Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Typo: 2028 -> 2008 #1

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion _pages/about.md
Original file line number Diff line number Diff line change
Expand Up @@ -29,4 +29,4 @@ In 2008, he, Stefano Ceri, Frank van Harmelen and Dieter Fensel identified this
> is it possible to make sense in real time of multiple, heterogeneous, gigantic and inevitably noisy and incomplete data streams in order to support the decision process of extremely large numbers of concurrent users?


Since 2028, the Stream Reasoning research community conducted investigations and wrote papers that envision, elaborate, evaluate and discuss many aspects of this research question. The Stream Reasoning community document that a) the Semantic Web stack can be extended so to incorporate streaming data and events as a first class objects, b) the Stream Reasoning task is feasible, c) the very nature of streaming data offers opportunities to optimize reasoning, d) a combination of deductive and inductive stream reasoning techniques can cope with incomplete and noisy data. The mature Stream Reasoning solutions got deployed in real scenarios such as Smart City, Social Media Analytics, Oil & Gas, Energy, and Transport.
Since 2008, the Stream Reasoning research community conducted investigations and wrote papers that envision, elaborate, evaluate and discuss many aspects of this research question. The Stream Reasoning community document that a) the Semantic Web stack can be extended so to incorporate streaming data and events as a first class objects, b) the Stream Reasoning task is feasible, c) the very nature of streaming data offers opportunities to optimize reasoning, d) a combination of deductive and inductive stream reasoning techniques can cope with incomplete and noisy data. The mature Stream Reasoning solutions got deployed in real scenarios such as Smart City, Social Media Analytics, Oil & Gas, Energy, and Transport.