Integrating Blockchain for Data Sharing and Collaboration Support in Scientific Ecosystem Platform

Simple item page
dc.contributor.authorCoelho, Raiane
dc.contributor.authorBraga, Regina
dc.contributor.authorDavid, José Maria
dc.contributor.authorDantas, Mário
dc.contributor.authorStroele, Victor
dc.contributor.authorCampos, Fernanda
dc.date.accessioned2020-12-24T19:01:04Z
dc.date.available2020-12-24T19:01:04Z
dc.date.issued2021-01-05
dc.description.abstractNowadays, scientific experiments are conducted in a collaborative way. In collaborative scientific experiments, aspects such interoperability, privacy and trust in shared data should be considered to allow the reproducibility of the results. A critical aspect associated with a scientific process is its provenance information, which can be defined as the origin or lineage of the data that helps to understand the results of the scientific experiment. Other concern when conducting collaborative experiments, is the confidentiality, considering that only properly authorized personnel can share or view results. In this paper, we propose BlockFlow, a blockchain-based architecture with the aim of bringing reliability to the collaborative research, considering the capture, storage and analysis of provenance data related to a scientific ecosystem platform (E-SECO).
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.031
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70642
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCollaboration for Data Science
dc.subjectblockchain
dc.subjecte-science.
dc.subjectprovenance
dc.subjectscientific collaboration
dc.titleIntegrating Blockchain for Data Sharing and Collaboration Support in Scientific Ecosystem Platform
prism.startingpage264

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0027.pdf
Size:
1.23 MB
Format:
Adobe Portable Document Format
Download

Collections

Collaboration for Data Science