I also published the source code (it's based on python and PHP) PRs are welcome https://github.com/Ladsgroup/wd-analyst
On Wed, Dec 9, 2015 at 7:20 AM Amir Ladsgroup <[email protected]> wrote: > Hey Markus, > > On Wed, Dec 9, 2015 at 12:12 AM Markus Krötzsch < > [email protected]> wrote: > >> Hi Amir, >> >> Very nice, thanks! I like the general approach of having a stand-alone >> tool for analysing the data, and maybe pointing you to issues. Like a >> dashboard for Wikidata editors. >> >> What backend technology are you using to produce these results? Is this >> live data or dumped data? One could also get those numbers from the >> SPARQL endpoint, but performance might be problematic (since you compute >> averages over all items; a custom approach would of course be much >> faster but then you have the data update problem). >> > I build a database based on weekly JSON dumps. we would have some delay in > the data but computationally it's fast. Using Wikidata database directly > makes performance so poor that it becomes a good attack point. > > >> An obvious feature request would be to display entity ids as links to >> the appropriate page, and maybe with their labels (in a language of your >> choice). >> >> Done. :) > >> But overall very nice. >> >> Regards, >> >> Markus >> >> >> On 08.12.2015 18:48, Amir Ladsgroup wrote: >> > Hey, >> > There has been several discussion regarding quality of information in >> > Wikidata. I wanted to work on quality of wikidata but we don't have any >> > source of good information to see where we are ahead and where we are >> > behind. So I thought the best thing I can do is to make something to >> > show people how exactly sourced our data is with details. So here we >> > have *http://tools.wmflabs.org/wd-analyst/index.php* >> > >> > You can give only a property (let's say P31) and it gives you the four >> > most used values + analyze of sources and quality in overall (check this >> > out <http://tools.wmflabs.org/wd-analyst/index.php?p=P31>) >> > and then you can see about ~33% of them are sources which 29.1% of >> > them are based on Wikipedia. >> > You can give a property and multiple values you want. Let's say you want >> > to compare P27:Q183 (Country of citizenship: Germany) and P27:Q30 (US) >> > Check this out >> > <http://tools.wmflabs.org/wd-analyst/index.php?p=P27&q=Q30|Q183>. And >> > you can see US biographies are more abundant (300K over 200K) but German >> > biographies are more descriptive (3.8 description per item over 3.2 >> > description over item) >> > >> > One important note: Compare P31:Q5 (a trivial statement) 46% of them are >> > not sourced at all and 49% of them are based on Wikipedia **but* *get >> > this statistics for population properties (P1082 >> > <http://tools.wmflabs.org/wd-analyst/index.php?p=P1082>) It's not a >> > trivial statement and we need to be careful about them. It turns out >> > there are slightly more than one reference per statement and only 4% of >> > them are based on Wikipedia. So we can relax and enjoy these >> > highly-sourced data. >> > >> > Requests: >> > >> > * Please tell me whether do you want this tool at all >> > * Please suggest more ways to analyze and catch unsourced materials >> > >> > Future plan (if you agree to keep using this tool): >> > >> > * Support more datatypes (e.g. date of birth based on year, >> coordinates) >> > * Sitelink-based and reference-based analysis (to check how much of >> > articles of, let's say, Chinese Wikipedia are unsourced) >> > >> > * Free-style analysis: There is a database for this tool that can be >> > used for way more applications. You can get the most unsourced >> > statements of P31 and then you can go to fix them. I'm trying to >> > build a playground for this kind of tasks) >> > >> > I hope you like this and rock on! >> > <http://tools.wmflabs.org/wd-analyst/index.php?p=P136&q=Q11399> >> > Best >> > >> > >> > _______________________________________________ >> > Wikidata mailing list >> > [email protected] >> > https://lists.wikimedia.org/mailman/listinfo/wikidata >> > >> >> >> _______________________________________________ >> Wikidata mailing list >> [email protected] >> https://lists.wikimedia.org/mailman/listinfo/wikidata >> >
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