Data storage and management related to soil carbon cycle by a NoSQL engine on a SQL platform - Joker Tao

The carbon dioxide (CO2) is the most important greenhouse gas contributing 60 % toward global warming, respectively (IPCC, 2007). The correlation management in researches which focus on greenhouse gases (GHG) emission and soil attributes require huge amount of data. These data are inducted from measuring devices directly or from systems which are used for experimental data storage and management. Generally, these data come from different database systems which use different data storage structure. &#x0D; The main objective of the present study was to discuss a non-relational databasing model called Joker Tao (JT) which provides Big Data management for soil data and their GHG production potential related to carbon cycle in relational-databasing environment (Oracle APEX).</jats:p

A novel data storage logic in the cloud [version 3; referees: 2 approved, 1 not approved]

Databases which store and manage long-term scientific information related to life science are used to store huge amount of quantitative attributes. Introduction of a new entity attribute requires modification of the existing data tables and the programs that use these data tables. A feasible solution is increasing the virtual data tables while the number of screens remains the same. The main objective of the present study was to introduce a logic called Joker Tao (JT) which provides universal data storage for cloud-based databases. It means all types of input data can be interpreted as an entity and attribute at the same time, in the same data table