Re: COVID19 Cross-Domain Linked Dataset

Thank you all
if the purpose of all this work  is to grab data/figures, this is the
website that clicks
for me. I think they use simple additions and deletion of duplicates to get
their figures which so far have been the most accurate
https://www.worldometers.info/coronavirus/

I d be interested in comparative figures, do your graphs match these
figures or differ
considerably would be interesting to know


thanks

PDM



On Mon, Mar 30, 2020 at 4:20 AM Krzysztof Janowicz <janowicz@ucsb.edu>
wrote:

> On 3/29/20 1:04 PM, Sebastien Ferre wrote:
> > Dear all,
> >
> > if you want to explore and query the UCSD dataset without the
> > burden of writing SPARQL queries and with full freedom,
> > here is a Sparklis view over it.
> >
>
> UCSB ;-). UCSD, btw, also works on a graph and we are about to integrate
> both.
>
>
> > https://rebrand.ly/kw5ejwq
>
> Thanks!
> >
> > Here is an example query ranking locations by decreasing
> > maximal number of confirmed cases, along with maximal
> > number of deaths, and a computation of the corresponding
> > death rate.
> >
> > https://rebrand.ly/anph5ef
> >
> > The data looks a bit outdated as France, for instance, has passed
> > 40,000 confirmed cases, rather than 14,000.
> >
>
> Thanks. We have written the scripts to pull the data daily, but we do
> not run them as often as parts of the infrastructure we envision on our
> side are not yet in place.
>
> Best,
>
> Krzysztof
>
>
> > Take care, and stay home if you can!
> >
> > Sébastien
> >
> >
> > On 03/27/2020 06:19 PM, Krzysztof Janowicz wrote:
> >> Dear all,
> >>
> >> This is an update on our open knowledge graph about COVID-19.
> >>
> >> In our knowledge graph, we have:
> >>    (1). COVID19 cases for countries and regions (data from Johns
> >> Hopkins University)
> >>    (2). Airlines that are suspended due to COVID19 (data are
> >> partially donated from Aviation Edge and partially from manual
> >> collection)
> >>    (3). Quarantine policies across the world (manually collected)
> >>    (4). Relief aids from NGO (manually collected)
> >>    (5). Regions on multiple levels
> >>    (6). Local event data such as cancellations (so far by example only)
> >>    (7). Supply chain disruptions (so far by example only)
> >>
> >> We are  updating our KG by adding more resources. Examples include:
> >>   (1). Supply chains from wikidata
> >>   (2). Virus strain data (we are collaborating with UCSD on this part
> >> right now)
> >>   (3). Research articles from Kaggle (Thanks to Pieter, we will
> >> integrate your KG to ours)
> >>
> >> This KG can be visualized at:
> >>
> http://covid.geog.ucsb.edu:7200/graphs-visualizations?config=48691118befc47e4a6a6aabde78cd73d
> >>
> >>
> >> Example query:
> >>
> http://covid.geog.ucsb.edu:7200/sparql?savedQueryName=Max%20Confirmed%20Cases&owner=admin&execute
> >>
> >>
> >> Query endpoint: http://covid.geog.ucsb.edu:7200/sparql and
> >> http://covid.geog.ucsb.edu:7200/repositories/COVID-19
> >>
> >> Raw RDF: use the export at http://covid.geog.ucsb.edu:7200/graphs
> >>
> >> Please keep in mind that we are constantly changing the data and even
> >> the underlying ontology; things will break at times.
> >>
> >> We hope this can be another initiative for our community to
> >> contribute to such a global challenge. Any suggestions and/or
> >> interests of collaborations are *most* welcome.
> >>
> >> Krzysztof
> >>
> >
>
> --
> Krzysztof Janowicz
>
> Geography Department, University of California, Santa Barbara
> 4830 Ellison Hall, Santa Barbara, CA 93106-4060
>
> Email: jano@geog.ucsb.edu
> Webpage: http://geog.ucsb.edu/~jano/
> Semantic Web Journal: http://www.semantic-web-journal.net
>
>
>