Abstract
Many organizations are tasked with the collection and processing of large quantities of data from various measurement devices. Data reported from these sources are often not interoperable with datasets and software used by analysts and other organizations in the same field, introducing barriers for collaboration on large-scale projects. This poses a particular problem for cross-device comparisons and machine learning applications. To address these challenges, the open source Time-Series Data Pipelines (Tsdat) software was developed by a joint collaboration between Pacific Northwest National Laboratory, the National Renewable Energy Laboratory, and Sandia National Laboratories to facilitate collaboration and accelerate advancements in the Marine Energy domain through the development of an open-source ecosystem of tools. This paper will describe the Tsdat software and the data standards within which the framework operates. A beta version of the framework has been released and is currently being used by several projects in marine energy, wind energy, and building energy systems.
Original language | American English |
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Number of pages | 9 |
State | Published - 2022 |
Event | Oceans Conference - San Diego, CA Duration: 20 Sep 2021 → 23 Sep 2021 |
Conference
Conference | Oceans Conference |
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City | San Diego, CA |
Period | 20/09/21 → 23/09/21 |
Bibliographical note
See NREL/CP-5700-82499 for paper as published in proceedingsNREL Publication Number
- NREL/CP-5700-80561
Keywords
- big data
- data lake
- data standards
- interoperability
- open-source
- Python