Discovery of village resources in urban regeneration project based on big data analytics

In this study, we examined resources at the local level, conducted status research, and explored alternatives based on big data analytics to regenerate a village in a small area in an information communications technology-based urban regeneration project. In particular, we used big data analytics to analyze the current conditions of the local area and provided a case demonstrating how connecting with a local university for expertise could solve current local problems. The main results can be summarized in three dimensions. First, there is job creation in villages using woodworking. At the center of it, it is possible to link with youth entrepreneurship by using the clubs of the local university (Seangnori Research Institute). Quantitatively, it is possible to design offices and offline stores for the sale of developed products, and qualitatively, it can lead to company growth by increasing the business volume of pre-land transportation-type social enterprises and expansion of regional governance through regional exchanges. Second, in terms of providing new information and education, it is possible to provide the Chungnam Appropriate Technology Federation, a non-profit organization in the region, for smooth education and practice. In particular, it is possible to promote the growth of the council through continuous product development. It is possible to strengthen the cooperative system. Third, the effect of the influx of population within the region can be obtained. As publicity and awareness of the visionary workshop project have been expanded, the youth independent talent nurturing process is systematized, and from this, students graduating from local universities can lead to youth jobs in the local area without looking for jobs in other areas, forming a virtuous cycle system. To this end, we divided real estate big data into the categories of system, technology and data, law and policy, structured data of real estate information and unstructured data of social media, web log data, smart device, and real estate policy, development, appraisal, and local analysis to apply to the case area and suggest implications.