Data are the backbone of science.This paper describes the construction of a complex database for social-ecological analysis in Mongolia.Funded through the National Science Foundation(NSF)Dynamics of Coupled Natural an...Data are the backbone of science.This paper describes the construction of a complex database for social-ecological analysis in Mongolia.Funded through the National Science Foundation(NSF)Dynamics of Coupled Natural and Human(CNH)Systems program,the Mongolian Rangelands and Resilience(MOR2)project focused on Mongolian pastoral systems,community adaptive capacity,and vulnerability to climate change.We examine the development of a complex,multi-disciplinary research database of data collected over a three-year period,both in the field and from other sources.This data set captures multiple types of data:ecological,hydrological and social science surveys;remotely-sensed data,participatory mapping,local documents,and scholarly literature.The content,structure,and organization of the database,development of data protocols and issues related to data access,sharing and long-term storage are described.We conclude with recommendations for long-term data management and curation from large multidisciplinary research projects.展开更多
基金supported by funds form the NSF Dynamics of Coupled and Human Systems(CNH)Program award BCS-1011801,The World Bank,USAID,American Association of University Women,Open Society Institute,Center for Collaborative Conservation,Colorado State University.
文摘Data are the backbone of science.This paper describes the construction of a complex database for social-ecological analysis in Mongolia.Funded through the National Science Foundation(NSF)Dynamics of Coupled Natural and Human(CNH)Systems program,the Mongolian Rangelands and Resilience(MOR2)project focused on Mongolian pastoral systems,community adaptive capacity,and vulnerability to climate change.We examine the development of a complex,multi-disciplinary research database of data collected over a three-year period,both in the field and from other sources.This data set captures multiple types of data:ecological,hydrological and social science surveys;remotely-sensed data,participatory mapping,local documents,and scholarly literature.The content,structure,and organization of the database,development of data protocols and issues related to data access,sharing and long-term storage are described.We conclude with recommendations for long-term data management and curation from large multidisciplinary research projects.
