RE: Why we work on RSP

Hi Haroon, 





I guess there would be different answers to this.


One example can be data discovery. If you already know your data sources
 then it's usually fine to use existing technologies: you know your 
schema and you can use your old pub-sub stuff.


But in IoT and other domains you sometimes do not know that beforehand, 
and the interpretable data comes very handy to do fancy data discovery 
tasks. On the contrary, if we use e.g. CSV values 3.0, 4.5, 3, 6.7 
without any semantic metadata it's impossible to
know what your data source is about.





I think there are many other examples, this could be one.





Jean-Paul 

Date: Mon, 27 Jul 2015 13:34:48 +0530
From: haroonr@iiitd.ac.in
To: public-rsp@w3.org
Subject: Why we work on RSP

Hello Everyone,


My apologies if I have sent this mail to the wrong discussion group.


My name is Haroon and I have joined the RSP W3C group recently. I am working on linked, streaming data from last one month approximately. I am considering IoT data (say temperature, humidity readings)  as a source of continuous data streams.  I find this area exciting; recently I had a discussion with some of my colleagues about linked stream data processing. During discussion we mainly discussed around the  following points:
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1. Why we need to work on linked-data (RDF) streams ?  
My response: Linked data is machine interpretable. Therefore​,​ we need to represent our data into linked data form so that machines can 
understand it and possibly can reason over it. This also makes data sharable/reusable. Other data representations are not machine interpretable. 

2. We have several data representations available (say XML, JSON, ….) and we have some efficient publish-subscribe systems, which consume IoT data streams and then push​ the​ relevant data to end users/applications. Existing data representations and publish-subscribe systems suffice the current needs​,​ then why should we go for linked streams data representation. Apart from machine-interpretable feature it does not add anything. Also​,​ it makes data much more verbose  and hence it might take more time to process the data at processing engine.
Response:  ….
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 At the end of ​the ​discussion I found my colleagues were not satisfied because none of them was ​an ​expert in semantic technologies. Although I am satisfied about this area​,​ but I need genuine feedback/comments from your side about the above mentioned points. What makes linked​,​ streaming data representation so special that we need to work over it further?


--
Haroon Rashid