Research Interests / Keywords
・Construction of Glocal Information Platform
・Development of area studies based on information science
・Research on long term preservation and utilization of academic data
|Construction of Glocal Information Platform|
An information platform for area studies has been constructed, operated and maintained to support research functions; (1) database building function (My database), (2) utilization function (My database API), (3) linking function (resource sharing system), and (4) application functions (spaciotemporal data processing tools). This information platform has been distinctive academic function of CSEAS, but it is difficult to handle open data and big data in recent years. For that reason, we begin reconstructing a new information platform by introducing the latest Web ontology technology. The new information platform aims to realize functions of (1) efficiently collecting, accumulating and managing the diverse and heterogeneous research big data, (2) efficiently and intelligently linking accumulated data and big data on the network, and (3)organizing and integrating domain knowledge of area studies using vocabularies.
Area studies, which have been developed as a knowledge system to understand areas, are forced to change its ways to design areas by linking and viewing global and local knowledge simultaneously, in response to the age of autonomous revitalization of areas and being aware of environment. The result of this research is to expand the knowledge of areas”” on which area studies stands and to provide information function to flexibly share and utilize them. In addition Kyoto University has accumulated one of the largest scale “knowledge of areas and this research will promote the access and utilization of society and researchers to these knowledge. Moreover this research is consistent with the open science policy promoted by government and industry. I believe that academic significance and social economic and cultural significance are high.
|Development of area studies based on information science|
A large amount of information related to are studies are distributed on the Web. It is no longer possible to collect and analyze this big data manually. Therefore, applying statistical and machine learning methods, we try to analyze and visualize big data. We also try to introduce quantitative models and combine them with the collected data, and to describe areas quantitatively.”
|Research on long term preservation and utilization of academic data|
In order to access the digital data accumulated in the database, “metadata” describing meaning and structure of a digital data is indispensable. “The information platform for area studies” operated by CSEAS includes more than 100 digital contents and metadata about area studies, and realizes to integrate 61 databases of 7 domestic and overseas institutions, which make CSEAS as an international information center for area studies. However, in order to realize advanced utilization of multilingual / multidisciplinary big data of area studies, advanced information processing using statics, artificial intelligence etc. is necessary, and in order to do this, computers have to interpret and share the meaning and structure of metadata (metadata schemas). This research will construct a metadata schema database to realize such functions.
As most of the academic databases don’t include metadata schemas, long-term use of data is difficult. Research on long-term use of digital data is an unexplored area in Japan, but this research is expected to make a breakthrough.”