Two, on the surface, totally unconnected posts – yet the the same message. Well that’s how they seem to me anyway.
Post 1 – The Problem With Wikidata from Mark Graham writing in the Atlantic.
When I reported the announcement of Wikidata by Denny Vrandecic at the Semantic Tech & Business Conference in Berlin in February, I was impressed with the ambition to bring together all the facts from all the different language versions of Wikipedia in a central Wikidata instance with a single page per entity. These single pages will draw together all references to the entities and engage with a sustainable community to manage this machine-readable resource. This data would then be used to populate the info-boxes of all versions of Wikipedia in addition to being an open resource of structured data for all.
In his post Mark raises concerns that this approach could result in the loss of the diversity of opinion currently found in the diverse Wikipedias:
It is important that different communities are able to create and reproduce different truths and worldviews. And while certain truths are universal (Tokyo is described as a capital city in every language version that includes an article about Japan), others are more messy and unclear (e.g. should the population of Israel include occupied and contested territories?).
He also highlights issues about the unevenness or bias of contributors to Wikipedia:
We know that Wikipedia is a highly uneven platform. We know that not only is there not a lot of content created from the developing world, but there also isn’t a lot of content created about the developing world. And we also, even within the developed world, a majority of edits are still made by a small core of (largely young, white, male, and well-educated) people. For instance, there are more edits that originate in Hong Kong than all of Africa combined; and there are many times more edits to the English-language article about child birth by men than women.
A simplistic view of what Wikidata is attempting to do could be a majority-rules filter on what is correct data, where low volume opinions are drowned out by that majority. If Wikidata is successful in it’s aims, it will not only become the single source for info-box data in all versions of Wilkipedia, but it will take over the mantle currently held by Dbpedia as the de faco link-to place for identifiers and associated data on the Web of Data and the wider Web.
I share some of his concerns, but also draw comfort from some of the things Denny said in Berlin – “WikiData will not define the truth, it will collect the references to the data…. WikiData created articles on a topic will point to the relevant Wikipedia articles in all languages.” They obviously intend to capture facts described in different languages, the question is will they also preserve the local differences in assertion. In a world where we still can not totally agree on the height of our tallest mountain, we must be able to take account of and report differences of opinion.
Post 2 – Danbri has moved on – should we follow? by a former colleague Phil Archer.
The Danbri in question is Dan Brickley, one of the original architects of the Semantic Web, now working for Google in Schema.org. Dan presented at an excellent Semantic Web Meetup, which I attended at the BBC Academy a couple of weeks back. This was a great event. I recommend investing in the time to watch the videos of Dan and all the other speakers.
Phil picked out a section of Dan’s presentation for comment:
In the RDF community, in the Semantic Web community, we’re kind of polite, possibly too polite, and we always try to re-use each other’s stuff. So each schema maybe has 20 or 30 terms, and… schema.org has been criticised as maybe a bit rude, because it does a lot more it’s got 300 classes, 300 properties but that makes things radically simpler for people deploying it. And that’s frankly what we care about right now, getting the stuff out there. But we also care about having attachment points to other things…
Then reflecting on current practice in Linked Data he went on to postulate:
… best practice for the RDF community… …i.e. look at existing vocabularies, particularly ones that are already widely used and stable, and re-use as much as you can. Dublin Core, FOAF – you know the ones to use.
Except schema.org doesn’t.
schema.org has its own term for name, family name and given name which I chose not to use at least partly out of long term loyalty to Dan. But should that affect me? Or you? Is it time to put emotional attachments aside and move on from some of the old vocabularies and at least consider putting more effort into creating a single big vocabulary that covers most things with specialised vocabularies to handle the long tail?
As the question in the title of his post implies, should we move on and start adopting, where applicable, terms from the large and extending Schema.org vocabulary when modelling and publishing our data. Or should we stick with the current collection of terms from suitable smaller vocabularies.
One of the common issues when people first get to grips with creating Linked Data is what terms from which vocabularies do I use for my data, and where do I find out. I have watched the frown skip across several people’s faces when you first tell them that foaf:name is a good attribute to use for a person’s name in a data set that has nothing to do with friends or friends of friends. It is very similar to the one they give you when you suggest that it may also be good for something that isn’t even a person.
As Schema.org grows and, enticed by the obvious SEO benefits in the form of Rich Snippets, becomes rapidly adopted by a community far greater than the Semantic Web and Linked Data communities, why would you not default to using terms in their vocabulary? Another former colleague, David Wood Tweeted No in answer to Phil’s question – I think this in retrospect may seem a King Canute style proclamation. If my predictions are correct, it won’t be too long before we are up to our ears in structured data on the web, most of it marked up using terms to be found at schema.org.
You may think that I am advocating the death, and replacement by Schema.org, of all the vocabularies well known, and obscure, in use today – far from it. When modelling your [Linked] data, start by using terms that have been used before, then build on terms more specific to your domain and finally you may have to create your own vocabulary/ontology. What I am saying is that as Schema.org becomes established, it’s growing collection of 300+ terms will become the obvious start point in that process.
OK a couple of interesting posts, but where is the similar message and connection? I see it as democracy of opinion. Not the democracy of the modern western political system, where we have a stand up shouting match every few years followed by a fairly stable period where the rules are enforced by one view. More the traditional, possibly romanticised, view of democracy where the majority leads the way but without disregarding the opinions of the few. Was it the French Enlightenment philosopher Voltaire who said: ”I may hate your views, but I am willing to lay down my life for your right to express them” – a bit extreme when discussing data and ontologies, but the spirit is right.
Once the majority of general data on the web becomes marked up as schema.org – it would be short sighted to ignore the gravitational force it will exert in the web of data if you want your data to be linked to and found. However, it will be incumbent on those behind Schema.org to maintain their ambition to deliver easy linking to more specialised vocabularies via their extension points. This way the ‘how’ of data publishing should become simpler, more widespread, and extensible. On the ‘what’ side of the the [structured] data publishing equation, the Wikidata team has an equal responsible to not only publish the majority definition of facts, but also clearly reflect the views of minorities – not a simple balancing act as often those with the more extreme views have the loudest voices.Main image via democracy.org.au.