@inproceedings{c8f42ee4b3e040f09072e729638d8669,
title = "New data paradigms: From the crowd and back",
abstract = "Knowledge generation from citizens is becoming both more feasible as well as important. Data directly from individuals can be critical as it can add information beyond what is available otherwise. Crowdsourced data also is very amenable in open data efforts given the nature of its generation. In this talk I will describe several efforts in which we are generating crowdsourced knowledge from open data and using it to more readily improve knowledge in public health.",
keywords = "Crowdsourcing, inference algorithms, public healthcare",
author = "Rumi Chunara",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 5th IEEE International Conference on Big Data, Big Data 2017 ; Conference date: 11-12-2017 Through 14-12-2017",
year = "2017",
month = jul,
day = "1",
doi = "10.1109/BigData.2017.8258409",
language = "English (US)",
series = "Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3979--3980",
editor = "Jian-Yun Nie and Zoran Obradovic and Toyotaro Suzumura and Rumi Ghosh and Raghunath Nambiar and Chonggang Wang and Hui Zang and Ricardo Baeza-Yates and Ricardo Baeza-Yates and Xiaohua Hu and Jeremy Kepner and Alfredo Cuzzocrea and Jian Tang and Masashi Toyoda",
booktitle = "Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017",
}