Abstract: There has been considerable growth in citizen science in academic contributions—researches by the paradigms of different disciplines and by the activities of citizens when undertaking data collecting, data processing, and data analyzing for disseminating results. These researches have proved the importance of data management practices—urgent to carry out the data life cycle. This study aims to analyze the scientific data contribution of citizen science under the data life cycle approach. It investigates 1,020 citizen science projects within the DataONE life cycle framework, which includes data management plan, data collection, data quality assurance, data documentation, data discovery, data integration, data preservation, and data analysis. As the major finding, the result of this study shows that the data management plan is developed with the leading of universities, which are the host of the majority of citizen science projects. The processes of data collection, data quality assurance, data documentation, data preservation, and data analysis are well organized with the systematic tool in the Information and Communications Technology (ICT) age; meanwhile the citizen science projects are cumulative. Data discovery has mostly linked with SciStarter (citizen science community site) and Facebook (social media). In data integration, it is found that most of the projects integrate with global observation. Finally, the study provides the process and procedure of citizen science data management in an effort to contribute the scientific data and the design of data life cycle to academic and governmental works.

Keywords: data management, citizen science, data life cycle, crowdsourcing, hybrid tasks, DataONE