Matches in Ruben’s data for { ?s ?p "Video has become a first class citizen on the Web with broad support in all common Web browsers. Where with structured mark-up on webpages we have made the vision of the Web of Data a reality, in this paper, we propose a new vision that we name the Web(VTT) of Data, alongside with concrete steps to realize this vision. It is based on the evolving standards WebVTT for adding timed text tracks to videos and JSON-LD, a JSON-based format to serialize Linked Data. Just like the Web of Data that is based on the relationships among structured data, the Web(VTT) of Data is based on relationships among videos based on WebVTT files, which we use as Web-native spatiotemporal Linked Data containers with JSON-LD payloads. In a first step, we provide necessary background information on the technologies we use. In a second step, we perform a large-scale analysis of the 148 terabyte size Common Crawl corpus in order to get a better understanding of the status quo of Web video deployment and address the challenge of integrating the detected videos in the Common Crawl corpus into the Web(VTT) of Data. In a third step, we open-source an online video annotation creation and consumption tool, targeted at videos not contained in the Common Crawl corpus and for integrating future video creations, allowing for weaving the Web(VTT) of Data tighter, video by video."@en }
Showing triples 1 to 1 of
1
with 100 triples per page.
- publication abstract "Video has become a first class citizen on the Web with broad support in all common Web browsers. Where with structured mark-up on webpages we have made the vision of the Web of Data a reality, in this paper, we propose a new vision that we name the Web(VTT) of Data, alongside with concrete steps to realize this vision. It is based on the evolving standards WebVTT for adding timed text tracks to videos and JSON-LD, a JSON-based format to serialize Linked Data. Just like the Web of Data that is based on the relationships among structured data, the Web(VTT) of Data is based on relationships among videos based on WebVTT files, which we use as Web-native spatiotemporal Linked Data containers with JSON-LD payloads. In a first step, we provide necessary background information on the technologies we use. In a second step, we perform a large-scale analysis of the 148 terabyte size Common Crawl corpus in order to get a better understanding of the status quo of Web video deployment and address the challenge of integrating the detected videos in the Common Crawl corpus into the Web(VTT) of Data. In a third step, we open-source an online video annotation creation and consumption tool, targeted at videos not contained in the Common Crawl corpus and for integrating future video creations, allowing for weaving the Web(VTT) of Data tighter, video by video.".