Filters








3,200,972 Hits in 3.2 sec

Towards Data Science

Yangyong Zhu, Yun Xiong
2015 Data Science Journal  
Providing natural and social sciences with data technologies and methods and exploring datanature can and should lead the transition towards this new science, data science.  ...  On the one hand, data science supports natural science and social science. Dealing with data is one of the driving forces behind data science.  ...  Data related research can and should lead the transition towards this new science -data science.  ... 
doi:10.5334/dsj-2015-008 fatcat:myvwa6pfkje6vgrsaszffeeyye

TOWARD HOLISTIC DATA SCIENCE EDUCATION

RICHARD DE VEAUX, ROGER HOERL, RON SNEE, PAUL VELLEMAN
2022 Statistics Education Research Journal  
We argue that data science education must move toward a holistic curriculum, and we provide examples and reasons for this emphasis.  ...  Holistic data science education places data science in the context of real world applications, emphasizing the purpose for which data were collected, the pedigree of the data, the meaning inherent in the  ...  TOWARDS A HOLISTIC APPROACH Many of the current limitations of data science arise from the simple fact that it is not truly a science (Donoho, 2017) . Or, perhaps we should say, not yet a science.  ... 
doi:10.52041/serj.v21i2.40 fatcat:cvc3pomrara2bborc2qttzeieq

Augmented Data Science: Towards Industrialization and Democratization of Data Science [article]

Huseyin Uzunalioglu, Jin Cao, Chitra Phadke, Gerald Lehmann, Ahmet Akyamac, Ran He, Jeongran Lee, Maria Able
2019 arXiv   pre-print
In this paper, we introduce our solution, Augmented Data Science (ADS), towards addressing this "human bottleneck" in creating value from diverse datasets.  ...  ADS is a data-driven approach and relies on statistics and ML to extract insights from any data set in a domain-agnostic way to facilitate the data science process.  ...  In this paper, we introduce Augmented Data Science (ADS) towards removing this human bottleneck. Our goal is to industrialize and democratize data science.  ... 
arXiv:1909.05682v1 fatcat:gpbwzdmjpzcjpokwarhxuuhd7y

Data Management for Data Science - Towards Embedded Analytics

Mark Raasveldt, Hannes Mühleisen
2020 Conference on Innovative Data Systems Research  
The rise of Data Science has caused an influx of new users in need of data management solutions.  ...  In this work, we describe the unique challenges and opportunities w.r.t workloads, resilience and cooperation that are faced by this new class of systems and the steps we have taken towards addressing  ...  INTRODUCTION The rise of Data Science has considerably increased the complexity of data analysis tasks. As a result, these tasks require more advanced tools than standard SQL queries [11] .  ... 
dblp:conf/cidr/RaasveldtM20 fatcat:vvsdxrwvqvdi7l7p3zrrb3mdee

Depth Self-Optimized Learning Toward Data Science [article]

Ziqi Zhang
2021 arXiv   pre-print
Conclusion and Perspective We propose DSOL for data science.  ...  1.301 3.140 3.0 8.225 10.300 10.0 23.073 25.889 25 49.090 51.984 50.0 59.011 62.214 60.0 97.988 101.951 100.0 https://github.com/workharduwillwin/Depth-Self-Optimized-Learning-Toward-Data-Science  ... 
arXiv:2011.02842v2 fatcat:r4ojd3uhqfbhtpzbbsvrbykp5q

Python: A Quintessential approach towards Data Science

Aniket M. Wazarkar
2021 International Journal for Research in Applied Science and Engineering Technology  
Python is an interpreted object-oriented programming language that is sustainably procuring vogue in the field of data science and analytics by fabricating complex software applications.  ...  Data scientists have to deal with the exceedingly large amount of data alias as big data.  ...  for data science.  ... 
doi:10.22214/ijraset.2021.35683 fatcat:pf67f6un6rghvaibjbolnztqmu

Towards Spatial Data Science: Bridging the Gap between GIS, Cartography and Data Science

Jan Wilkening
2019 Abstracts of the International Cartographic Association  
</p><p>To bridge the gap between spatial sciences (such as GIS and cartography) and data science, we need an integrated framework of "spatial data science" (Figure 2).  ...  </p><p>Spatial data science could become the core competency of GIScientists and cartographers who are willing to integrate methods from the data science knowledge stack.  ...  Figure 2 . 2 Spatial Data Science at the interface between Spatial Science and Data Science.  ... 
doi:10.5194/ica-abs-1-403-2019 fatcat:35zsfevnnbfzxaiikxodys266a

Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications

Iqbal Sarker
2018 EAI Endorsed Transactions on Scalable Information Systems  
Based on the availability of mobile phone data, and the usefulness of data-driven applications, in this paper, we discuss about mobile data science that involves in collecting the mobile phone data from  ...  We also highlight the key elements and explain various key modules involving in the process of mobile data science.  ...  On the other hand, computing is moving toward pervasive, ubiquitous environments [17] .  ... 
doi:10.4108/eai.13-7-2018.155866 fatcat:mmniqyxp7falxnzrtpu237n4xq

Surgical Data Science – from Concepts toward Clinical Translation [article]

Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya, Keno März, Toby Collins, Anand Malpani, Johannes Fallert, Hubertus Feussner, Stamatia Giannarou, Pietro Mascagni, Hirenkumar Nakawala, Adrian Park (+38 others)
2021 arXiv   pre-print
Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data.  ...  Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery.  ...  science] AND [surgery] or [surgical data science].  ... 
arXiv:2011.02284v2 fatcat:i5mq42uevjfxjmji5xdap3kgse

Surgical Data Science - from Concepts toward Clinical Translation

Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya, Keno März, Toby Collins, Anand Malpani, Johannes Fallert, Hubertus Feussner, Stamatia Giannarou, Pietro Mascagni, Hirenkumar Nakawala, Adrian Park (+39 others)
2021 Medical Image Analysis  
Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data.  ...  Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery.  ...  Surgical Data Science -from Concepts toward Clinical Translation Surgical Data Science -from Concepts Clinical Translation Surgical Data Science -from Concepts Clinical Translation Surgical Data Science  ... 
doi:10.1016/j.media.2021.102306 pmid:34879287 pmcid:PMC9135051 fatcat:4n27fogyqndghlc2e54h7uohgq

Agnostic Science. Towards a Philosophy of Data Analysis

D. Napoletani, M. Panza, D. C. Struppa
2010 Foundations of Science  
This is the perspective we propose to call agnostic science, and we argue that, rather than diminishing or flattening the role of mathematics in science, the lack of isomorphisms with phenomena liberates  ...  We argue that the modus operandi of data analysis is implicitly based on the belief that if we have collected enough and sufficiently diverse data, we will be able to answer most relevant questions concerning  ...  In our view the changes brought by the methods of data analysis are not simply an issue of automated versus human science.  ... 
doi:10.1007/s10699-010-9186-7 fatcat:5a2yyicsdzh4vgpqxfflwmubxe

Beyond NGS data sharing and towards open science [article]

Bruno Dantas, Calmenelias Fleitas, Alexandre P. Francisco, José Simão, Cátia Vaz
2016 arXiv   pre-print
The NGSPipes framework and underlying architecture provides a major step towards open science and true collaboration in what concerns tools and pipelines among computational biology researchers and practitioners  ...  And although our motivation comes from biosciences, the following is true for many areas of science: published results are usually hard to reproduce either because data is not available or tools are not  ...  Discussion Although much NGS data have been published and shared in recent years, we cannot yet talk about open science.  ... 
arXiv:1701.03507v1 fatcat:wvgmkef2rjcyvibkn5qfuqtu7m

Deep feature synthesis: Towards automating data science endeavors

James Max Kanter, Kalyan Veeramachaneni
2015 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)  
We entered the Data Science Machine in 3 data science competitions that featured 906 other data science teams. Our approach beats 615 teams in these data science competitions.  ...  In this paper, we develop the Data Science Machine, which is able to derive predictive models from raw data automatically.  ...  We can see this in Figure 8 , where the Data Science Machine scores toward the end of the plateau. At some point, moving up the leader board might not be worth the cost required to do so.  ... 
doi:10.1109/dsaa.2015.7344858 dblp:conf/dsaa/KanterV15 fatcat:ir45igp6y5e2didlbtxpkgn6jq

Towards cognitively plausible data science in language research

Petar Milin, Dagmar Divjak, Strahinja Dimitrijević, R. Harald Baayen
2016 Cognitive Linguistics  
structures from information science such as hash tables, linked lists, letter trees or information gain trees.  ...  The field now abounds with studies that use statistical classification models to analyse either textual corpus data or behavioural experimental data.  ... 
doi:10.1515/cog-2016-0055 fatcat:lgivxxh5xretll4td5667qeata

Towards Science With Lsst: Data Products And Communication

Melissa Graham
2017 Zenodo  
Participants left the workshop empowered to continue on their path towards science with LSST.  ...  answering the question of "How will I do my science with LSST data?"  ...  Workshop Goals: To move all workshop participants further towards answering the question of "How will I do my science with LSST data?"  ... 
doi:10.5281/zenodo.1067257 fatcat:k45lawtgiza3pakiayc5x3jj44
« Previous Showing results 1 — 15 out of 3,200,972 results