compare https://www.outpan.com/data?k=germany
to http://netbase.pannous.com/html/verbose/germany (wikidata mirror)
Edit: It was the Bonn Summary of wikipedia
Really curious to try it. It's a really neat idea. Has this been done before? I've never seen anything like it.
The full value of this would likely come from interesting, productive, insightful visualizations of the underlying graph that is being built.
Questions that come to my mind:
- What if you write bots that scrape Wikipedia, Twitter, etc. and output entries from semantic analysis performed on these sources?
- If many people write such bots, how similar would the graphs be? What are the parameters that determine graph overlap?
- Can you use this to tie in to the real world?
"A key can be any unique string such as product barcodes, book ISBNs, email addresses, URLs, domain names, names, phone numbers ..."
Interesting stuff there... A way to make this into an interesting social network is if people curated their own graphs, e.g. of books and webpages and favorite restaurants, and other people could browse these graphs in a read only mode. (perhaps they can clone it to their graphs or so and then start to edit them)
The temporal aspect might be interesting too. Would there be value in seeing how my graph has changed over time? When I was in academia, none of the tools to keep track of the papers I read suited me. I could see this working well for this use case scenario.
(if you could write a Prolog against this, would it have interesting properties?)
I see that a submitter just posted 7630028603780 -> volume -> 75ml (the first number being probably the bar code of some beverage), that's neat.
Someone else just posted the following entry:
5010438013621 -> ingredients -> Water, sugar, mixed fruit juices from concentrate 10% (Grape, blackcurrant, raspberry), acid (Citric acid), Vimto flavouring (Includes natural extracts of fruits, herbs, barley malt and spices), colouring food (Concentrate of carrot, hibiscus), acidity regulator (Sodium citrate), preservatives (Sodium benzoate, Potassium sorbate), Vitamin C, Sweeteners (Sucralose, Acesulfame K).
Now what the site should be doing is converting this to something like:
5010438013621 -> ingredients -> water
5010438013621 -> ingredients -> sugar
5010438013621 -> ingredients -> vitamin C
...
(Outpan person/people, I'm in SF, if you want to chat more around coffee, there's an email is in my profile)
Depends what you mean by "this"! RDF [1] and most of the technology surrounding it and the "Semantic Web" are based on (subject, predicate, object) triples almost exactly like this, where each element is often a URI, and objects are often strings just like they are here.
It even has taken this idea to the next level where the statements expressed by such a triple can themselves be given an "anonymous" ID, which can then be used as a subject or object – meaning you can make meta statements about the statement itself, all while still using this simple system of triples.
There are even entire languages built around querying graphs of such triples: https://www.w3.org/TR/sparql11-query/
DBpedia [1] is one such project that attempts to encode data from Wikipedia in triples like this; their About page says that the 2014 version of the database had 3 billion triples, so that number is probably much higher now. Here's a preview if you want to see what these triples look like:
• Homepages of things: http://downloads.dbpedia.org/preview.php?file=2015-10_sl_cor...
• Genders of things: http://downloads.dbpedia.org/preview.php?file=2015-10_sl_cor...
etc. You'll notice that RDF predicates are all namespaced by URIs; that way you can unambiguously know in what sense "homepage" and "gender" are used (consider more ambiguous properties like "length"). That means there can be other uses of "homepage", "gender", "length" etc. that mean different things, and those will be namespaced by a different URI.
Anyway, this Outpan project is obviously a more loose and freeform version of that – but only slightly; RDF is not very strict at all, it's just that people have thought a lot about how to successfully model the entire world's information, and so real-world RDF ontologies end up looking somewhat complicated. I'm not sure if a freeform version like this has been widely attempted before.
[1] https://en.wikipedia.org/wiki/Resource_Description_Framework [2] http://wiki.dbpedia.org/
SELECT DISTINCT ?property ?value WHERE {
<http://dbpedia.org/resource/Donald_Trump> ?property ?value
} LIMIT 500
As you can see there's a lot of metadata type properties, but scroll down and you can see his birthdate, children, alma mater, etc.
This page is just a prettified version of that data: http://dbpedia.org/page/Donald_Trump
I will send you an email :)
I expect this to work on a larger key space as well. It is interesting to see how the expansion works out in terms of usage patterns.
if you want really all the data: http://lod-cloud.net/
but still, neat project.
As for curation, it is intended to provide examples of what key, attr and values are regardless of their content. This is an experimental feature and might be removed/tweaked...
If you search for the key "germany" it has no results, if you search "london" it finds no results.
The fluidity of the data is definitely a hindrance, if you wanted to use the dataset you'd have to already know what you are looking for to find the value.
Perhaps that reveals that a forward slash might be a better separator though - like a URI.