id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-151118-25cbus1m	Murray, Benjamin	Accessible Data Curation and Analytics for International-Scale Citizen Science Datasets	2020-11-02		.txt	text/plain	4954	256	58	To test the performance of the join operator when ExeTera and Pandas are used, we generate a dataset composed of a left primary key (int64), a right foreign key (int64) and 1, 2, 4, 8, 16 , and 32 fields respectively of random numbers corresponding to entries in the right table (int32). In this work, we present ExeTera, a data curation and analytics tool designed to provide users with a low complexity solution for working on datasets approaching terabyte scale, such as national / international-scale citizen science datasets like the Covid Symptom Study. ExeTera provides features for cleaning, journaling, and generation of reproducible processing and analytics, enabling large research teams to work with consistent measures and analyses that can be reliably recreated from the base data snapshots. Although ExeTera was developed to provide data curation for researchers working on the Zoe Symptom Study, this software is being developed to be generally applicable to large-scale relational datasets for researchers who work in Python.	./cache/cord-151118-25cbus1m.txt	./txt/cord-151118-25cbus1m.txt