data science best papers






Data Science : Profession and Education
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Advanced analytics, data science , and new-generation artificial intelligence (AI) represent probably the most promising areas and directions in todays and near-futures Information and Communications Technology (ICT) and Science , Engineering and Technology (SET)

NumPy/SciPy Recipes for Data Science : Computing Nearest Neighbors
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Our discussion in this note will focus on the common case where xi, q ∈ Rm and is the Euclidean norm. We will also assume that n is of moderate size, say, up to O(106). Although our setting therefore seems somewhat limited, it is practically relevant. To see why, we remark the

Research challenges for data mining in science and engineering
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Department of Computer Science University of Illinois at Urbana-Champaign www.cs.uiuc.edu/~ hanj October 1 2007 Page 2. 10/17/2007 2 Why Data Mining in Science and Engineering Data is mounting up rapidly and is available! Giga-bytes → terabytes → peta-bytes in very fast

Bringing clarity to data science projects with decision modeling: A case study
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This organization is a global leader in information technology. Like many large companies, it has teams focusing on data science in organizations like marketing, engineering, supply chain, and IT. They also have a centralized business intelligence and analytics capability

Data Science with Microsoft SQL Server 2016
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R is one of the most popular, powerful data analytics languages and environments in use by data scientists. Actionable business data is often stored in Relational Database Management Systems (RDBMS), and one of the most widely used RDBMS is Microsoft SQL

Data science
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Course structure diagrams for illustrative purposes only. Refer to the UWA Handbook (handbooks. uwa. edu. au) for full details. 1: Not required by students with a pass in Mathematics: Methods ATAR or higher. 2: Students who choose to study Data Science as aHealthcare systems around the world are facing vast challenges in responding to trends of aging population, the rise of chronic diseases, resources constraints, and the growing focus of citizens on healthy living and prevention. Consequently, there is an increasing focus on

Outline and exercises for a novel introductory course in data science and visualization
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Data Science is an increasingly popular term for the deliberate, methodological study of the principles and techniques involved in the storage, management, mining, and visualization of large amounts of data , as used to solve problems in diverse domains. This paper provides a

Introduction to Data Science
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Page 1. Introduction to Data Science Rob Gould UCLA Department of Statistics rgould@stat.ucla. edu Page 2. Funded by the National Science Foundation as a partnership between UCLA Computer Science , UCLA Statistics, UCLA Center X, and Los Angeles Unified School District.Science is considered to rest upon four basic pillars. Traditionally, experiment and theory are considered as the first and second of these. Advances in computing power have driven simulation to become the third pillar. The development of large repositories of data so

Building an urban data science summer program at the university of washington escience institute
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During the Summer of 201 the University of Washington eScience Institute ran an interdisciplinary summer internship program focused on urban informatics, civic engagement, and data -intensive social science . Borrowing elements from the successful

Biomedicine as a data driven science
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Page 1. Biomedicine As A Data Driven Science Philip E. Bourne, PhD, FACMI Associate Director for Data Science National Institutes of Health National Data Integrity Conference Colorado State University 2015 Page 2. Office of Biomedical Data Science Mission Statement To use data The disciplines of Data Science and Big Data , coming hand in hand, form one of the rapidly growing areas of research, have already attracted attention of industry and business. The prominent characterization of the area highlighting the essence of the problems

ExpoDB: An Exploratory Data Science Platform.
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We are entering a new data era: on the one hand, we are witnessing an unprecedented explosion of data volume and variety; and on the other hand, the data is now becoming increasingly interconnected yet disconnected. To derive insights from data , there is a

KDD for Science Data Analysis: Issues and Examples.
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Tile analysis of tile massive data sets collected by scientific instruments demands automation as a prerequisite to analysis. There is an urgent need to create an intermediate level at which scientists can operate effectively; isolating them from the massive sizes and

A Data Science Environment for Legal Texts.
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Since the beginning of legal informatics, data analysis has been very attractive to the scientific community in different domains and areas. Modern algorithms and mining technologies are able to unveil structural, such as network-like features and semantic This book is a compilation of invited presentations and lectures that were presented at the Second Symposium of the International Chinese Statistical Association Canada Chapter (ICSA CANADA) held at the University of Calgary, Canada, August 4 2015 (http://www

The role of Statistics in Data Science , and vice versa
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There are two cultures in the use of statistical modeling to reach conclusions from data . One assumes that the data are generated by a given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown. The statistical community

Towards a data science collaboratory
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Data -driven research requires many people from different domains to collaborate efficiently. The domain scientist collects and analyzes scientific data , the data scientist develops new techniques, and the tool developer implements, optimizes and maintains existing techniques

Making Data Science Count In and For Education
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New data sources and analytic techniques have enabled educational researchers to ask new questions and work to address enduring problems. Yet, there are challenges to those learning and applying these methods. In this chapter, we provide an overview of a nascent

R a Global Sensation in Data Science
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The main objective of this paper is to expose the evolution of R, as the most used data analysis tool among statisticians and the academic researchers. Its flexibility and complexity simply gained the statisticians and data scientists. The paper examines some of the reasons

Data quality under a computer science perspective
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La qualità dei dati è una tematica affrontata in ambito statistico, gestionale, informatico, insieme a molti altri settori scientifici. Il presente articolo considera il problema della definizione della qualità dei dati dal punto di vista informatico. Sono comparate alcune

Improving reproducibility of data science experiments
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Data analysis in fundamental sciences nowadays is an essential process that pushes frontiers of our knowledge and leads to new discoveries. At the same time we can see that complexity of those analyses increases fast due to a) enormous volumes of datasets being

Public engagement with UK government data science : Propositions from a literature review of public engagement on new technologies
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While data is nothing new, in recent years there has been a revolution in the mechanisms of creating, collecting, processing, connecting, and applying data . In the United Kingdom (UK), the recent passing of the Investigatory Powers Act (Investigatory Powers Act 201 2016;

Usage of Visualization Techniques in Data Science Workflows
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The increasing interest in data science and data analytics lead to a growing interest in data visualization and exploratory visual data analysis. However, there is still a clear gap between new developments in visualization research, and the visualization techniques

Finding spatio-temporal patterns in earth science data
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This paper presents preliminary work in using data mining techniques to find interesting spatio-temporal patterns from Earth Science data . The data consists of time series measurements for various Earth science and climate variables (eg soil moisture

Organic data science : a task-centered interface to on-line collaboration in science
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Although collaborative activities are paramount in science , little attention has been devoted to supporting on-line scientific collaborations. Our work focuses on scientific collaborations that revolve around complex science questions that require significant coordination to

XAFS-A data analysis program for materials science
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1. INTRODUCTION Structural disorder is an important and common problem in materials science . Local probes such as XAFS offer advantages over methods relying on translational symmetry. However, extracting the structural information from EXAFS data is a challenge for

ASCENDS: Advanced data science toolkit for non- data scientists
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Recently, advances in machine learning and artificial intelligence have been playing more and more critical roles in a wide range of areas. For the last several years, industries have shown that how learning from data , identifying patterns and making decisions with minimal

The Cambridge handbook of earth science data
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earth science data by Paul Henderson. This handbook presents an indispensable compilation of fundamental facts and figures about the Earth. It brings together reliable physical, chemical, biological (source: Nielsen Book Data ). Publishers Summary.[

Recent Advancements in Study of Effects of Nano/Micro Additives on Solid Propellants Combustion by Means of the Data Science Methods.
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ABSTRACT The efforts of Russian-Indian research team for application of the data science methods, in particular, artificial neural networks for development of the multi-factor computational models for studying effects of additives properties on the solid rocket

Global health and data science : Future needs for tomorrows cardiologist
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Compared with other diseases, cardiovascular diseases (CVD) are responsible for the greatest burden of disease both globally1 and in the UK. 2 Drugs for CVD and its risk factors have always been represented in the list of international blockbuster drugs. Important

The Emerging Role of the Data Scientist and the experience of Data Science education at the University of Amsterdam
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The CF-DS includes common competences required for the successful work of Data Scientists in different work environments in industry and in research and throughout the whole career path. Future CF-DS development will include coverage of domain-specific

Survival analysis of the florida cancer data system: A data science project using stata
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This technical report provides a survival analysis of the Florida Cancer Data System (FCDS). The technical report consists of two chapters, an appendix, and a separate supplement. Chapter Data Management, states the problem of survival analysis and it creates theData Science is a multidisciplinary approach based mainly on the methods of statistics and computer science suitably supplemented by the knowledge of the different domains to meet the new challenges posed by the actual information society. Aim of Data Science is to

Skills Requirements of Business Data Analytics and Data Science Jobs: A Comparative Analysis
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Big data analytics is increasingly shaping the way organizations manage their decision- making processes, create new services and products, and gain competitive advantage. The demand for analytics and its applications is driving the expansion of information technology

Towards Behavioral Measures of Boundary Spanning Success: A Data Science Approach
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In recent years, the ability to mine, manage, and examine big data has sparked a strong interest among scholars and managers to leverage data science approaches for measuring and in turn enhancing the efficiency and effectiveness of various areas of knowledge

An Educational Data Science Approach Towards Prediction Of Student Performance
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This paper attempts to apply classification techniques on educational data to predict student performance during studies. Classification is one of the active techniques to find out potential hidden interesting patterns with in data sets. The aim is to help teachers focusing

School, teaching and family influence on student attitudes toward science : Based on TIMSS data for Cyprus
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The Third International Mathematics and Science Study (TIMSS) is the largest, most comprehensive and most ambitious comparative study of mathematics and science undertaken to date, with over half a million student participants from more than 40 countries

Data science for the detection of emerging music styles
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We present a music browsing service which allows users to discover emerging music styles in the United Kingdom. Postulating that an emerging music style is a product of four important factors (artists, genres, locations and fans), we give a brief overview of over 1 CSE PROJECTS

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