A4 Article in conference proceedings
Open Data Science




List of Authors: Lahti L.
Publisher: Springer Verlag
Publication year: 2018
Journal: Lecture Notes in Computer Science
Book title *: Advances in Intelligent Data Analysis XVII: 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings
Journal name in source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Title of series: Lecture Notes in Computer Science
Volume number: 11191
ISBN: 978-3-030-01767-5
eISBN: 978-3-030-01768-2
ISSN: 0302-9743

Abstract

The increasing openness of data, methods, and collaboration networks has
created new opportunities for research, citizen science, and industry.
Whereas openly licensed scientific, governmental, and institutional data
sets can now be accessed through programmatic interfaces, compressed
archives, and downloadable spreadsheets, realizing the full potential of
open data streams depends critically on the availability of targeted
data analytical methods, and on user communities that can derive value
from these digital resources. Interoperable software libraries have
become a central element in modern statistical data analysis, bridging
the gap between theory and practice, while open developer communities
have emerged as a powerful driver of research software development.
Drawing insights from a decade of community engagement, I propose the
concept of open data science, which refers to the new forms of research enabled by open data, open methods, and open collaboration.



Internal Authors/Editors

Downloadable publication

This is an electronic reprint of the original article.
This reprint may differ from the original in pagination and typographic detail. Please cite the original version.




Last updated on 2019-29-01 at 10:52