A framework for cross-datasources agricultural research-to-impact analysis

Agricultural research is a very important activity for developing countries as its economy relies on the agricultural sector. To ensure that the investment in the research is in the right direction, it is necessary to determine the relationship between trade values and invested research. However, the effective and efficient evaluation is constrained by the complexity and fragmentation of information required for analysis. The large number of agricultural products and related research items occurred between the time research grants were allocated and the time of the trade, such as research projects, publications, intellectual property, etc. mean that the amount of data to be processed is enormous and is responsible by many organizations. The data which are collected and stored in different databases are uncoordinated and there are seldom explicit links between records, both within and across databases. The only research item with direct links is research publication and even that is rarely attributed directly to research grants.In this paper, we propose a framework for cross-datasources analysis for agricultural products. The data are automatically collected from official sources of agricultural data and stored into a unified database to eliminate dependencies between the visualization and structure of datasources. The pathways are recognized by analyzing links between items among their parameters, such as names, affiliations, etc. The framework is demonstrated by analyzing agricultural research activities in Thailand. The total number of gathered data records is approximately 8.8 million records. Visualization of research-to-impact pathways of two agricultural products (pineapple and sugarcane) are used as case study.