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AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

Creator:

Harper, Lisa, Campbell, Jacqueline, Cannon, Steve, Carson, James, Condon, Bradford, Cooper, Laurel, Dunn, Nathan, Elsik, Christine G., Farmer, Andrew, Ficklin, Stephen P., Grant, David, Grau, Emily, Cannon, Ethalinda K. S., Herndon, Nic, Hu, Zhi-Liang, Humann, Jodi, Jaiswal, Pankaj, Jonquet, Clement, Laporte, Marie-Angelique, Larmande, Pierre, Lazo, Gerard, McCarthy, Fiona, Menda, Naama, Jung, Sook, Mungall, Christopher J., Munoz-Torres, Monica C., Naithani, Sushma, Nelson, Rex, Nesdill, Daureen, Park, Carissa, Reecy, James, Reiser, Leonore, Sanderson, Lacey-Anne, Sen, Taner Z., Poelchau, Monica, Staton, Margaret, Subramaniam, Sabarinath, Tello-Ruiz, Marcela Karey, Unda, Victor, Unni, Deepak, Wang, Liya, Ware, Doreen, Wegrzyn, Jill, Williams, Jason, Woodhouse, Margaret, Walls, Ramona, Yu, Jing, Main, Doreen, Andorf, Carson, Arnaud, Elizabeth, Berardini, Tanya Z., and Birkett, Clayton

Abstract:

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require datamanagement plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated...

Resource Type:

Article

Full Text:

, Steve Cannon1, James Carson9, Bradford Condon10, Laurel Cooper11, Nathan Dunn12, Christine G. Elsik13