The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
An Overview and Implementation of Extraction-Transformation-Loading (ETL) Process in Data Warehouse (Case Study: Department of Agriculture)
Extraction-transformation-loading (ETL) process in data warehouse development perform data extraction from various resources, transform the data into suitable format and loadit into data warehouse storage. In the ETL process, there is data cleansing process function that handles redundancy, inconsistency and integrity data. ETL process will move data from the source to the integration layer (data store in data warehouse). In the integration layer, the data can be grouped into smaller scope and more specific for the requirement in other repositories called data marts. Reporting program of data warehouse will be associated with a data mart as its data source. In this research, the data warehouse is built to handle the ETL process. The data warehouse build metadata to support the process. The metadata construction for ETL processes will lead to ETL programs with high degree of reusability. The conclusion from this research is the use of dynamic ETL process (using metadata ETL) is required when ETL process is dealing with the operational system that still unstable and likely to change the database schema. Dynamic ETL process is also needed to address the increase requirement for report from the users.
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