TY  - JOUR
T1  - DataCon: Lessons Learned Enabling Easier Data Sharing,
Exploration and Fusion Building a DataCon AutoGenerator Module
AU - Cha, Kyung Jin AU - Kim, Hwa Jong 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 4
SP  - 981
EP  - 987
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.981.987
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.981.987
KW  - summarization
KW  -data fusion
KW  -Automatic metadata generation
KW  -metadata
KW  -tagging
KW  -DataCon
AB  - Data is transforming the world. Individuals, organizations, companies and governments are rushing
to build technologies that generate, manage and analyze ever-increasing amounts of data. However, sharing,
exploring and fusing datasets remain difficult and painful processes. We previously proposed a “DataCon”
system that supports easier data sharing, exploration and fusion of many types of datasets and announced a
3 years, 1 million USD project funded by the Korean government to develop a DataCon-based data sharing
platform. We now describe the lessons learned during our first phase of development: a proof of concept
DataCon AutoGenerator Module which takes in arbitrary datasets and automatically generates corresponding
DataCon objects. Specifically, the study describes several potential use cases for a DataCon-based data sharing
platform, explores how several popular data repositories organize their datasets, sketches a preliminary data
taxonomy to organize the DataCon repository, maps out a tentative technological development roadmap,
recounts lessons learned implementing the initial proof of concept and lists several potential avenues for future
research. We will use this study as a blueprint for future development and hope it also informs the work of
others who want to make working with data easier, accelerating our collective ability to transform the world with
data.
ER  -