CaltechAUTHORS
  A Caltech Library Service

DataJoint: managing big scientific data using MATLAB or Python

Yatsenko, Dimitri and Reimer, Jacob and Ecker, Alexander S. and Walker, Edgar Y. and Sinz, Fabian and Berens, Philipp and Hoenselaar, Andreas and Cotton, R. James and Siapas, Athanassios S. and Tolias, Andreas S. (2015) DataJoint: managing big scientific data using MATLAB or Python. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20181030-105013213

[img] PDF - Submitted Version
Creative Commons Attribution.

547Kb

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20181030-105013213

Abstract

The rise of big data in modern research poses serious challenges for data management: Large and intricate datasets from diverse instrumentation must be precisely aligned, annotated, and processed in a variety of ways to extract new insights. While high levels of data integrity are expected, research teams have diverse backgrounds, are geographically dispersed, and rarely possess a primary interest in data science. Here we describe DataJoint, an open-source toolbox designed for manipulating and processing scientific data under the relational data model. Designed for scientists who need a flexible and expressive database language with few basic concepts and operations, DataJoint facilitates multi-user access, efficient queries, and distributed computing. With implementations in both MATLAB and Python, DataJoint is not limited to particular file formats, acquisition systems, or data modalities and can be quickly adapted to new experimental designs. DataJoint and related resources are available at http://datajoint.github.com.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/031658DOIDiscussion Paper
ORCID:
AuthorORCID
Siapas, Athanassios S.0000-0001-8837-678X
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Record Number:CaltechAUTHORS:20181030-105013213
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20181030-105013213
Official Citation:DataJoint: managing big scientific data using MATLAB or Python Dimitri Yatsenko, Jacob Reimer, Alexander S Ecker, Edgar Y Walker, Fabian Sinz, Philipp Berens, Andreas Hoenselaar, Ronald James Cotton, Athanassios S. Siapas, Andreas S. Tolias bioRxiv 031658; doi: https://doi.org/10.1101/031658
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90496
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:30 Oct 2018 19:34
Last Modified:03 Oct 2019 20:25

Repository Staff Only: item control page