TY - JOUR
T1 - Eleven quick tips for finding research data
AU - Khalsa, Siri Jodha
AU - Michener, William
AU - Psomopoulos, Fotis
AU - Wu, Mingfang
PY - 2018/4/1
Y1 - 2018/4/1
N2 - Over the past decades, science has experienced rapid growth in the volume of data available for research—from a relative paucity of data in many areas to what has been recently described as a data deluge [1]. Data volumes have increased exponentially across all fields of science and human endeavour, including data from sky, earth, and ocean observatories; social media such as Facebook and Twitter; wearable health-monitoring devices; gene sequences and protein structures; and climate simulations [2]. This brings opportunities to enable more research, especially cross-disciplinary research that could not be done before. However, it also introduces challenges in managing, describing, and making data findable, accessible, interoperable, and reusable by researchers [3].
AB - Over the past decades, science has experienced rapid growth in the volume of data available for research—from a relative paucity of data in many areas to what has been recently described as a data deluge [1]. Data volumes have increased exponentially across all fields of science and human endeavour, including data from sky, earth, and ocean observatories; social media such as Facebook and Twitter; wearable health-monitoring devices; gene sequences and protein structures; and climate simulations [2]. This brings opportunities to enable more research, especially cross-disciplinary research that could not be done before. However, it also introduces challenges in managing, describing, and making data findable, accessible, interoperable, and reusable by researchers [3].
U2 - https://doi.org/10.1371/journal.pcbi.1006038
DO - https://doi.org/10.1371/journal.pcbi.1006038
M3 - Article
JO - PLOS Computational Biology
JF - PLOS Computational Biology
ER -