Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

The Practice of Reproducible Research

Case Studies and Lessons from the Data-Intensive Sciences
TaschenbuchKartoniert, Paperback
368 Seiten
Englisch
University of California Presserschienen am17.10.2017
The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. Each of the thirty-one case studies in this volume describes the workflow that an author used to complete a real-world research project, highlighting how particular tools, ideas, and practices have been combined to support reproducibility. Authors emphasize the very practical how, rather than the why or what, of conducting reproducible research. Part 1 contains an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.mehr
Verfügbare Formate
TaschenbuchKartoniert, Paperback
EUR42,50
E-BookEPUBDRM AdobeE-Book
EUR30,49

Produkt

KlappentextThe Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. Each of the thirty-one case studies in this volume describes the workflow that an author used to complete a real-world research project, highlighting how particular tools, ideas, and practices have been combined to support reproducibility. Authors emphasize the very practical how, rather than the why or what, of conducting reproducible research. Part 1 contains an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.
Details
ISBN/GTIN978-0-520-29475-2
ProduktartTaschenbuch
EinbandartKartoniert, Paperback
Erscheinungsjahr2017
Erscheinungsdatum17.10.2017
Seiten368 Seiten
SpracheEnglisch
MasseBreite 149 mm, Höhe 228 mm, Dicke 25 mm
Gewicht500 g
Artikel-Nr.42650721
Verwandte Artikel

Inhalt/Kritik

Inhaltsverzeichnis
Contributors Preface: Nullius in Verba Philip B. Stark Introduction Justin Kitzes PART I: PRACTICING REPRODUCIBILITY Assessing Reproducibility Ariel Rokem, Ben Marwick, and Valentina Staneva The Basic Reproducible Workflow Template Justin Kitzes Case Studies in Reproducible Research Daniel Turek and Fatma Deniz Lessons Learned Kathryn Huff Building toward a Future Where Reproducible, Open Science Is the Norm Karthik Ram and Ben Marwick Glossary Ariel Rokem and Fernando Chirigati PART II: HIGH-LEVEL CASE STUDIES Case Study 1: Processing of Airborne Laser Altimetry Data Using Cloud-Based Python and Relational Database Tools Anthony Arendt, Christian Kienholz, Christopher Larsen, Justin Rich, and Evan Burgess Case Study 2: The Trade-Off between Reproducibility and Privacy in the Use of Social Media Data to Study Political Behavior Pablo Barberá Case Study 3: A Reproducible R Notebook Using Docker Carl Boettiger Case Study 4: Estimating the Effect of Soldier Deaths on the Military Labor Supply Garret Christensen Case Study 5: Turning Simulations of Quantum Many- Body Systems into a Provenance-Rich Publication Jan Gukelberger and Matthias Troyer Case Study 6: Validating Statistical Methods to Detect Data Fabrication Chris Hartgerink Case Study 7: Feature Extraction and Data Wrangling for Predictive Models of the Brain in Python Chris Holdgraf Case Study 8: Using Observational Data and Numerical Modeling to Make Scientific Discoveries in Climate Science David Holland and Denise Holland Case Study 9: Analyzing Bat Distributions in a Human- Dominated Landscape with Autonomous Acoustic Detectors and Machine Learning Models Justin Kitzes Case Study 10: An Analysis of Household Location Choice in Major US Metropolitan Areas Using R Andy Krause and Hossein Estiri Case Study 11: Analyzing Cosponsorship Data to Detect Networking Patterns in Peruvian Legislators José Manuel Magallanes Case Study 12: Using R and Related Tools for Reproducible Research in Archaeology Ben Marwick Case Study 13: Achieving Full Replication of Our Own Published CFD Results, with Four Diff erent Codes Olivier Mesnard and Lorena A. Barba Case Study 14: Reproducible Applied Statistics: Is Tagging of Therapist-Patient Interactions Reliable? K. Jarrod Millman, Kellie Ottoboni, Naomi A. P. Stark, and Philip B. Stark Case Study 15: A Dissection of Computational Methods Used in a Biogeographic Study K. A. S. Mislan Case Study 16: A Statistical Analysis of Salt and Mortality at the Level of Nations Kellie Ottoboni Case Study 17: Reproducible Workflows for Understanding Large-Scale Ecological Effects of Climate Change Karthik Ram Case Study 18: Reproducibility in Human Neuroimaging Research: A Practical Example from the Analysis of Diff usion MRI Ariel Rokem Case Study 19: Reproducible Computational Science on High-Performance Computers: A View from Neutron Transport Rachel Slaybaugh Case Study 20: Detection and Classification of Cervical Cells Daniela Ushizima Case Study 21: Enabling Astronomy Image Processing with Cloud Computing Using Apache Spark Zhao Zhang PART III: LOW-LEVEL CASE STUDIES Case Study 22: Software for Analyzing Supernova Light Curve Data for Cosmology Kyle Barbary Case Study 23: pyMooney: Generating a Database of Two-Tone Mooney Images Fatma Deniz Case Study 24: Problem-Specific Analysis of Molecular Dynamics Trajectories for Biomolecules Konrad Hinsen Case Study 25: Developing an Open, Modular Simulation Framework for Nuclear Fuel Cycle Analysis Kathryn Huff Case Study 26: Producing a Journal Article on Probabilistic Tsunami Hazard Assessment Randall J. LeVeque Case Study 27: A Reproducible Neuroimaging Workflow Using the Automated Build Tool Make Tara Madhyastha, Natalie Koh, and Mary K. Askren Case Study 28: Generation of Uniform Data Products for AmeriFlux and FLUXNET Gilberto Pastorello Case Study 29: Developing a Reproducible Workflow for Large-Scale Phenotyping Russell Poldrack Case Study 30: Developing and Testing Stochastic Filtering Methods for Tracking Objects in Videos Valentina Staneva Case Study 31: Developing, Testing, and Deploying Efficient MCMC Algorithms for Hierarchical Models Using R Daniel Turek Indexmehr

Autor

Justin Kitzes is Assistant Professor of Biology at the University of Pittsburgh.
Daniel Turek is Assistant Professor of Statistics at Williams College.
Fatma Deniz is Postdoctoral Scholar at the Helen Wills Neuroscience Institute and the International Computer Science Institute, and Data Science Fellow at the University of California, Berkeley.
Weitere Artikel von
Turek, Daniel
Hrsg.