Big Data Bags: A Scalable Packaging Format for Science

Mike D'Arcy, Kyle Chard, Ian Foster, Carl Kesselman, Ravi Madduri, Nickolaus Saint, Rick Wagner
2019 Workshop on Research Objects  
The need to describe and exchange large and complex data underlies the vast majority of science conducted today. Such needs arise when downloading data from a repository, moving data between remote locations, exchanging data between collaborators, and even publishing data as part of the publication process. While such examples are common, it is surprisingly difficult to describe and exchange data, and it is even more difficult when datasets are large and span multiple storage locations. To
more » ... locations. To address some of these challenges we proposed the Big Data Bag (BDBag) as a data packaging format for representing and describing complex, distributed, and large datasets. In this presentation, we outline the BDBag model and describe three scenarios in which it is currently being used
doi:10.5281/zenodo.3338725 dblp:conf/ro/DArcyCFKMSW19 fatcat:3oertb7mdngtto5f4eprcdaj2i