- From: Ed Summers <ehs@pobox.com>
- Date: Mon, 10 Jun 2013 10:28:49 -0400
- To: public-prov-comments@w3.org
Hi Tom, Thanks for sharing. Is the paper here: http://www2013.org/companion/p167.pdf the same version of the paper you have to pay IEEE for? //Ed On Mon, Jun 10, 2013 at 4:58 AM, Tom De Nies <tom.denies@ugent.be> wrote: > 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 >> > >
Received on Monday, 10 June 2013 14:29:21 UTC