Jung, Segun
Chard, Kyle
D'Arcy, Mike
Heavner, Ben
Foster, Ian
Kesselman, Carl
Madduri, Ravi
Rodriguez, Alexis
Soiland-Reyes, Stian
Goble, Carole
Clark, Kristi
Deutsch, Eric W.
Dinov, Ivo
Price, Nathan
Toga, Arthur
2016-12-05
<p><em>Big data workflows</em> often require the assembly and exchange of complex, multi-element datasets. For example, in biomedical applications, the input to an analytic pipeline can be a dataset consisting thousands of images and genome sequences assembled from diverse repositories, requiring a description of the contents of the dataset in a concise and unambiguous form. Typical approaches to creating datasets for big data workflows assume that all data reside in a single location, requiring costly data marshaling and permitting errors of omission and commission because dataset members are not explicitly specified.</p>
<p>We address these issues by proposing simple methods and tools for assembling, sharing, and analyzing large and complex datasets that scientists can easily integrate into their daily workflows. These tools combine a simple and robust method for describing data collections (<strong>BDBags</strong>), data descriptions (<strong>Research Objects</strong>), and simple persistent identifiers (<strong>Minids</strong>) to create a powerful ecosystem of tools and services for big data analysis and sharing.</p>
<p>We present these tools and use biomedical case studies to illustrate their use for the rapid assembly, sharing, and analysis of large datasets.</p>
https://doi.org/10.1109/BigData.2016.7840618
oai:zenodo.org:820878
IEEE
https://static.aminer.org/pdf/fa/bigdata2016/BigD418.pdf
https://www.research.manchester.ac.uk/portal/files/45989205/bagminid.pdf
http://bd2k.ini.usc.edu/tools/
https://github.com/ini-bdds/bdbag
https://www.research.manchester.ac.uk/portal/en/publications/ill-take-that-to-go(8335e672-1d85-4649-a245-56fbdb1bd423).html
https://w3id.org/ro/bagit
https://zenodo.org/communities/linkeddata
https://zenodo.org/communities/eu
https://zenodo.org/communities/bioexcel
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Big Data, 2016 IEEE International Conference on Big Data, Washington, DC, USA, 2016-12-05 / 2016-12-08
Big Data
data analysis
BDBags
Big Data analysis
Big Data bags
Big Data sharing
Minid
data assembling
data collections
data descriptions
datasets
identifiers
research objects
Encoding
Metadata
Payloads
Robustness
Software
Uniform resource locators
bdbag
I'll take that to go: Big data bags and minimal identifiers for exchange of large, complex datasets
info:eu-repo/semantics/conferencePaper