MINI-LD: Minimalist Consumption over Linked Data

نویسندگان

  • Jeff Z. Pan
  • Honghan Wu
چکیده

With the wide adoption of linked data idea and its rapid growth in recent years, we have witnessed vast increase of Linked Data datasets not only in the volume, but also in number of various domains and across different sectors. While such big semantic data are bringing in much more value than what we have ever seen, the challenges to consume such data also increase dramatically, which result with overwhelmed digital life for linked data consumers. In this paper, we propose the idea of adopting minimalist consumption over linked data by borrowing the idea of less is more from the popular minimalist living style in real life. We introduce our basic idea for such a preliminary minimalist consumption system (http://honghan.info/minild/), and describe the main functionalities and features towards this direction.

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تاریخ انتشار 2014