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Deans, Andrew R. , Lewis, Suzanna E. , Huala, Eva , Anzaldo, Salvatore S. , Ashburner, Michael , Balhoff, James P. , Blackburn, David C. , Blake, Judith A. , Burleigh, J. Gordon , Chanet, Bruno , Cooper, Lauren D. , Courtot, Mélanie , Csösz, Sándor , Cul, Hong , Dahdul, Wasila , Das, Sandip , Dececchi, T. Alexander , Dettal, Agnes , Diogo, Rui , Druzinsky, Robert E. , Dumontier, Michel , Franz, Nico M. , Friedrich, Frank , Gkoutos, George V. , Haendel, Melissa , Harmon, Luke J. , Hayamizu, Terry F. , He, Yongqun , Hines, Heather M. , Ibrahim, Nizar , Jackson, Laura M. , Jaiswal, Pankaj , James-Zorn, Christina , Köhler, Sebastian , Lecointre, Guillaume , Lapp, Hilmar , Lawrence, Carolyn J. , Le Novère, Nicolas , Lundberg, John G. , Macklin, James , Mast, Austin R. , Midford, Peter E. , Mikó, István , Mungall, Christopher J. , Oellrich, Anika , Osumi-Sutherland, David , Parkinson, Helen , Ramírez, Martín J. , Richter, Stefan , Robinson, Peter N. , Ruttenberg, Alan , Schulz, Katja S. , Segerdell, Erik , Seltmann, Katja C. , Sharkey, Michael J. , Smith, Aaron D. , Smith, Barry , Specht, Chelsea D. , Squires, R. Burke , Thacker, Robert W. , Thessen, Anne , Fernandez-Triana, Jose , Vihinen, Mauno , Vize, Peter D. , Vogt, Lars , Wall, Christine E. , Walls, Ramona L. , Westerfeld, Monte , Wharton, Robert A. , Wirkner, Christian S. , Woolley, James B. , Yoder, Matthew J. , Zorn, Aaron M. , and Mabee, Paula
Abstract:
Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across...
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Article
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