The Tetherless World Weblog

I’ve been asked to give a 30 minute talk on biomedical semantics in the cloud at the Molecular Med Tri Con in the symposium on cloud computing. Here’s what I know about what’s going on in this area at the moment:

• LexEVS is available as a AMI: https://cabig-kc.nci.nih.gov/Vocab/KC/index.php/Cloud_Computing_Services
• A Virtuoso Universal Server is available as an AMI: http://virtuoso.openlinksw.com/dataspace/dav/wiki/Main/VirtInstallationEC2
• I’m pretty sure NCBO is doing something here, but I can’t find any specifics.
• Will Stardog be available as an AMI or similar?

So that’s on the “semantics using the cloud” side, but I really think that there’s a lot of potential going the other way: using semantics to discover data and services in the cloud. SADI has the ability to discover and link services through ontologies. It’s similar to SAWSDL (in fact, they wrap SAWSDL services), but they don’t bother with the extra layer, and just let the service process RDF directly. When SADI services are deployed to the cloud, it’ll solve a big problem for people who want others to use their services/algorithms without the overhead of maintaining those servers themselves. In fact, with the Amazon DevPay structure, it’s possible for small labs to release datasets, databases, and algorithms to the world and not have to pay to support it.

I say when, not if, because my implementation of SADI in Python is almost ready for deployment through Google App Engine (which can be deployed in AWS or other systems using AppScale), and from what I hear, it won’t take much work to do the same with the Java implementation. Between this and the extreme portability of python SADI services (it’s just a script), use in the cloud and redeployment to private clouds is going to be trivial.

So I’m asking folks, am I full of it? Also, what else is there out there? Please help me out so that we all get some good exposure!

A few days ago I (Alvaro Graves) participated in the Open Government Data Camp 2011 in Warsaw, Poland, where people from different groups, organizations and governments met to discuss issues related to Open Data at government level. Here are some of the most important issues found in theese talk, in my opinion.

The current state of OGD

David Eaves, an activist who advises the city of Vancouver, Canada in issues about Open Data, gave a keynote in which he described his views on the current state of Open Data movement. First, it is striking that the success stories are not just a few anymore (as Data.gov or Data.gov.uk) but there are dozens (perhaps hundreds), both at national, regional and local levels. Similarly, the term Open Government Data is becoming increasingly popular, which is good because it is easier to stop explaining the ‘what’ and start focusing in the ‘how’.

Another interesting point is how the movement of Open Government Data already passed an inflection point, where it is no longer seen as people demanding from the outside, but being increasingly being invited to help working on these initiatives from within the government. For many, this change in perspective can be confusing and may create some concerns of Open Data being absorbed in a bureaucratic system that makes impossible to implement Open Data initiatives. However, it is clear that in order for these changes to occur, the movement can not reject to collaborate with governments.

Local initiatives, by locals

A talk that I really liked was by Ton Zylstra, who lives in the city of Enschede, the Netherlands. This city has only 150,000 inhabitants. He wanted an Open Data initiative there, however, it was difficult to convince the authorities, so he with a group of people decided to start working on their own. Inviting a handful of hackers to a bar, they created their first application that used data from Twitter, Foursquare, and the venues of a local festival. Eventually they convinced the municipal government that the default option for local data ought to be open.

From this experience, Ton showed several important lessons: You have to create something concrete, no matter if it is small: This implies something that requires little funding (the first beers at the bar were free) and short-term (no more than a couple of weeks). It does not matter if it is something original or not, there are some great ideas out there that deserve to be copied and are very useful for the local community.

How the Open Data died

Another very interesting keynote was by Chris Taggart, founder of OpenCorporates, who warned of the risks that the Open Data movement is facing today. His main concern is the lack of relevance in terms of impact Open Data has on society. For example, he mentioned that so far no one’s business depends on Open Data (although this is not true, there are a few out there, but I have to concede they are rare examples). In general, making data available is not enough, it is necessary for it to be used either in applications, by data journalists, etc. Also, it is fundamental to link different sites with Open Data (something quite uncommon in the movement), so that people can find out more information. Finally, I liked his idea that if the Open Data does not cause problems to its incumbents, then it is not working.

Redefining what is public

Finally another talk that I found interesting was the idea of ​​Dave Rasiej, founder of Personal Democracy, and Nigel Shaldbolt, professor at University of Southampton, to redefine “the public” in terms of data that “is available on the Web in machine-processable formats.” That is, uploading a bunch of PDFs with scanned tables does not make that information public, because it is not easily accessible. This initiative raises the bar of what public data is, especially when compared to the FOIA (Freedom of Information Act) that allows you to request information from government. Note that this applies to all information, as Rasiej so vehemently described it.

So… what did you talked about at OGDCamp?

In my case, I presented a system for publishing Linked Data called LODSPeaKr, which can be used for the rapid publication of government data and to create applications based on Linked Data. In the near future I will be writing more about this framework, but for now you can see my presentation here.

————————————————————————————————
Title:  Open Government Knowledge: AI Opportunities and Challenges
When:  4-6 November 2011
Where:  Westin Arlington Gateway in Arlington, Virginia, USA
Homepage: http://tw.rpi.edu/ogk2011
Program (PDF): http://tw.rpi.edu/media/latest/ogk2011.pdf
————————————————————————————————

Please join us to meet the thought governmental and business leaders in
US open government data activities, and discuss the challenges. The
symposium features Friday (Nov 4) as governmental day with speakers on
Data.gov, openEi.org, open gov data activities in NIH/NCI, NASA. and
Saturday (Nov 5) as R&D day with speakers from industry such as Google
and Microsoft, as well international researchers.

This symposium will explore how AI technologies such as the Semantic Web,
information extraction, statistical analysis and machine learning, can be used
to make the valuable knowledge embedded in open government data more
explicit, accessible and reusable.

Co-Chairs
* Li Ding, Qualcomm (Previously RPI)
* Tim Finin, UMBC
* Lalana Kagal, MIT
* Deborah McGuinness, RPI

A discussion came up on the W3C Semantic Web Healthcare and Life Sciences (HCLS) SIG mailing list around models in OWL, validation and XSD. I’m reproducing my response here, because it’s worthwhile for a larger audience and it involves some work from a TWCer (Jiao Tao), the Pellet ICV.

I feel I need to cut to the chase with this one: XML schema cannot validate semantic correctness.

It can validate that XML conforms to a particular schema, but that is syntactic. The OWL validator is nothing like a schema validator, first it produces a closure of all statements that can be inferred from the asserted information. This means that if a secondary ontology is used to describe some data, and that ontology integrates with the ontology that you’re attempting to validate against, you will get a valid result. An XML schema can only work with what’s in front of it.
Read more…

I had a bizarre dream last night, one of those surreal shockers. The details aren’t important, but I realized on waking up that the dream’s theme was all about unanticipated consequences.  I realized I needed to write this post.

To set some context: I went to bed upset last night.  I was upset at two things, one is an article on techcrunch entitled “Five Open Questions For Data.gov Before We #SaveTheData,” the other was my response to the article.  I hope I can respond to the first and apologize for the second.  I want to make one thing clear, however, before I start – I am a strong supporter of http://data.gov, I think it is a great experiment in democracy resulting from bold leadership, and if it dies in the current budget cutting it will be an enduring embarrassment for the USA and a major loss to government transparency.

The article I was upset about was written by Kate Ray (@kraykray), an amazingly bright and articulate young woman who has made several very impressive videos and online articles that I am a fan of.  She recently was one of the co-founders of “NerdCollider,” a website designed to bring intelligent discussion to interesting issues — an idea I support.  I was proud to be an early contributor to one of their discussions, which asked “What would you change about Data.gov to get more people to care?”

In the TechCrunch blog post I mentioned above, Kate takes several quotes from this discussion and reflects on their import — is data.gov taking some of the key issues into account?  As a good reporter, Kate’s OpEd is actually quite objective – she reports on several comments made by people, including me, as to issues the site has in terms of its effort to share government data.   TechCrunch is a very influential site, the article title has been tweeted and retweeted hundreds of times to hundreds of thousands of potential readers (congrats to Kate on this viral takeup), raising awareness of Congress’ narrow-minded goal of killing the project, which I guess is a good thing.  Unfortunately, the choice of the word “Before” in “… Before we #savethedata” has a negative implication, and I’m hoping that doesn’t kill off the positive efforts that the #savethedata meme was designed to promote.

In her article, Kate brings up important issues, but what she doesn’t make clear is that most of the people she quotes are indeed strong supporters of the Open Government movement and fans of Data.gov.  The seeming criticisms were actually constructive responses to the question of how we could get more people to care (a positive), and not meant to say what was wrong with the site that must be fixed before the site was useful.  It’s already very useful, but like any new effort, there’s always room for improvement. However, those changes will never happen if the site is forced to go dark!

As I said, Kate’s article has been phenomenally well tweeted, in fact, if you look at #savethedata the stream is so filled with pointers to this article that one can no longer easily find the link to the Petition created by the Sunlight Foundation to help stop the budget cuts — that petition is where the #savethedata meme started (thanks @EllnMiller).  Kate also doesn’t point to the great HuffPost article by @bethnoveck explaining why cutting the funding to this and other egovernment sites will threaten American jobs which was also retweeting around the #savethedata meme.

So I hope one unanticipated consequence of this article is that it doesn’t help cause the death of data.gov by killing off the awareness of its importance or losing the momentum on the petition that could save it.

But, as Arlo Guthrie used to say, “that’s not what I came here to talk about tonight…”

In my response to Kate’s article, I referred to her making factual errors.  This is a horrible thing to accuse a young journalist of, and I was being unfair.  The errors I wanted to point out were not in Kate’s piece, but in the chart chosen to go along.  It appears to show a flatline in the interest in data.gov, using figures from (as Kate told me later in a separate tweet) compete.com on “unique visits.”  I don’t know where compete.com gets the data, but the tracking of the  number of visitors on the data.gov site — which are reported on the site on a daily basis seems to show a much larger number with a more positive trend (over 180,000 visits in March).  It’s unclear why there is this discrepancy (I suspect it’s in how compete.com figures uniqueness for sites they don’t control), but it is clear it isn’t Kate’s fault.   She also cites the number of downloads in her article as 1.5M since Oct 2010, which is the number reported on data.gov, but as of last week, the site broke 2M downloads, and the number is trending up.

Anyway, I’m digressing again (occupational hazard of a college professor) — the key point is the errors are not Kate’s and that she was reflecting on what she found.

I also was upset that she quoted me out of context – in my nerdcollider response I made it clear I was supporting data.gov, and offering some constructive solutions to the question of how we could make the site better.  As the quote appears in her piece, it looks like I’m saying the data is poorly organized on the site — but what I was actually saying is that in the incredible richness of  data sets available (data.gov hosted over 300,000 datasets at last count!) we have to explore new ways to search for data  — it’s a wonderful problem to have!  But I did say what she quoted, and as she pointed out to me, correctly, one of the good things about nerdcollider is that the full context of the quotes are there to be cited.  She’s right.

So just as I hope Kate’s piece doesn’t have the unanticipated consequence of hurting data.gov, I hope my admittedly intemperate response doesn’t have the unanticipated consequence of hurting the reputation of this young potential online media star.

@kraykray – I apologize.