Re: Modeling Uncertainty in PROV - presented at WWW2013

Thanks, Tom -

WRT UnCertML, yes – the model and encoding is designed for more complex geoscience and related modeling and statistical analysis. 

Regards

Carl


From: Tom De Nies 
Sent: Monday, June 10, 2013 2:58 AM
To: Carl Reed 
Cc: public-prov-comments@w3.org 
Subject: Re: Modeling Uncertainty in PROV - presented at WWW2013

Hi Carl,

thanks for the useful information!

COBWEB looks like an extremely interesting project, where there is a clear need for trustworthiness assessment of the data that is gathered.

I hadn't heard of UnCertML. For my use cases, at first glance it's seems to be a bit overkill since there's less statistics involved, but I'll definitely keep it in mind should more complex scenarios present themselves. In any case, it would definitely be interesting to see how it could be combined with PROV.

Regards,
Tom 

Tom De Nies
Researcher Semantic Web
Ghent University - iMinds
Faculty of Engineering and Architecture
Department of Electronics and Information Systems - Multimedia Lab
Gaston Crommenlaan 8 bus 201, B-9050 Ledeberg-Ghent, Belgium

t: +32 9 331 49 59
e: tom.denies@ugent.be

URL:  http://multimedialab.elis.ugent.be 




2013/6/7 Carl Reed <creed@opengeospatial.org>

  Thanks, Tom - 

  Uncertainty is a “big deal” with spatial data, whether collected by traditional survey techniques, from sensors, or for volunteered geographic information (VGI).

  For example, check out COBWEB http://www.opengeospatial.org/projects/initiatives/cobweb as an interesting example of where data quality, provenance, and uncertainty all collide. 

  In terms of the geosciences (hydrology, meteorology, etc), we have been using UnCertML for modeling and encoding uncertainty in our standards work.

  I will share your presentation with the OGC Membership. I suspect that there will be considerable interest.

  Regards

  Carl Reed, PhD
  CTO
  OGC


  From: Tom De Nies 
  Sent: Friday, June 07, 2013 6:22 AM
  To: public-prov-comments@w3.org 
  Subject: Modeling Uncertainty in PROV - presented at WWW2013

  Hi all,

  since we're sharing PROV stories, I thought I'd let you know of our recent contribution at WWW2013 [1].

  It's a very simple & lightweight set of attributes, used to model provenance in case the content is uncertain, or when the provenance statements are uncertain themselves. 
  I needed these for my work with Named Entity Recognition, provenance reconstruction and trust assessment, and decided to write a short paper about them in case someone else had use for them. Since most PROV statements support attributes, the PROV I add these to remains perfectly valid.
  Of course, you could create your own attributes for this, but should you want to use them as well, we've created an "UP" namespace at our lab's website [2].

  Best regards,
  Tom

  [1] De Nies, Tom, et al. "Modeling uncertain provenance and provenance of uncertainty in W3C PROV." Proceedings of the 22nd international conference on World Wide Web companion. International World Wide Web Conferences Steering Committee, 2013.
  http://dl.acm.org/citation.cfm?id=2487871
  [2] http://semweb.mmlab.be/ns/up/


  Tom De Nies
  Researcher Semantic Web
  Ghent University - iMinds
  Faculty of Engineering and Architecture
  Department of Electronics and Information Systems - Multimedia Lab
  Gaston Crommenlaan 8 bus 201, B-9050 Ledeberg-Ghent, Belgium

  t: +32 9 331 49 59
  e: tom.denies@ugent.be

  URL:  http://multimedialab.elis.ugent.be