Abstract.Websites that provide content creation and sharing features have become quite popular recently. These sites allow users to categorize and browse content using 'tags' or free-text keyword topics. Since users contribute and tag social media content across a variety of social web platforms, creating new knowledge from distributed tag data has become a matter of performing various tasks, including publishing, aggregating, integrating, and republishing tag data. However, there are a number of issues in relation to data sharing and interoperability when processing tag data across heterogeneous tagging platforms. In this paper we introduce a semantic tag model that aims to explicitly offer the necessary structure, semantics and relationships between tags. This approach provides an improved opportunity for representing tag data in the form of reusable constructs at a semantic level. We also demonstrate a prototype that consumes and makes use of shared tag metadata across heterogeneous sources.
Abstract. Tagging has proven to be a successful and efficient way for creating metadata through a human collective intelligence. It can be considered not only an application of individuals for expressing one's interests, but also as a starting point for leveraging social connections through collaborative user participations. A number of users have contributed to tag resources in web sites such as Del.icio.us, Flickr etc.However, there is no uniform structure to describe tags and user's activities. This makes difficult to share and represent tag data among people. The SCOT (Social Semantic Cloud of Tags) ontology is aimed to represent the structure and semantics of a set of tags and promotes their global sharing. The paper introduce the SCOT ontology and methods of its representation.
Knowledge workers have different applications and resources in heterogeneous environments for doing their knowledge tasks and they often need to solve a problem through combining several resources. Typical personal knowledge management (PKM) systems do not provide effective ways for representing knowledge worker's unstructured knowledge or idea. In order to provide better knowledge activity for them, we implement Wiki-based sociAl Network Thin client (WANT) that is a wiki-based semantic tagging system for collaborative and communicative knowledge creation and maintenance for a knowledge worker. And also, we suggest the social semantic cloud of tags (SCOT) ontology to represent tag data at a semantic level and combine this ontology in WANT. WANT supports a wide scope of social activities through online mash-up services and interlink resources with desktop and web environments. Our approach provides basic functionalities such as creating, organising and searching knowledge at individual level, as well as enhances social connections among knowledge workers based on their activities.
Open data is an important element in a variety of new industries, such as artificial intelligence and smart cities. While the South Korean government is continuously releasing new data on the public data portal, it is limited in the accomplishment of the goals such as job creation and the new economic leaps expected by the Korean government. From a data point of view, this limitation is due to a lack of data that users require and a lot of lowquality data to use. This paper analyses standard terms used in public data. The findings of this study reveals that standard vocabularies established by the government require updates to reflect the nature of public data, and the relevant laws and guidelines need to be revised.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.