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Virtual data Grid middleware services for data-intensive science

Yong Zhao, Michael Wilde, Ian Foster, Jens Voeckler, James Dobson, Eric Gilbert, Thomas Jordan, Elizabeth Quigg
2006 Concurrency and Computation  
We describe the design and implementation of such middleware services in terms of a virtual data system interface called Chiron, and present virtual data integration examples from the QuarkNet education  ...  The GriPhyN Virtual Data System provides a suite of components and services for data-intensive sciences that enables scientists to systematically and efficiently describe, discover, and share large scale  ...  The GriPhyN Virtual Data System was implemented by Gaurang Mehta, Karan Vahi, Jens Voeckler, and Yong Zhao.  ... 
doi:10.1002/cpe.968 fatcat:pxtqiiyg6fdohli2hzqkv7ut5a

Fostering Computational Thinking Through Data Visualization and Design on Secondary School Students

Güldem Alev Özkök
2021 Journal of universal computer science (Online)  
This research aims to model the process of data visualization (DV) and design to facilitate computational thinking (CT) of secondary-level students.  ...  This research proposes a model to facilitate development of CT by DV with the analysis of complex data, creating an effective method by enabling analytics and visualizing data.  ...  Evaluate in practice phase: A total of 71% of the students stated they were able to understand the basic concepts of data visualization (data, data analytics, DV models, DV tools) well on their DV activities  ... 
doi:10.3897/jucs.66265 fatcat:oxtne25s6vdldosmiswvrvx4pe

An Analysis of Data Processing for Big Data Analytics

Steve Blair, Jon Cotter
2021 Journal of Computing and Natural Science  
The use of deep learning to Data Analytics is investigated. The benefits of integrating BDA, deep learning, HPC (High Performance Computing), and HC are highlighted.  ...  The need for high-performance Data Mining (DM) algorithms is being driven by the exponentially increasing data availability such as images, audio and video from a variety of domains, including social networks  ...  Section IV presents an overview of the conventional Machine Learning (ML), Big Data Analytics (BDA), and Data Mining (DM). Lastly, Section V draws the final remarks of research and recommendations.  ... 
doi:10.53759/181x/jcns202101019 fatcat:z5wjv3y2prfthk3l34xaz3hx6e

C¹ Positive Surface over Positive Scattered Data Sites

Farheen Ibraheem, Malik Zawwar Hussain, Akhlaq Ahmad Bhatti, Cheng-Yi Xia
2015 PLoS ONE  
Half of the parameters in the description of the interpolant are constrained to keep up the positive shape of data while the remaining half are set free for users' requirement.  ...  The aim of this paper is to develop a local positivity preserving scheme when the data amassed from different sources is positioned at sparse points.  ...  It is evident fromFig 10 that the positivity of data could not be conserved in visual model.  ... 
doi:10.1371/journal.pone.0120658 pmid:26057122 pmcid:PMC4461286 fatcat:abfpklo5a5cbjpm32tmfrig5ci

A Study of Hierarchical Correlation Clustering for Scientific Volume Data [chapter]

Yi Gu, Chaoli Wang
2010 Lecture Notes in Computer Science  
We also evaluate the three hierarchical clustering methods in terms of quality and performance.  ...  Correlation study is at the heart of time-varying multivariate volume data analysis and visualization.  ...  Wittenberg at NOAA for providing the climate data set. We also thank the anonymous reviewers for their helpful comments.  ... 
doi:10.1007/978-3-642-17277-9_45 fatcat:jrvhxprymzfnrf5ymt47eshb7q

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

O. Rubel, G.H. Weber, Min-Yu Huang, E.W. Bethel, M.D. Biggin, C.C. Fowlkes, C.L. Luengo Hendriks, S.V.E. Keranen, M.B. Eisen, D.W. Knowles, J. Malik, H. Hagen (+1 others)
2010 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii) evaluation of the number of clusters k in the context  ...  The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible.  ...  ACKNOWLEDGMENTS We thank the members of the Visualization and Computer Graphics Research Group at the Institute for Data Analysis and Visualization (IDAV) at the University of California, Davis, the members  ... 
doi:10.1109/tcbb.2008.49 pmid:20150669 fatcat:xisu6bdyuvduxc3fvhjg6dd42y

MedVir: An Interactive Representation System of Multidimensional Medical Data Applied to Traumatic Brain Injury's Rehabilitation Prediction [chapter]

Santiago Gonzalez, Antonio Gracia, Pilar Herrero, Nazareth Castellanos, Nuria Paul
2014 Lecture Notes in Computer Science  
to detect whether a patient may recover or not, and all of that in a quick and easy way through a visualization technique which allows interaction.  ...  Based on complex data mining techniques, this provides not only the differentiation between TBI patients and control subjects (with a 72% of accuracy using 0.632 Bootstrap validation), but also the ability  ...  One of the fields in which DR techniques for DV are currently very useful, is the scientific interactive visualization field, or Visual Analytics (VA).  ... 
doi:10.1007/978-3-319-08729-0_24 fatcat:iaoc4naeorbflcm2g75arp46km

A Multiple Imputation Strategy for Eddy Covariance Data

D. Vitale, M. Bilancia, D. Papale
2018 Journal of Environmental Informatics  
By using EC measurements that are part of the FLUXNET2015 dataset, we evaluate the performance of a multiple imputation (MI) strategy based on an efficient computational strategy introduced in Honaker  ...  a high percentage of missing data.  ...  DV conceived the study; DV and DP contributed to the study design; DV, MB and DP wrote the first draft of the manuscript.  ... 
doi:10.3808/jei.201800391 fatcat:43pqgxrh4jbmtf3pcljp4cmcni

The affordance of virtual reality to enable the sensory representation of multi-dimensional data for immersive analytics: from experience to insight

Jules Moloney, Branka Spehar, Anastasia Globa, Rui Wang
2018 Journal of Big Data  
The focus of the early use of CAVE was on scientific visualization, with relatively minimal research into data visualization.  ...  [20, 21] , which in our view is one of the earliest and most comprehensive evaluations of virtual reality for visual data mining.  ...  Abbreviations CAVE: computer aided virtual environment; EDA: exploratory data analysis; HCI: human computer interfaces; HMD: head mounted display; VR: virtual reality; VDM: visual data mining.  ... 
doi:10.1186/s40537-018-0158-z fatcat:76o37al2lvfnrccazuegiwpmri

CORAL: COde RepresentAtion Learning with Weakly-Supervised Transformers for Analyzing Data Analysis [article]

Ge Zhang, Mike A. Merrill, Yang Liu, Jeffrey Heer, Tim Althoff
2020 arXiv   pre-print
to the builders of scientific toolkits.  ...  We then evaluate the model on a new classification task for labeling computational notebook cells as stages in the data analysis process from data import to wrangling, exploration, modeling, and evaluation  ...  To draw insights on the data science process, previous work has conceptualized the analysis pipeline as a sequence of discrete stages starting from importing libraries and wrangling data to evaluation  ... 
arXiv:2008.12828v1 fatcat:64bnnp5hsvgzleyp2r3a2lfag4

Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

Robert Eckardt, Christian Berger, Christian Thiel, Christiane Schmullius
2013 Remote Sensing  
For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed.  ...  A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations.  ...  Conflict of Interest The authors declare no conflict of interest.  ... 
doi:10.3390/rs5062973 fatcat:riamii2xrzg5noivirk22qu7ee

Relational Collaborative Topic Regression for Recommender Systems

Hao Wang, Wu-Jun Li
2015 IEEE Transactions on Knowledge and Data Engineering  
Collaborative topic regression (CTR) is one of these methods which has achieved promising performance by successfully integrating both feedback information and item content information.  ...  Due to this sparsity problem, traditional CF with only feedback information will suffer from unsatisfactory performance.  ...  We evaluate the predictive performance with two cases: Q ¼ 10% and Q ¼ 100%.  ... 
doi:10.1109/tkde.2014.2365789 fatcat:wxxjxrcbgvgr3d6ap76p4eihn4

Experimental neutron spectroscopy data visualization: Adaptive tessellation algorithm

I. Bustinduy, F. J. Bermejo, T. G. Perring, G. Bordel
2007 Review of Scientific Instruments  
We report on an adaptive binning approach designed for data visualization within scientific disciplines where counting statistics are expected to follow Poisson distributions.  ...  Our main focus of interest concerns, however, neutron spectroscopy data from single-crystal samples where signals span a four-dimensional space defined by three spatial coordinates plus time.  ...  Finally, and on a broader scope, the work reported here provides a contribution of interest to the general field of scientific visualization where, as mentioned not long ago 27, 28 not only do the data  ... 
doi:10.1063/1.2722398 pmid:17477675 fatcat:ujo4fgovmfdnxkasjqgtfhxh5e

Analyzing and Evaluating Data Freshness in Data Integration Systems

Verónika Peralta, Raúl Ruggia, Mokrane Bouzeghoub
2004 Ingénierie des Systèmes d'Information  
values are aggregated(Figure 4.3e), e.g. dv 1 ''=2 (minimum of dv 1 and dv 1 ') and f 1 ''= 240 (δ 1 '' * dv 1 '').  ...  Quality evaluation performance In this test we analyze quality evaluation performance.  ... 
doi:10.3166/isi.9.5-6.145-162 fatcat:mby7k2jdvbe2tfwh3adeeu2qky

Paths Explored, Paths Omitted, Paths Obscured: Decision Points Selective Reporting in End-to-End Data Analysis [article]

Yang Liu, Tim Althoff, Jeffrey Heer
2019 arXiv   pre-print
Drawing reliable inferences from data involves many, sometimes arbitrary, decisions across phases of data collection, wrangling, and modeling.  ...  In concert with our interviews, we also contribute visualizations for communicating decision processes throughout an analysis.  ...  We also thank Alex Kale, Eunice Jun, Rene Just, Tongshuang Wu, anonymous reviewers, and members of the Interactive Data Lab for their feedback.  ... 
arXiv:1910.13602v2 fatcat:2ts2rql27vhfbefxiavhomk76q
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