee shops in Manhattan, highlighting the accuracy, coverage, and trend value of POI data. Feldmeyer (2020) used the attribute values of OSM data to generate four socio-economic ...
The increasing use of text as data in social science research necessitates the development of valid, consistent, reproducible, and efficient methods for generating text-based concept measures. This paper presents a novel method that leverages the internal hidden states of large language models (LLMs) to generate these concept measures. Specifically, the proposed method learns a concept vector ...
1 Department of Governance and Innovation, Campus Fryslan, University of Groningen, Leeuwarden, Netherlands; 2 Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, Netherlands; Despite the lack of consensus on an official definition of Big Data, research and studies have continued to progress based on this "no consensus ...
2.4. Data availability. The 129 articles analysed are listed in the Annex. They are referred to throughout the article by means of numbers in brackets. In addition, the data resulting from this research are freely available in comma‐separated values (CSV) format (Borrego & Mezquita, 2023). For each article, the dataset includes the topic of ...
Robert E. Kass, the Maurice Falk University Professor of Statistics and Computational Neuroscience in the Department of Statistics and Data Science, the Machine Learning Department, and the Neuroscience Institute at Carnegie Mellon University, will present "Reasoning from Data in Science" at 11 a.m. in Duxbury Hall Room 214.