- From: Xiang Su <xiangsu@ee.oulu.fi>
- Date: Tue, 4 Aug 2015 15:40:07 +0300
- To: public-rsp@w3.org, haroonr@iiitd.ac.in, fadirra@gmail.com, jean-paul.calbimonte@epfl.ch, Xiang Su <xiang.su@ee.oulu.fi>
Hi,
We have some publications about utilizing different semantic
representation for IoT data.
http://onlinelibrary.wiley.com/doi/10.1002/cpe.3203/full
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7030117&tag=1
I hope they somehow help.
br,
-Xiang
On 4.8.2015 15:07, Haroon Rashid wrote:
> Thanks Fariz for the detailed explanation. Although I understood the
> importance of RDF, but I am still curious to know why people are not
> interested in it. I think people either find it difficult to adapt or
> find it much more verbose.
>
> On Tue, Aug 4, 2015 at 2:02 AM, Fariz Darari <fadirra@gmail.com
> <mailto:fadirra@gmail.com>> wrote:
>
> Hi Haroon,
>
> I would like to give a try answering your questions:
>
> 1. RDF is good at interoperability. Consider the use case of stream
> data integration. There can be two different situations:
> a. When your data and the others have already been described using a
> shared, common ontology (e.g., Semantic Sensor Networks ontology
> [1]), you basically need minimal/no integration effort.
> b. When your data is in RDF but is described in different
> ontologies: you can use some off-the-shelf stream integration
> techniques like from [2], which uses the R2RML standard as a mapping
> language.
>
> 2. RDF is good at reasoning. On top of RDF, there is OWL, which is
> an ontology language for additional inference over your stream data.
> TrOWL is an example of an OWL reasoner for stream services [3].
>
> 3. RDF is good for the Web. RDF by design is a data model for the
> Web. Everything is represented by URIs, can ideally be dereferenced
> via HTTP, and can be linked with other URIs [4]. Thus, the power of
> the Web is inherited to RDF. As an example, you need not stream
> complete description of some resources. You can just use URIs in
> your stream, and the complete descriptions can be dereferenced on
> demand depending whether your data stream consumers are interested in.
>
> I hope this helps.
>
> Best,
> Fariz
>
> [1]
> http://www.slideshare.net/rgcmme/overview-of-the-w3c-semantic-sensor-network-ssn-ontology
>
> [2] https://github.com/jpcik/morph-stream
> [3] http://trowl.org/about/
> [4] http://www.w3.org/DesignIssues/LinkedData.html
>
>
> Regards,
> Fariz
>
> On Sat, Aug 1, 2015 at 9:53 AM, Haroon Rashid <haroonr@iiitd.ac.in
> <mailto:haroonr@iiitd.ac.in>> wrote:
>
> Dear All,
>
> Sorry for disturbing you during the weekend.
>
> Thanks
> Jean
> for the explanation.
> Here I am considering only IoT data. Generally, we send data
> from sensors in Json/ Xml format, where a specific value
> /reading
> is represented by different key-value pairs
> as
>
> {sensor/device:
>
> device_name
> type:
>
> temperature
> value:
>
> 32
> unit:
>
> degree
> time:
>
> 12:12:12
> }
> I
> k
> now that RDF/RDFa data is machine interpretable because of URIs,
> which make it special. Things I am not able to understand
> include:
>
> 1. How RDF makes data more discoverable? I mean even JSON/XML
> data is discoverable because data is associated with a
> number of attributes as shown in
> the
> example. In both representations,
>
> i.e., json/xml or RDF representation
> ,
>
> we must be knowing the attribute names or URIs before hand.
> 2. Also, you are saying that if we don’t know the data
> source/structure a-priori, then RDF data allows us to do
> some fancy tasks. Can you please elaborate it with an
> example? I think if we don’t have any clue about data
> structure then It does not matters whether it is in json or
> xml or RDF.
>
> The main point is here to find the importance of RDF/linked
> data. How it makes a different impact on the research community.
> Why should I represent my IoT data in RDF
> steams
> ?
>
>
>
> On Thu, Jul 30, 2015 at 1:54 PM, Jean Paul Calbimonte
> <jpcalbimonte@delicias.dia.fi.upm.es
> <mailto:jpcalbimonte@delicias.dia.fi.upm.es>> wrote:
> >
> > 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 <mailto:haroonr@iiitd.ac.in>
> > To: public-rsp@w3.org <mailto: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:
> >
> ______________________________________________________________________________________________
>
> >
> > 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: ….
> >
> ______________________________________________________________________________________________
> >
> > 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
>
>
>
>
> --
> Haroon Rashid
>
>
>
>
>
> --
> Haroon Rashid
>
>
Received on Tuesday, 4 August 2015 12:46:57 UTC