What professional benefits do you see by investing time into a FOAF-style network?

Social networking sites like Facebook almost entirely rely on friend-of-a-friend relationships. Actually, they facilitate these types of relationship by sending notifications saying “Connect with John Smith. You have 147 friends in common.” So what started out as just a social activity, is now being utilized for professional and career purposes. FOAF networks bring people together through other people and common interests. It’s no surprise that these types of networks are being for professional benefits. Personally, I would find the major benefit of being able to know the people you could be working with at your job beforehand and that way you already have an established relationship (which could either be a good or bad thing). More often than not, the job you’re looking for is probably not going to be advertised all over the place, and through FOAF networks and the more you have, there’s a better chance that you can find a job you love simply through who you know.

I now have a new improved version of my family tree up as linked data here. To produce this family tree I converted the original family tree that my parents created using a perl script that takes GEDCOM to RDF. I then manually cleaned up the RDF to get the URIs in a form that I wanted.

This resulted in an RDF file giving information about parent/child, sibling and spouse relations for my family members. The vocabularies (or ontologies) used for this were FOAF, BIO and RELATIONSHIP.

I was interested in displaying more than just parent/child, sibling and spouse relationships and decided a simple extension could be to have grandparent/grandchild and ancestor/descendant information. To compute this information I used the Protege 4 OWL 2 editor. To compute grandparent information I used a property of OWL 2 called “property chains“. The property chain for computing grandchild relationships from child ones was straightforward:

childOf o childOf -> grandChildOf

(or for those who prefer rules: childOf(?x,?y) , childOf(?y,?z) -> grandChildOf(?x,?z) )

This simply states that “the child of the child of someone is a grandchild of that someone”.

The ancester information was event more straightforward to compute. Here we just make the property parentOf a subproperty of ancesterOf and then make ancesterOf a transitive property.

Given the two axioms above we can then let the OWL reasoner in Protege 4 do all the hard work and compute the implicit relationships based on the explicitly stated ones. Anyone interested in using OWL to compute more family relations should read this paper by Robert Stevens.

So I now have some RDF containing parent/child, ancester/descendant, sibling and spouse relationships. Also in this data are notions of family groups and information about birth [1] and death events. These events contain information about dates and places (given as text) of birth/death. Having this information as literals is not very interesting as it means I then have to go and use Google (or similar) to find additional information about the dates/places. To get round this (and create some links in my linked data) I decided to connect the places of birth/death to the corresponding resource in DBpedia (an RDF version of wikipedia) and do similarly for the dates [2]. An example of this can be seen here http://www.johngoodwin.me.uk/family/event1917. This means I can now find additional information about a persons place of death/birth by following the links in the data if I should choose to do so. To link birth/death events to dates/place I used the event ontology.

In order to host the data as linked data I used the Talis Platform and the Paget (2) PHP library.

There is a SPARQL endpoint for the data here. We can use this to query for my uncles as follows:

PREFIX rel: <http://purl.org/vocab/relationship/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX family: <http://www.johngoodwin.me.uk/family/>
select ?uncle ?name
where
{
family:I0243 rel:childOf ?parent .      ( finds my parents)
?parent rel:siblingOf ?uncle .          (finds my parents siblings)
?uncle foaf:gender “male” .          ( find the male siblings)
?uncle foaf:name ?name .         (this returns their names)
}

My next plan is to build some mash-ups using this data. Such a mash-up could use resources on the web of linked data to find famous people born in the same place/year as various family members, identify BBC programmes that are about said places etc. etc.

Now all I need to do is find a long lost relative who is also into genealogy and linked data so I can connect some nodes…what are the chances???

[1] – for obvious privacy reasons no birth information is given for people still living.

[2] – this was a fairly tedious manualish process – but some scripting helped.

Embedding travel data within FOAF profiles is an obvious way to share and expose the personal travel habits and/or intentions of a foaf:Person; yet, few of us do it, partly because the necessary RDF vocabularies are lacking.  Some neat widgets created by Richard Cyganiak (FOAF – Where Am I?) and Alexandre Passant (FOAFMap.net) a couple of years ago to facilitate the use of Basic Geo (WGS84 lat/long) Vocabulary within FOAF for the purposes of mapping a foaf:Person have been useful, but their application is essentially confined to mapping the geographical coordinates of individuals’ office location (via the foaf:based_near property).  It therefore seems to me that there is a need for a basic, lightweight RDF vocabulary to leverage the expressiveness of vocabularies such as BasicGeo and RDF Calendar within FOAF in order to better model individuals’ travelling habits.  The motivation behind this is clear…

Firstly, many of those active in research and academia attempt to do something similar already via their homepages.  They tell us about their upcoming trips and occasionally mark them up using RDF Calendar.  Their intention is to share future journeys and travel itineraries with colleagues so that synergies in travel patterns can be identified and important meetings arranged between busy people (“Ahhhh, I’ll catch up with person X about our research idea at Y conference…”).  Ivan Herman and Dan Connolly’s W3C homepages are two high profile examples of this.  This also seems to be true for those in the business community who appear to be making good use of ’smart travel’ services such as Dopplr to achieve something similar.  Dopplr essentially allows users to create and share details of future journeys and travel itineraries with friends, colleagues or business contacts, but also allows users to map these itineraries.  People also like to record where they have been and why, and the ‘Cities I’ve Visited‘ Facebook application by TripAdvisor provides yet another example of wanting to associate travel with a personal profile, albeit within Facebook.

However, better exposing personal travel in a distributed and machine processable way (i.e. via FOAF profiles) would not only expose it to the Semantic Web and enrich social graphs, but make applications (similar to those described above) possible in an open way.  Of course, it is possible to use the RDF Calendar vocabulary on its own to model some travel, but it’s a little itchy and lacks the necessary semantics.  On the other hand, heavy weight travel ontologies exist (for example this) but these tend to occupy the other end of the spectrum; optimised for ’serious’ travel applications and too heavy weight for a simple FOAF profile.  A middle way is required; a basic, light weight RDF travel vocabulary, ideally for use with FOAF.  It is therefore my intention (hopefully) to author such a rudimentary RDF vocabulary and RDF Schema in coming days.

Most properties would entail being a foaf:Person; so, for example, in my current FOAF profile I could include my intention to deliver a paper at the forthcoming ECDL conference (including details of the event, its location and geocoordinates):

<foaf:Person rdf:about="http://www.staff.ljmu.ac.uk/bsngmacg/#me">
...
 <travoc:delPaperAt>
   <cal:Vevent rdf:about="http://www.ionio.gr/conferences/ecdl2009/">
    <dcterms:title>ECDL 2009</dcterms:title>
    <cal:dtstart>2009-09-27</cal:dtstart>
    <cal:dtend>2009-10-02</cal:dtend>        
    <travoc:location rdf:resource="http://dbpedia.org/data/Corfu"/>
    <geo:Point geo:lat="39.61929" geo:long="19.91958"/>    
   </cal:Vevent>                    
 </travoc:delPaperAt>

Or, record some basic information pertaining to recent tourist destinations:

<foaf:Person rdf:about="http://www.staff.ljmu.ac.uk/bsngmacg/#me">
...
  <travoc:visited>
    <travoc:Place rdf:about="http://dbpedia.org/data/Istanbul">
    <geo:Point geo:lat="41.01237" geo:long="28.97592"/>
    <travoc:favSite rdf:resource="http://dbpedia.org/data/ Sultan_Ahmed_Mosque"/>
    </travoc:Place>
   </travoc:visited>

I suppose it would also be possible to incorporate the (controversial?) Google data vocabulary to rate hotels, tourists sites, etc.

Anyone have any thoughts about the above?  In particular, I would be interested know if any similar vocabulary exists.  I’ve had a thorough look but can’t find anything.  If not I’ll press ahead and have something published soon – hopefully.

In Erwartung, ähm, internationaler Resonanz bedient sich dieser Eintrag ausnahmsweise der englischen Sprache.

Identi.ca is trying hard to be the Open Twitter. Thus, it provides many ways to access and utilize its data, including a FOAF file that gives a semantic description of a users social network.

Retrieving and geocoding their profile location via Yahoo Pipes is just a snap, so here you go: A Yahoo Pipe that gives you a world map of all your identi.ca friends.

It probably still has some issues, so if anything goes wrong, feel free to leave me a comment – or clone the pipe and fix it yourself.

I’ve been hacking away at danbri’s version of specgen so we can rev the foaf spec. The idea is that you take an RDFS / OWL schema and generate some human-readable HTML from it, by taking the classes and properties and writing out their basic constituents. Optionally you can add some introductory text in a template, plus some individual bits of text for each property and class, eventually in different languages too.

I slapped in some RDFa yesterday because we needed a replacement for the ugly addition of RDF directly into the html, which makes it invalid. I realise some people may think this is back to front, but the foaf spec’s ‘original’ format has always been RDFS/OWL so it makes sense for us. I’m not actually sure we need two RDF versions (as there is alternate pointing to RDFS/OWL version from the HTML) but heck why not, and danbri’s consulting the community so there’s probably an argument I’ve missed.

There are several specgens available and at some point it might be nice to rationalise, or maybe go for functional equivalence. These are probably better in some senses than the one I’ve been working on, especially as I’m new to Python.

The ones I’ve found:

• SIOC’s specgen, a rev from danbri’s original one (which was itself based on something Chris Schmidt did, I think) – requires Redland
• Morfeo specgen, a rev from the SIOC one, again requires Redland
• Foaf specgen – requires RDFlib
• Patrick Sinclair’s ldontospec which uses Rena (Ruby)

I think the two things that unite the first three is that they are (a) self-described hacks (b) in python. The Foaf one uses RDFlib rather than Redland because danbri was having trouble with Redland installation on the Mac I believe.

Next things I’d like to look at are

• Generating specs from sample data (maybe someone’s done this already? It wouldn’t be complete but could be a start)
• Defining application profiles or Argots and using them to generate, say, useful Sparql queries
• Pictures!

The organisers of the Science Online London 2009 conference are asking people to propose their own session ideas (see some examples here), so here is a proposal:

Title: Who Are You? Digital Identity in Science

Many important decisions in Science are based on identifying scientists and their contributions. From selecting reviewers for grants and publications, to attributing published data and deciding who is funded, hired or promoted, digital identity is at the heart of Science on the Web.

Despite the importance of digital identity, identifying scientists online is an unsolved problem [1]. Consequently, a significant amount of scientific and scholarly work is not easily cited or credited, especially digital contributions: from blogs and wikis, to source code, databases and traditional peer-reviewed publications on the Web. This (proposed) session will look at current mechanisms for identifying scientists digitally including contributor-id (CrossRef), researcher-id (Thomson), Scopus Author ID (Elsevier), OpenID, Google Scholar [2], Single Sign On, PubMed, Google Scholar [2], FOAF+SSL, LinkedIn, Shared Identifiers (URIs) and the rest. We will introduce and discuss each via a SWOT analysis (Strengths, Weaknesses, Opportunities and Threats). Is digital identity even possible and ethical? Beside the obvious benefits of persistent, reliable and unique identifiers, what are the privacy and security issues with personal digital identity?

If this is a successful proposal, I’ll need some help. Any offers? If you are interested in joining in the fun, more details are at scienceonlinelondon.org

References

1. Bourne, P., & Fink, J. (2008). I Am Not a Scientist, I Am a Number PLoS Computational Biology, 4 (12) DOI: 10.1371/journal.pcbi.1000247
2. Various Publications about unique author identifiers bookmarked in citeulike
3. Yours Truly (2009) Google thinks I’m Maurice Wilkins
4. The Who (1978) Who Are You? Who, who, who, who? (Thanks to Jan Aerts for the reference!)

I’ve been busy converting my parents hard work on their  family tree into RDF. I blogged about initial attempts here. It’s far from finished, but at around 500,000 triples already it looks like it’s going to be a lot of RDF!

You can view the RDF (as it is) here, but seeing as RDF is for machines a more human friendly version can be browsed here. So far I’ve been concentrating on linking places of death and birth to various other datasets include geonames, DBpedia, Freebase and Ordnance Survey (though there still a fair few places to link).

To be done:

1) Finish connecting all the places.

2) Sort date formats out.

3) Turn into linked data with dereferencable URIs and content negotation.

A more detailed write up when it’s all finished…

You know that situation. Every time you want to order flowers via the Web or book a flight (where you not happen to be a premium member of the airline’s frequent fliers club having all the data handy), you are urged to fill in the most stupid and plain forms. Day in, day out, the same boring and time-consuming activity.

How about a sort of Mechanical Turk that does the dirty work for you?

Ok, enough words: here is my take on it, using RDForms‘ fusion capabilities, one can fill in her profile data from one’s FOAF file:

profile auto-complete demo based on RDForms fusion algorithm

Check out http://ld2sd.deri.org/pac/ and let me know what and how we could extend that little toy (maybe pre-selecting fields or protect certain fields, etc. ?). The code is also available at the pushback project svn.

Warning: this is a Sunday-morning hack, not a ready-to-go product, so please, bear with it/me

human-readable

–>

machine-readable

–>

human-readable.

FoaF Explorer è un tool che permette di visualizzare in forma human-readable la struttura di una rete FOAF.

By MQIT.com (an IBM Business Partner Strategy Methodology Center of Excellence SOA BPM ESB EAI WebSphere)

Source: DERI Semantic Web Web 20 SOA
(The pdf can be found at the MQIT PRESS BOX at the bottom right of MQIT.com.)

By MQIT.com (an IBM Business Partner Strategy Methodology Center of Excellence SOA BPM ESB EAI WebSphere)

Source: DERI Semantic Web Web 20 SOA
(The pdf can be found at the MQIT PRESS BOX at the bottom right of MQIT.com.)

Note: Social site users, geeks or IT entrepreneurs will have something to take away after reading this blog.

Before viewing the four videos below that introduce Semantic Web, what is semantic web?

The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners.

The Semantic Web is a Web of data. There is a lot of data we all use every day, and it’s not part of the Web. For example, I can see my bank statements on the web, and my photographs, and I can see my appointments in a calendar. But can I see my photos in a calendar to see what I was doing when I took them? Can I see bank statement lines in a calendar? Why not? Because we don’t have a web of data. Because data is controlled by applications, and each application keeps it to itself.

The vision of the Semantic Web is to extend principles of the Web from documents to data. Data should be accessed using the general Web architecture using, e.g., URI-s; data should be related to one another just as documents (or portions of documents) are already. This also means creation of a common framework that allows data to be shared and reused across application, enterprise, and community boundaries, to be processed automatically by tools as well as manually, including revealing possible new relationships among pieces of data.

Semantic Web technologies can be used in a variety of application areas; for example: in data integration, whereby data in various locations and various formats can be integrated in one, seamless application; in resource discovery and classification to provide better, domain specific search engine capabilities; in cataloging for describing the content and content relationships available at a particular Web site, page, or digital library; by intelligent software agents to facilitate knowledge sharing and exchange; in content rating; in describing collections of pages that represent a single logical “document”; for describing intellectual property rights of Web pages (see, eg, the Creative Commons), and in many others.

The Semantic Web is an evolving extension of the World Wide Web in which the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content. It derives from World Wide Web Consortium director Sir Tim Berners-Lee’s vision of the Web as a universal medium for data, information, and knowledge exchange.

At its core, the semantic web comprises a set of design principles, collaborative working groups, and a variety of enabling technologies. Some elements of the semantic web are expressed as prospective future possibilities that are yet to be implemented or realized. Other elements of the semantic web are expressed in formal specifications. Some of these include Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, N3, Turtle, N-Triples), and notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain.

Video #1: Eric Schmidt, Chairman and CEO of Google, on Web 2.0 and Web 3.0

Transcript by MQIT Corporation

Easy question.
What is Web 3.0?
We know what is Web 2.0 is.
What has Google see Web 3.0 ought to be?

Well, Web 2.0 is a marketing term.
And I think you just invented Web 3.0.
But if I were to guess what Web 2.0 is.
I would tell you that it is a different way of building an applications.
Up until now Web 2.0 has been a term that corresponds to something called AJAX.
AJAX is a computer architecture that is the underlaying architecture that I have been talking about.
And my prediction is would be that Web 3.0 will be ultimately be seen.
As applications that are piece together.
A number of characteristics.
Application are relatively small.
The data is in the cloud.
The applications can run on any device, PC or mobile phone.
That the applications are very fast.
And that they are very customizable.
And further more the applications are distributed by virus.
Essentially virally, literally by social networks, by email.
You will not go to the store to purchase them.
You will say – I send to you.
Here is a new interesting way of doing one thing or another.
That is a very different application model than we have ever seen in computing.
Very different from the mainframe era.
Very different from the PC industry.
Much likely to be very very large.
Has low variance entry.
The new generation of tools that is being announce today.
Google and other companies make it relatively easy to do.
Solves a lot of problem.
And works everywhere.

Video #2: Tim Berners-Lee, Inventor of WWW and Director of W3C, on the Semantic Web

Video #3: Introduction to Semantic Web from Digital Bazaar

Video #4: Semantic Web from GoogleTalks and DERI

The Semantic Web is a field aiming a the creation, deployment, and interoperation of machine readable data on the Internet. In the talk we present some projects in DERI on Semantic Web technologies – notably Semantic Interlinking of Online Community sites, Social Semantic Collaborative Filtering, and ActiveRDF, a library for Browsing, programming and navigating Semantic Web data.

The SIOC (Semantic Interlinking of Online Communities) project is an effort aiming at establishing and deploying a metadata vocabulary for interlinking and connecting distributed conversation on blogs, bulletin boards, and mailing lists. The vocabulary has been implemented…

Some of the technologies and projects mentioned in the videos above.

RDFa, Resource Description Framework in attribute
Today’s web is built predominantly for human consumption. Even as machine-readable data begins to appear on the web, it is typically distributed in a separate file, with a separate format, and very limited correspondence between the human and machine versions. As a result, web browsers can provide only minimal assistance to humans in parsing and processing web data: browsers only see presentation information. We introduce RDFa, which provides a set of XHTML attributes to augment visual data with machine-readable hints. We show how to express simple and more complex datasets using RDFa, and in particular how to turn the existing human-visible text and links into machine-readable data without repeating content.

Microformats
Designed for humans first and machines second, microformats are a set of simple, open data formats built upon existing and widely adopted standards. Instead of throwing away what works today, microformats intend to solve simpler problems first by adapting to current behaviors and usage patterns (e.g. XHTML, blogging).

Operator
Operator leverages microformats and other semantic data that are already available on many web pages to provide new ways to interact with web services.

SIOC, Semantic-Interlinked Online Communities
What is SIOC? The SIOC initiative (Semantically-Interlinked Online Communities) aims to enable the integration of online community information. SIOC provides a Semantic Web ontology for representing rich data from the Social Web in RDF. It has recently achieved significant adoption through its usage in a variety of commercial and open-source software applications, and is commonly used in conjunction with the FOAF vocabulary for expressing personal profile and social networking information. By becoming a standard way for expressing user-generated content from such sites, SIOC enables new kinds of usage scenarios for online community site data, and allows innovative semantic applications to be built on top of the existing Social Web. The SIOC ontology was recently published as a W3C Member Submission, which was submitted by 16 organisations.

OWL, Web Ontology Language
The World Wide Web as it is currently constituted resembles a poorly mapped geography. Our insight into the documents and capabilities available are based on keyword searches, abetted by clever use of document connectivity and usage patterns. The sheer mass of this data is unmanageable without powerful tool support. In order to map this terrain more precisely, computational agents require machine-readable descriptions of the content and capabilities of Web accessible resources. These descriptions must be in addition to the human-readable versions of that information. The OWL Web Ontology Language is intended to provide a language that can be used to describe the classes and relations between them that are inherent in Web documents and applications.

ActiveRDF
ActiveRDF is a library for accessing RDF data from Ruby programs. It can be used as data layer in Ruby-on-Rails, in the same way as you can use ActiveRecord for accessing relational databases. Using ActiveRDF with Ruby-on-Rails allows you to create semantic web applications very rapidly. ActiveRDF gives you a domain specific language for your RDF model: you can address RDF resources, classes, properties, etc. programmatically, without queries.

SSCF / SIOC Support
This project delivers a number of components that combined together allow users to search and browse the information space using existing semantic relations and social annotations.

The three first components (partially refactored from FOAFRealm and JeromeDL projects) are:
* SSCF – Social Semantic Collaborative Filtering
* MBB – MultiBeeBrowse – a modern faceted navigation
* SQE – Semantic Query Expansion based on a community-aware user profile

JeromeDL
JeromeDL is a Social Semantic Digital Library. As a digital library, it allows institutions to easily publish documents on the Web. It supports a variety of document formats and allows to store and query a rich bibliographic description of each document.

FoaF, Friend of a Friend
Our goal is to design and implement D-FOAF, a distributed authentication and trust infrastructure without a centralised authority. D-FOAF will be a backbone for trust applications based on social relationships and will establish idenity of users similar to the way we establish identity and trust in real life. D-FOAF will be based on previous work like the P2P HyperCuP topology and FOAFRealm, a Semantic Web based user and relationship management system. Implementation work will be conducted for the J2EE, .NET and PHP environments.

SKOS, Simple Knowledge Organization System

Note: Social site users, geeks or IT entrepreneurs will have something to take away after reading this blog.

Before viewing the four videos below that introduce Semantic Web, what is semantic web?

The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners.

The Semantic Web is a Web of data. There is a lot of data we all use every day, and it’s not part of the Web. For example, I can see my bank statements on the web, and my photographs, and I can see my appointments in a calendar. But can I see my photos in a calendar to see what I was doing when I took them? Can I see bank statement lines in a calendar? Why not? Because we don’t have a web of data. Because data is controlled by applications, and each application keeps it to itself.

The vision of the Semantic Web is to extend principles of the Web from documents to data. Data should be accessed using the general Web architecture using, e.g., URI-s; data should be related to one another just as documents (or portions of documents) are already. This also means creation of a common framework that allows data to be shared and reused across application, enterprise, and community boundaries, to be processed automatically by tools as well as manually, including revealing possible new relationships among pieces of data.

Semantic Web technologies can be used in a variety of application areas; for example: in data integration, whereby data in various locations and various formats can be integrated in one, seamless application; in resource discovery and classification to provide better, domain specific search engine capabilities; in cataloging for describing the content and content relationships available at a particular Web site, page, or digital library; by intelligent software agents to facilitate knowledge sharing and exchange; in content rating; in describing collections of pages that represent a single logical “document”; for describing intellectual property rights of Web pages (see, eg, the Creative Commons), and in many others.

The Semantic Web is an evolving extension of the World Wide Web in which the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content. It derives from World Wide Web Consortium director Sir Tim Berners-Lee’s vision of the Web as a universal medium for data, information, and knowledge exchange.

At its core, the semantic web comprises a set of design principles, collaborative working groups, and a variety of enabling technologies. Some elements of the semantic web are expressed as prospective future possibilities that are yet to be implemented or realized. Other elements of the semantic web are expressed in formal specifications. Some of these include Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, N3, Turtle, N-Triples), and notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain.

Video #1: Eric Schmidt, Chairman and CEO of Google, on Web 2.0 and Web 3.0

Transcript by MQIT Corporation

Easy question.
What is Web 3.0?
We know what is Web 2.0 is.
What has Google see Web 3.0 ought to be?

Well, Web 2.0 is a marketing term.
And I think you just invented Web 3.0.
But if I were to guess what Web 2.0 is.
I would tell you that it is a different way of building an applications.
Up until now Web 2.0 has been a term that corresponds to something called AJAX.
AJAX is a computer architecture that is the underlaying architecture that I have been talking about.
And my prediction is would be that Web 3.0 will be ultimately be seen.
As applications that are piece together.
A number of characteristics.
Application are relatively small.
The data is in the cloud.
The applications can run on any device, PC or mobile phone.
That the applications are very fast.
And that they are very customizable.
And further more the applications are distributed by virus.
Essentially virally, literally by social networks, by email.
You will not go to the store to purchase them.
You will say – I send to you.
Here is a new interesting way of doing one thing or another.
That is a very different application model than we have ever seen in computing.
Very different from the mainframe era.
Very different from the PC industry.
Much likely to be very very large.
Has low variance entry.
The new generation of tools that is being announce today.
Google and other companies make it relatively easy to do.
Solves a lot of problem.
And works everywhere.

Video #2: Tim Berners-Lee, Inventor of WWW and Director of W3C, on the Semantic Web

Video #3: Introduction to Semantic Web from Digital Bazaar

Video #4: Semantic Web from GoogleTalks and DERI

The Semantic Web is a field aiming a the creation, deployment, and interoperation of machine readable data on the Internet. In the talk we present some projects in DERI on Semantic Web technologies – notably Semantic Interlinking of Online Community sites, Social Semantic Collaborative Filtering, and ActiveRDF, a library for Browsing, programming and navigating Semantic Web data.

The SIOC (Semantic Interlinking of Online Communities) project is an effort aiming at establishing and deploying a metadata vocabulary for interlinking and connecting distributed conversation on blogs, bulletin boards, and mailing lists. The vocabulary has been implemented…

Some of the technologies and projects mentioned in the videos above.

RDFa, Resource Description Framework in attribute
Today’s web is built predominantly for human consumption. Even as machine-readable data begins to appear on the web, it is typically distributed in a separate file, with a separate format, and very limited correspondence between the human and machine versions. As a result, web browsers can provide only minimal assistance to humans in parsing and processing web data: browsers only see presentation information. We introduce RDFa, which provides a set of XHTML attributes to augment visual data with machine-readable hints. We show how to express simple and more complex datasets using RDFa, and in particular how to turn the existing human-visible text and links into machine-readable data without repeating content.

Microformats
Designed for humans first and machines second, microformats are a set of simple, open data formats built upon existing and widely adopted standards. Instead of throwing away what works today, microformats intend to solve simpler problems first by adapting to current behaviors and usage patterns (e.g. XHTML, blogging).

Operator
Operator leverages microformats and other semantic data that are already available on many web pages to provide new ways to interact with web services.

SIOC, Semantic-Interlinked Online Communities
What is SIOC? The SIOC initiative (Semantically-Interlinked Online Communities) aims to enable the integration of online community information. SIOC provides a Semantic Web ontology for representing rich data from the Social Web in RDF. It has recently achieved significant adoption through its usage in a variety of commercial and open-source software applications, and is commonly used in conjunction with the FOAF vocabulary for expressing personal profile and social networking information. By becoming a standard way for expressing user-generated content from such sites, SIOC enables new kinds of usage scenarios for online community site data, and allows innovative semantic applications to be built on top of the existing Social Web. The SIOC ontology was recently published as a W3C Member Submission, which was submitted by 16 organisations.

OWL, Web Ontology Language
The World Wide Web as it is currently constituted resembles a poorly mapped geography. Our insight into the documents and capabilities available are based on keyword searches, abetted by clever use of document connectivity and usage patterns. The sheer mass of this data is unmanageable without powerful tool support. In order to map this terrain more precisely, computational agents require machine-readable descriptions of the content and capabilities of Web accessible resources. These descriptions must be in addition to the human-readable versions of that information. The OWL Web Ontology Language is intended to provide a language that can be used to describe the classes and relations between them that are inherent in Web documents and applications.

ActiveRDF
ActiveRDF is a library for accessing RDF data from Ruby programs. It can be used as data layer in Ruby-on-Rails, in the same way as you can use ActiveRecord for accessing relational databases. Using ActiveRDF with Ruby-on-Rails allows you to create semantic web applications very rapidly. ActiveRDF gives you a domain specific language for your RDF model: you can address RDF resources, classes, properties, etc. programmatically, without queries.

SSCF / SIOC Support
This project delivers a number of components that combined together allow users to search and browse the information space using existing semantic relations and social annotations.

The three first components (partially refactored from FOAFRealm and JeromeDL projects) are:
* SSCF – Social Semantic Collaborative Filtering
* MBB – MultiBeeBrowse – a modern faceted navigation
* SQE – Semantic Query Expansion based on a community-aware user profile

JeromeDL
JeromeDL is a Social Semantic Digital Library. As a digital library, it allows institutions to easily publish documents on the Web. It supports a variety of document formats and allows to store and query a rich bibliographic description of each document.

FoaF, Friend of a Friend
Our goal is to design and implement D-FOAF, a distributed authentication and trust infrastructure without a centralised authority. D-FOAF will be a backbone for trust applications based on social relationships and will establish idenity of users similar to the way we establish identity and trust in real life. D-FOAF will be based on previous work like the P2P HyperCuP topology and FOAFRealm, a Semantic Web based user and relationship management system. Implementation work will be conducted for the J2EE, .NET and PHP environments.

SKOS, Simple Knowledge Organization System

Talking about RDF getting into the mainstream! John Musser just reported on the US Congress SpaceBook system that also includes the foaf data of, eg, senators. And he explicitly quotes the foaf data of Hillary Clinton (see that article for the details)…

Hm, hm. The foaf file is actually included in the page for Hillary Clinton as an… XML comment. Oops. Maybe its time to put this into RDFa… Also, as far as I know (I am not in the US so my knowledge of US regulation is not that good), now that she is Secretary of State, she has to give up here senator’s seat, right? If so, that URI will disappear…

Anyway, let us not grumble too much. It is a start!

31 Enero 2009

Yaiza Martínez

La Universidad de Stanford, en Estados Unidos, está probando un prototipo de sistema de e-mail que podría revolucionar el correo electrónico.
Se trata del SEAmail, un sistema de correo electrónico semántico que permitirá a los usuarios dirigir mensajes a personas, sin que haya que conocer necesariamente su dirección,… o ni tan siquiera sus nombres.

Los envíos los establece SEAmail a partir de un nuevo tipo de información: aquélla que permite agrupar o definir a los receptores de los mensajes en conjuntos semánticos.

Búsqueda mediante claves

Según explica Michael Genesereth, un profesor de ciencias computacionales de Stanford y uno de los artífices de este sistema, en la revista Technology Review, el e-mail tradicional es una forma artificial de dirigir mensajes a personas concretas, al menos generalmente.

Las tecnologías semánticas tratan de hacer que esto sea más sencillo, específicamente con programas informáticos capaces de comprender contextos, de manera que el usuario pueda interactuar con el software de manera más natural. Así, por ejemplo el e-mail semántico es capaz de buscar las personas a las que queremos enviar un e-mail, sólo con que le introduzcamos determinadas claves significativas como, por ejemplo, “profesores graduados en Harvard desde 1960”.

A partir de esta información, SEAmail busca las direcciones de correo electrónico de todos aquellos profesores con estas características, y pone a nuestra disposición el listado de esas direcciones.

Según los investigadores, en SEAmail el usuario selecciona los receptores de un mensaje de manera muy similar a como realizaríamos una búsqueda en una base de datos. Los parámetros pueden ser tan sencillos como el nombre de una persona, o tan complejos como un conjunto de requisitos.

Versión integrada y sencilla

Por eso, para aprovechar al máximo el potencial de este sistema, afirma Genesereth, se necesita tener datos abundantes sobre las personas que están enviándose mensajes entre sí, sus intereses y otras informaciones relevantes. El desafío tecnológico de SEAmail radica en ofrecer una versión integrada de estos datos, a la que se pueda acceder fácilmente.

Actualmente, explican los creadores del sistema en otro artículo, utilizamos listas de correo para enviar a grupos predefinidos de personas, definidas por conceptos demasiado amplios. El nuevo sistema, permite ajustarse mucho más a nuestros requisitos específicos, permitiendo enviar los correos a un conjunto de personas o entidades semánticamente definidas.

Esto permitirá, por ejemplo, que si una persona cambia de e-mail, SEAmail encuentre su nuevo mail y mande el mensaje que inicialmente se quería enviar a la nueva dirección.

Otros beneficios

Otros beneficios del sistema, según sus autores, es que no requiere de mantenimiento. En las listas de correo tradicionales, un administrador debe crear y mantener la lista, cambiando progresivamente la información que ésta contiene. El servidor de SEAmail se adapta automáticamente a los cambios.
Además, este sistema tiene aplicaciones tanto en intranets corporativas (redes de computadores interconectadas) como en Internet.

Así, por ejemplo, dado que las empresas y las organizaciones suelen tener sus bases de datos de información sobre personal, proyectos, clientes, etc., los usuarios de SEAmail podrán aprovechar toda esta información para enviar e-mails basándose en los datos de dichas bases acerca de sus compañeros de trabajo y otras personas vinculadas a su compañía.

En el caso de Internet, recientemente ha ganado popularidad FOAF (Friend Of A Friend), que es un proyecto dentro de la Web semántica para describir relaciones mediante RDF (Resource Description Framework), que puedan ser procesadas fácilmente por las máquinas.

FOAF no tiene aspiraciones comerciales, su organización es horizontal y propone describir relaciones en lenguaje comprensible para los computadores, de manera que se creen redes de relaciones entre amigos. En estas redes la información personal abunda: nombres, e-mails, miembros de los grupos, cumpleaños, intereses, proyectos, etc.

Lo contrario del spam

Desde 2004, 1,25 millones de documentos FOAF están disponibles en Internet, y este número seguirá creciendo. Con SEAmail esta información podrá usarse para enviar e-mails a personas agrupadas en cualquier conjunto semántico.

Con esta libertad de acceso a otras personas, alguien podría sospechar que este sistema propiciará el spam (mensajes no solicitados de contenido publicitario). Pero sus creadores se apresuran en afirmar que el SEAmail es lo contrario del spam, porque éste va dirigido a cualquiera, a todo el que se pueda llegar, mientras que el e-mail semántico se dirige sólo a aquellos posibles interesados, y que han sido definidos semánticamente.

SEAmail será utilizado a finales de este año en Stanford dentro de un proyecto de “departamento digital” que pretende introducir diversas tecnologías semánticas. El departamento de ciencias computacionales utilizará en primer lugar el sistema, pero después se espera que éste se extienda para todos los usuarios de esta Universidad.

Fuente: Tendencias 21

FOAF – Friend Of A Friend – è un progetto che fornisce dei meccanismi per la creazione decentralizzata di una rete di individui in formato machine-readable, che esprima le relazioni che esistono tra le persone e le loro informazioni personali. Per fare ciò, FOAF si appoggia sul modello RDF ed introduce un vocabolario che definisce le proprietà RDF per esprimere le entità e le loro relazioni in FOAF; FOAF può essere vista come una ontologia per il Semantic Web. Il vocabolario FOAF è una fusione di un vocabolario ad-hoc creato appositamente per il progetto e di altri vocabolari già esistenti, come Dublin Core; questa caratteristica è possibile grazie al modello RDF. FOAF utilizza RDF perchè ne acquisisce l’estendibilità e dà la possibilità di combinare le relazioni definite con FOAF con altre definite utilizzando un qualsiasi vocabolario RDF, permettendo al vocabolario FOAF di base di non dover trattare al suo interno ogni possibile aspetto riguardo le persone, che come possiamo immaginare sono molteplici e appartenenti a dominii differenti, sfruttando invece la riusabilità.RDF fornisce anche un insieme di proprietà (oggetti e relativi attributi) che FOAF può sfruttare

La FOAF Vocabulary specification definisce le classi e le proprietà RDF che devono essere utilizzate per creare i documenti FOAF in modo che applicazioni semantiche – o semantic-aware – possano effettuarvi delle elaborazioni; per questo motivo i documenti FOAF devono essere documenti RDF\XML validi.

Analizziamo un esempio di documento FOAF per comprendere la sintassi. Il seguente blocco di codice è stato generato tramite FOAF-a-Matic, un’applicazione JavaScript che genera un FOAF dalle informazioni personali inseriti nei campi di testo dell’apposita scheda.

<rdf:RDF

xmlns:rdf=”http://www.w3.org/1999/02/22-rdf-syntax-ns#”

xmlns:rdfs=”http://www.w3.org/2000/01/rdf-schema#”

xmlns:foaf=”http://xmlns.com/foaf/0.1/“

xmlns:admin=”http://webns.net/mvcb/”>

Dopo la definizione del documento RDF troviamo le namespace declarations per definire gli URIs dei vocabolari dai quali vengono utilizzati i termini che seguono i prefissi rdf:, rdfs:, foaf: ed admin:.

Come possiamo notare troviamo il vocabolario per RDF, RDFS, il vocabolario FOAF ed uno per il prefisso admin:.

Il vocabolario FOAF è identificato dall’URI http://xmlns.com/foaf/0.1/, questo non viene modificato con l’evolversi del vocabolario, quindi presenta ancora la versione 0.1, ma non deve far pensare che il vocabolario si trovi ancora in una versione non-stabile. In questo vocabolario inoltre il concetto di stabilità è definito a livello di termine, per ognuno di questi viene mostrato lo stato (unstable, testing, stable).

<foaf:PersonalProfileDocument rdf:about=”">

<foaf:maker rdf:resource=”#me”/>

<foaf:primaryTopic rdf:resource=”#me”/>

<admin:generatorAgent rdf:resource=”http://www.ldodds.com/foaf/foaf-a-matic”/>

<admin:errorReportsTo rdf:resource=”mailto:leigh@ldodds.com”/>

</foaf:PersonalProfileDocument>

La definizione della persona a cui la descrizione FOAF appartiene è rappresentata con la classe PersonalProfileDocument, con la quale è possibile dire chi ha generato questo codice (foaf:maker) e definire questa persona come primaryTopic della descrizione. In questo caso però vediamo che vengono utilizzati due vocabolari per rappresentare la risorsa, infatti vediamo altre due proprietà con il prefisso admin:, quindi che fanno riferimento ad un altro vocabolario, all’interno della classe PersonalProfileDocument. Queste due proprietà servono per definire l’URI del software con cui il proprietario del documento FOAF ha generato questo codice (generatorAgent) e per definire a qule indirizzo devono essere comunicati eventuali errori del documento (errorReportsTo).Questo è un esempio di estendibilità del modello RDF, che FOAF eredita basandovici.

In questo modo abbiamo detto che la persona cui si riferisce il FOAF ne è il creatore ed ha utilizzato il software specificato all’URL http://www.ldodds.com/foaf/foaf-a-matic per generarlo.

<foaf:Person rdf:ID=”me”>

<foaf:name>Simone Dezaiacomo</foaf:name>

<foaf:title>Sig.</foaf:title>

<foaf:givenname>Simone</foaf:givenname>

<foaf:family_name>Dezaiacomo</foaf:family_name>

<foaf:nick>deza</foaf:nick>

<foaf:mbox_sha1sum>0c4fb8c1cc504e824daff59fc8aa113183a3075d</foaf:mbox_sha1sum>

<foaf:homepage rdf:resource=”semanticweb30.wordpress.com”/>

<foaf:depiction rdf:resource=”http://www.flickr.com/photos/34369927@N05/3199121418/”/>

<foaf:phone rdf:resource=”tel:+39-333-4*******”/>

<foaf:schoolHomepage rdf:resource=”www.internet.unibo.it”/>

Prima parte della definizione delle informazioni riguardante la persona cui il FOAF si riferisce; queste sono rappresentate tutte come proprietà all’interno della clase Person che, come ci si può immaginare, identifica una persona. La chiarezza dei nomi delle proprietà permette di non dilungarsi sul loro significato, notiamo che il valore di queste è espresso nell’attributo rdf:resource= se si tratta di URI, mentre per proprietà come name e givenname vengono inseriti come contenuto dell’elemento.

L’indirizzo email è stato codificato con SHA1 per proteggerlo, viene quindi riportata la stringa corrispondente alla codifica invece che l’indirizzo email completo in alternativa sarebbe stato possibile rappresentarlo “in chiaro”:

<foaf:mbox rdf:resource=”mailto:dezamail@gmail.com”/>

Con questo blocco di codice abbiamo detto che la persona identificata dall’indirizzo email dezamail@gmail.com ha come nome Simone, cognome Dezaiacomo, la sua homepage è all’indirizzo semanticweb30.wordpress.com, etc…

<foaf:knows>

<foaf:Person>

<foaf:name>Elena M</foaf:name>

<foaf:mbox_sha1sum>1206dcfb6be843b295fff6148c90757e89f1f40d</foaf:mbox_sha1sum>

</foaf:Person>

</foaf:knows>

Questo blocco di codice rappresenta un amico della persona descritta nel FOAF, il cuore delle possibilità che FOAF introduce.

Tramite la proprietà knows, viene specificata una persona che ha una relazione di qualche tipo – non necessariamente amicizia, ma una conoscenza in generale – con la persona descritta nel blocco di codice precedente. Il conoscente viene descrito utilizzando le stesse classi e proprietà della persona “soggetto” del FOAF e nel caso in cui l’amico possedesse un profilo FOAF, è bene inserirlo come proprietà seeAlso indicando l’URL al quale si trova

<rdfs:seeAlso rdf:resource=”www.sito-del-conoscente.com/foaf.rdf”/>

per permettere la creazione di una rete di FOAF. Possono essere chiaramente descritti più conoscenti per la stessa persona all’interno dello stesso documento FOAF.

…

</foaf:Person>

</rdf:RDF>

Una volta creato il codice e salvato il file (ad esempio foaf.rdf), è necessario caricarlo sul proprio spazio web in modo che possa essere riconosciuto dai crawler,per facilitare questa operazione è consigliato inserire nella HEAD della propria homepage la seguente riga di codice:

<link rel=”meta” type=”application/rdf+xml” title=”FOAF” href=”foaf.rdf” />

che punta al file rdf inserito.

Le possibilità di utilizzo di FOAF sono diverse, anche grazie all’estendibilità permessa da RDF; nell’esempio appena visto sono state utilizzate solo alcune delle proprietà disponibili. Il vantaggio dell’utilizzo del modello RDF si nota soprattutto in termini di aggregazione ed elaborazione delle descrizioni FOAF ed in questo sta la differenza sostanziale tra un profilo generato con FOAF ed i profili personali creati sui vari social network, ai quali è comunque possibile fare riferimento all’interno della descrizione FOAF utilizzando la proprietà holdsAccount e descrivendoli con la classe OnlineAccount. In questo modo un accesso alla risorsa rdf fornisce informazioni dettagliate sui diversi aspetti dell’utente cui si riferisce.

Come abbiamo detto FOAF nasce per creare informazioni “machine-readable” sugli individui ma è comunque utile poter visualizzare queste informazioni, quindi sono stati sviluppati alcuni strumenti che permettono una visualizzazione e gestione “human-oriented” del profilo FOAF, un esempio sono i FoaF Tools creati da Morten Frederiksen.

E’ inoltre possibile inserire il proprio FOAF all’interno di pagine XHTML utilizzando RDFa, in questo modo non è necessario il file .rdf associato ed i browser potranno rilevare la presenza del profilo FOAF direttamente dalla pagina, ad esempio se si utilizza il plug-in Semantic Radar per Firefox.

W3C SWEO

Il Linking Open Data è un progetto del W3C SWEO che ha lo scopo di estendere il Web creando una rete di dati aperti e disponibili a tutti – offerti dall’ Open Data Movement – pubblicando in formato RDF insiemi di dati provenienti da diverse sorgenti e connettendone gli elementi definendo le relazioni che esistono tra questi, in modo da poter passare da un informazione ad un’altra a questa legata anche se appartengono a due sorgenti diverse; questa possibilità vale anche per i crawler dei motori di ricerca, facilitando il recupero delle informazioni. Questo progetto copre diversi dominii di riferimento delle risorse ed è un esempio di evoluzione verso il data-web globale, che può essere sfruttato dalle applicazioni semantiche.

Insiemi di dati del LOD

Come possiamo vedere dal grafico sono diversi i progetti che supportano il LOD. Tra questi uno dei più rilevanti è DBpedia.

DBpedia è un progetto che recupera i dati presenti negli articoli di Wikipedia e li raccoglie strutturandoli e rendendoli disponibili sul web in formato RDF. La knowledge base di DBpedia attualmente comprende circa 274 milioni di triple RDF (fonte DBpedia.org, Novembre 2008) riferite ad elementi appartenenti a diversi dominii – persone, film, musica, luoghi, organizzazioni – e raccolte da 14 versioni localizzate di Wikipedia, che lo rendendono uno dei mattoni principali del “Web of Data”.
Gli elementi in DBpedia vengono definiti tramite gli URI nella forma

http://dbpedia.org/resource/Elemento_esempio

dove Elemento_esempio è il nome della risorsa recuperata dall’URL relativo a questa su en.wikipedia.org:

http://en.wikipedia.org/wiki/Elemento_esempio

In questo modo DBpedia può essere anche vista come un’ontologia multi-dominio (caratteristica che la differenzia notevolmente dalla maggior parte delle ontologie che trattano un dominio singolo) che definisce univocamente – tramite gli URI, appunto – diverse entità che possono essere riusate, ad esempio, in un profilo FOAF personale per descrivere un certo interesse che altrimenti non sarebbe identificabile, oppure per definire tag in maniera strutturata con Faviki.
Le risorse catalogate in DBpedia possiedono inoltre delle proprietà che le definiscono, come un abstract (nelle lingue per cui è disponibile) che le descrive, la categoria di appartenenza, le informazioni della relativa Infobox, collegamenti a pagine HTML con dbpedia:resource o foaf:homepage o a documenti RDF con owl:sameAs, coordinate geografiche.
Al di là dell’enorme quantità di dati che rende disponibile sul web, il progetto DBpedia è di grande importanza poichè permette il collegamento di queste risorse con altre provenienti da sorgenti diverse, come ad esempio gli 85000 link con il database geografico Geonames , e la pubblicazione dei dati in formato RDF ne rende possibile il riuso e fa sì che possano essere effettuate delle query SPARQL complesse sugli articoli di Wikipedia, che invece supporta solo la ricerca basata sulle keyword, utilizzando tools come SNORQL Query Explorer.

It is probably fair to say that FOAF is where the social web meets the semantic web. FOAF, which has been around for a while now, basically creates a machine readable graph of the sort of information you might include on sites like facebook, myspace etc. Your FOAF file can include links to people you know, your interests and other personal information. It is probably also fair to say that FOAF files were, until now, the sole property of the geek. However, this has changed, and a number of social networking sites such as livejournal, identi.ca and friend feed build FOAF files from your profile information (are there others?). At least now you don’t need to know how to edit RDF in order to have your own FOAF file. Despite that, these profiles are limited by the features offered on the respective sites.

Recently though QDOS launched a new service that makes FOAF profiles extremely easy to build. This service allows uses to create a FOAF profile generated from information contained in your last.fm, livejournal and flickr profiles as well as importing existing FOAF files. You are then given the option to manually enter other information. Furthmore, you can create a public and private view of your FOAF file. I would not recommend including information like your address, phone number or date of birth in a public FOAF file.  So what are you waiting for – go building yourself a FOAF file and join the linked data web.  My FOAF profile can be found here (my original one is maintained here).

For any linked data geeks one other interesting thing about the QDOS FOAF builder is that it has started linking music data from last.fm to the new music linked data service from the BBC. Hopefully this will be just the beginning and we’ll see links to other linked data services from DBpedia, geonames and Ordnance Survey.

Teaching a six year old about Triples, by Leigh Dodds. Some rights reserved.

Content modeling & FOAF — this is really very good stuff — you should read these then subscribe to Paul’s blog

Paul’s experiments with FOAF and Doctor Who
“I chose the first ever episode of the show, from 1963. This featured four main characters, and thanks to the workshop from Yves and the others, I had an inkling of an understanding of how to create FOAF profiles. The results can be seen here (best viewed if you use a Firefox plugin like Tabulator). So far so good. I then linked each character to the other, using the simple ‘knows’ relationship. Finally, to get my linked open data brownie points, I linked each character to its DBpedia equivalent, using the OWL ’same as’ relationship.” Modeling Doctor Who is going to be cool esp if Paul looks at the different incarnations of the Doctor (different actors + different version).

Part three of Paul’s investigation into fictional content modeling and FOAF
One thing that has come up in the discussions, though, is that there’s perhaps two elements to what I’m trying to achieve. The first is to link existing ontologies and, if needed, build a new one, to help describe the narrative content of ’stories’ within the context of television and radio programmes. The second is to experiment (and for me to learn) with existing ontologies, again, linking them up, to build dynamic and interesting webpages that work on linked data principles.

SUDS an ontology (an extension to FOAF) for Soap operas [author stream presentation]
Celia Romaniuk’s presentation on SUDS and it’s application to Eastenders. 

Visualising radio — I can’t but applaud the team and I love the technology but does the idea make sense? I’m not so sure…

… a bit like ‘enhanced podcast’ (you know podcasts with pictures) because my iPod lives in my pocket as far as I’m concerned the images are just a waste of bandwidth; likewise visual radio. That said it’s well worth checking out.

Visual radio launch announced [BBC Radio Labs]
Snippets of information delivered over http to visualise the Chris Moyles show.

Visualising Radio, pushing, not pulling [whomwah.com]
A bit of technical background from Duncan. “So, the big news here is that we are pushing and not pulling. Ordinarily, you would request a webpage using your browser and a some data would be returned. The only way that you would then subsequently see any changes to that data, would be if you requested it again, or if something on that page requested it for you, maybe via polling.”

These are just great…

In Search of Cultural Identifiers [BBC - Radio Labs]
Getting this stuff right is really the first job in any web project. Identify the objects you want to talk about and model the relations between those objects. The key point is to ensure the things you model map to user’s mental models of the world. User centric design starts here and if you choose to model and expose things that users can’t easily comprehend no amount of product requirements or personaes or storyboards will help you out. For want of a better label we A&M types often refer to this work as ‘cultural identifiers’. One identifier, one URL, one page per cultural artifact, all interlinked. It’s something that Wikipedia does better than anyone. One page per concept, one concept per page. bbc.co.uk could be a much more pleasant place to be if we can build something similar for the BBC.

Teaching a Six Year Old About Triples [Lost Boy]
“I suggested to him that we try drawing it out. I thought that this might help him get a better mental picture. I explained to him that we could try writing down the characters names and start drawing lines between them to illustrate the relationships. He got it straight away.” This is brilliant and shows just how intuitive RDF is.

Wikipedia over DNS [DgL]
“I had written some code to take wikipedia articles and summarise them. I wanted to offer this for use in various places, now the obvious way to offer it is just a web service (via REST, SOAP, etc), but that’s boring and I had a cunning plan. Why not offer it over DNS – it is basically a huge associative array and DNS is designed for this stuff. So I wrote a little nameserver which returns the results as TXT records. There are some obvious limitations for example responses are limited to around 430 bytes (it only does UDP). It has advantages too, it gets cached at your nameserver and it is also faster than HTTP (no need to setup a TCP session).” Such a cool idea and lovely URLs too.

I set out to read all the 72 papers for this workshop, as I think it should be very interesting (if a little chaotic perhaps if 100s of people come), though I can’t attend. It’s possible others might find the tiny reviews of the papers below useful so I thought I might as well post them here (I’m up to number 42; it’s taking longer than I thought!). Please don’t be offended if I seem dismissive of your paper – inevitably the reviews reflect my interests and preferences, and with 72 papers to get through, I’ve not been able to spend a huge amount of time on each one. So far, I liked 8, 12, 22, 25, 28, 29, 35, 36, 38 particularly, and all the mobile phone companies papers are worth a read to see what their ideas are in this area. I’ll pull out some themes along with the remaining reviews later today.

Update: part 2 is here.

Sorry the post is so huge…

1. The mobile smoking room (pdf) HIQ, Vibeke Wara

Interesting idea (build something that enables informal communication across a company and engages people in shaping their corporate environment as much as a smoking room) but very general – no explicit proposal.

2. Climbing towards trust and privacy management in social mobile communities (pdf) Alberto Crespo, Rubén Méndez (ATOS ORIGIN) and Katja Liesebach (Goethe-Universität Frankfurt)

Much of the paper seems to be from an EU project proposal; ATOS origin’s section is more interesting and a list of suggested topics for the workshop is good to have (I wonder if in future it would help if this was required of all papers?)

3. The Future of Social Networking Michael Chisari, Appleseed Project

Sole developer talking about his experiences creating distributed social networks and the implications for privacy and trust – worth a skim, and points for using html.

4. The Future of The Appleseed Platform Michael Chisari, Appleseed Project

Describes a distributed social networking project, designed to be a pltform for distributed social networking, including multiple identities, multi-lingual support. Some would question some of his technology choices (IM2000) and modelling choices (are several identities necessary?). Not clear to me how this differs from say, Ning, except in being open source.

5. Social TV: A new wave of Social Networking for Television (pdf) Soohong Daniel Park, Samsung Electronics

Brief paper about (IP)TV and social networking (chatting, presence etc). All rather familiar to me because of Joost. Would like social TV issues to be considered by any W3C XG.

6. Security issues in the future of social networking (pdf) Giles Hogben, ENISA

More weighty summary of some of the issues with social networks pertaining to online identity management, coming mostly from a workshop held by ENISA: “a Centre of Expertise for the EU Member States and EU Institutions in Network and Information Security, giving expert advice and recommendations”. Suggests techniques for maintaining social reputation using PGP keys

7. Information analysis in mobile social networks for added-value services (pdf) Christos Zigkolis, Informatics and Telematics Institute (Greece), Yiannis Kompatsiaris, Informatics and Telematics Institute (Greece), Athena Vakali, Department of Informatics, Aristotle University (Greece)

Part of an EU project; arguing that automated extraction of social network data can be beneficial in the mobile area. Some of their logic is not terribly convincing in parts, though I suppose they may well be right nevertheless.

8. Position Paper from Telefonica (pdf)David Sainz González, Maria Cristina, Fernández Grande, Jordi Rovira Simón, Telefonica

Creating contexts using data from mobile devices and their sensors; generate social graphs using data, weighted by, say, location; data mining and profiling for more presonalised applications, recommendations. Considerations of UI, semi-automation and security. Interesting.

9. Position Paper from Universidad Politécnica de Madrid (DIT) (pdf) Joaquín Salvachúa, Antonio Tapiador, Antonio Fumero, Javier Cerviño, Juan Quemada, Universidad Politécnica de Madrid (DIT)

Interesting idea – weakly-linked, temporary organisations for doing specific projects, and all that entails for security. OAuth and OpenID namechecked, slightly odd ‘we thought of it first’ attitude about the various social APIs that are around

10. The social network behind telecom networks (pdf) Luis Ángel Galindo (Telefónica Spain), David Moro (Telefónica R&D), David Lozano (Telefónica R&D),

Similar to paper 8, unsurprisingly, given it’s the same company. Idea to generate a social network site from phone contacts, so no joining the network costs; syncing phone contacts with the social site; automatic provision of lifestreaming. They have an initiative – wims20.org. Slightly sinister because of the implication that they can use the carrier infrastructure to gather private data. No discussion of security or privacy implications.

11. Open architecture for multilingual social networking (pdf) M.T. Carrasco Benitez.

A brief discussion of desired features and architecture of multilingual and localised websites, specifically UI features, backend services, mention of the possibility of translation services to connect users on social networking sites. Explicitly not the opinion of the contributor’s employer, the EC. http://multilingualwebsites.org

12. Online Presence in Social Networks (pdf) Milan Stankovic (Université Paris-Sud XI, Orsay, France), Jelena Jovanovic (University of Belgrade, Belgrade, Serbia)

Describes the reasoning behind the the Online Presence Ontolology (OPO), that gives structure to statements about presence (using foaf, sioc, geo etc), and the possibility of using this information to govern kinds of interaction with the user, when gathered from multiple sites. http://www.milanstankovic.org/opo/. Interesting idea – I wonder how they would create the structured data.

13. Africa: A mobile frontier (pdf) Gloria Ruhrmund

States that mobile social networks may be a very good fit for Africa, possibly commercial, also NGOs, governments; vague about exactly how; notes that MSN South Africa is popular, and that airtime is now an informal currency in parts of Africa.

14. Position Paper from German National Library (pdf) Panagiotis Kitmeridis, Anne Löhden, Dr. Lars Svensson, German National Library

Discussion of plans to add user generated content (selection, quality rating, characterisation of resources) to libraries, and indicating that social networks (groups with different access levels) might improve the trustworthiness and accuracy of UGC in this context.

15. Position Paper from University of Reading Shirley Williams, Pat Parslow, Karsten Oster Lundqvist, University of Reading

A new technology requires adaptation and people don’t always realise the consequences of their digital identity (how they appear online to others), particularly if they have multiple identities in different social networks. “There is also anecdotal evidence of users increasingly using disparate systems to facilitate communication with different groups of peers, either through explicit choices being made or because they have to subscribe to the services already in use by their friends and colleagues.” learning / education perspective. And in html

16. XDI Trust Information – A Trustability Protocol for Validating Distributed Information (pdf) Elizabeth Cano, Gregoire Burel, University of Sheffield, UK

Describes the use of two oasis-homed TLAs to validate information about a person by them establishing a ‘contract’ with someone who can validate the information, using as special type of link. If no contracts is present, XTI can allow you to access other documents from the site, and look at those recursively looking for validation. “XRIs (Extensible Resource Identifiers) address a longstanding problem on the Internet: how to have a persistent, portable, privacy-protected identifier for any resource, from a person to a company to an application to a concept. XDI (XRI Data Interchange) uses XRIs to securely and privately share, link, and synchronize data between any two devices, domains, or applications – and maintain this link for as long as the two parties want to keep a data sharing relationship.” (from http://www.xdi.org/faq.html).

17. Leveraging Web 2.0 Communities in Professional Organisations (pdf) A. Scherp (University of Koblenz), F. Schwagereit (University of Koblenz), N. Ireson (University of Sheffield), V. Lanfranchi (University of Sheffield), S. Papadopoulos (Informatics and Telematics Institute, Greece), A. Kritikos (Informatics and Telematics Institute, Greece), Y. Kompatsiaris (Informatics and Telematics Institute, Greece), P. Smrz (Brno University of Technology, Czech Republic)

A discussion of the contrasts between tradition organisational structures and web 2.0 ones and specific discussion of the potential to use user generated content in the emergency services for disasters. Suggests that process-mining of virtual organsations can be used to generate workflow models that might bridge this gap.

18. Tangibility in social networks – Easing interactions with social networks in mobility using proximity sensor technologies (pdf) Antoine Fressancourt, Colombe Hérault, Eric Ptak, Atos Worldline R&D

Describes an aplication that uses NFC (Near Field Communication, an extension of RFID for mobile devices) that allows the user to voluntarily state his location and then distributes the location information via a centralised server to various social networks, having been run through user-defined privacy rules first. Incentives include getting contextually-appropriate apps to mobile devices. Potentially interesting ideas.

19. Leveraging Social data with Semantics Guillaume Erétéo (Orange Labs), Michel Buffa (Université Nice Sophia Antipolis, Kewi Team, CNRS/I3S), Fabien Gandon (INRIA), Mylène Leitzelman (Telecom ParisTech), Freddy Limpens (INRIA)

(More) semantics can be added to social networks by looking at social interactions in those networks (mostly path computations) and then adding this new data to the description of the network using ontologies. This is done using sparql extensions. Connecting the content in these networks (folksonomies) to ‘common references’ like dbpedia, or other taxonomies helps create “shared knowledge graphs”. Combined, this can make sense of the mass of data generated by social wetworks.

20. Instant Feeds for Social Networks (pdf) Gustavo García, Telefonica I+D

Makes a technical point about the efficiency of presence networks and the requirement to be instantly informed when data changes, and the high load this places on servers. Suggests using the combination of openid attributes or XRDS for discovery; oauth for authorisation; and atompub or SIP or XMPP for distribution.

21. Privacy and Social Network Sites: Follow the Money! (pdf) Martin Pekárek, Ronald Leenes, Tilburg Institute for Law, Technology and Society (TILT)

Analysis of the types of harm caused by attacks on privacy in social networks, as well as the types of attackers, including harm from the networks themselves selling user profile data. Concludes that the benefits to users of using social networks are high albeit short term and so they are unlikely to stop; suggests best thing might be to discourage the profit motive of companies who can currently do more or less what they like with user profile data. Suggests a p2p system might work.

22. Position Paper from Vodafone Julian Pye, Wolfgang Schuster, Vodafone

Useful list of their interests in the second paragraph. The body of the paper is about differences in the ways people use social networks on mobile devices compared to stationary ones. Using different states of the user (or times of the day, family time, leisure, work time) suggest different modes of social interaction (lean-forward, lean back, on-the-go contexts) and so different modes of the device (e.g. business contacts first). Lots of interesting ideas, and html to boot.

23. Position Paper from Peperoni (pdf) Marcus Ladwig, Peperoni

Large mobile portal suggests that there’s a large potential untapped market for mobile social networking, presently untapped because of the various issues with mobile data access, including scepticism of network operators (p8); suggests the need for industry standards, policies and APIs (p10); and including sharing networks’ user profiling data with advertisers (opt-in)

24. Legal Problems of the social networks (pdf) Pablo Álvarez de Linera Granda, Nelly Sánchez Mouriz, Sofía Cuervas-Mons Ruiloba, J&A GARRIGUES

Legal / privacy issues arising from the use of social networks plus advice on what users and providers should do (respect countries’ privacy laws, allow the deletion of all data created by the user, think before you post, especially if it has to do with children; do not allow spidering of profile data). Declares that international coordination is required; refers to a couple of recent meetings in europe on the topic.

25. Tapping the Mobile Digital Tapestry: Can mobile 2.0 companies make money without being greedy for personal data (pdf) Daniele Quercia, University College London

Interesting paper about sharing data and other items of interest such as music very locally, for example on a wifi access point or using bluetooth, and suggesting that using such a model could open up a non-privacy invading way of making money – by using location-based ads.

26. Identity Management in Social Networks (pdf) Miguel-Angel Monjas, David Suárez, Ericsson España

List of interests page 2-3. Top interests include: use of SIMs as identification mechanisms; tools for handling and tracking one’s own data, knowing how it is used; inferring social networks from behaviour using machine learning; federated identity systems; brokers for authentication, geo.

27. The Social Web: Small Businesses / Big Solutions (pdf) Timothée P. Anglade, Ori Pekelman, Louis Montagne, AF83

Talks about various issues of interest to SME and social networks, specifically the problem that buisness models are currently only about growing the size of the network; suggests some alternative business models, including micropayments for goods or services; emphasising the importance of business models that rely on a common interest for the sites and their users.

28. Trends in mobile social networking for mainstream consumers and supporting technologies required (pdf) Lisa McKnight (Nokia), Lubna Dajani (Stratemerge),

The issues they would like W3C to focus on are in the first section and are mostly about interoperability between social networks; also addressbook interop. They are most interested in non-early adopters, as the market grows. The paper is based on interviews with users. Also worries about the privacy of disclosing geo location. Definitely worth a look this one, though I don’t see the sample size mentioned anywhere.

29. Privacy-Preserving Friendship Relations for Mobile Social Networking (pdf) Sören Preibusch, Alastair R. Beresford, University of Cambridge, UK

Argues that the existance of public friendship links are privacy-intruding because of socio-economic interests that can be inferred; even if the user is able to keen them private, the friends may not. The paper desribes a technique for hashing private relationships using foaf, in a P2P network. Interesting stuff, not sure how you’d make it usable.

30. HelloWorld: An Open Source, Distributed and Secure Social Network (pdf) Markus Ackermann, Krister Hymon, Benjamin Ludwig, Kai Wilhelm, University of Applied Sciences Kaiserslautern, Germany

Long paper describing an open, decentralised social network using pgp keys to encrypt personal information, using downloadable software, and using Freenet, with a centralised ‘phonebook’ and importating contacts using hcard. A prototype is available.

31. Accessible social networking in practice, the GDF-SUEZ experience in France (pdf) Ruddy RACON (GDF SUEZ), Pierre GUILLOU (AccessiWeb).

A large company argues that accessibility can and should be addressed in web 2.0 sites, and has made a social networking site to show that the functionality can be implemented in an accesssible way.

32. The Interoperability of Lightweight Semantics for Social Networks (pdf) Matthew Rowe, University of Sheffield, UK

Describes microformats and RDFA compared with RDF. Argues that interoprability is needed between xfn and foaf; argues that digital identity is important; describing a digital identity card per citizen, including a weighted social network. On joining a new social network, the network could request access to it. OpenID and Oauth. Reputation building over sites. Suggests lightweight semantics could be used to connect people.

33. Social networking across devices: opportunity and risk for the disabled and older community (pdf) Henny Swan, Opera

Argues for the need for accessibility in social networking sites.

34. The Future of Social Networking: Let everyone in, and remember they’re all on the move (pdf) Miquel Martin, NEC Network Laboratories, Heidelberg

Argues for standardised apis for contextual information from device sensors, e.g. geo info, cross platform. Ideas for discussion on page 4.

35. Sentient Computing meets Social Networking (pdf) Simon Hay, Joseph Newman, Andrew Rice, University of Cambridge

Using sensors to infer context “x has just left his desk” – belief that it is now mature enough to be used in social networking. Privacy and interfaces are important. Describes some interesting projects in this area.

36. Decentralization: The Future of Online Social Networking (pdf)Ching-man Au Yeung (University of Southampton), Ilaria Liccardi (University of Southampton), Kanghao Lu (CSAIL, MIT), Oshani Seneviratne (CSAIL, MIT), Tim Berners-Lee (CSAIL, MIT)

Paper describing various semantic web and linked data tools that could be used for distributed social networks: foaf, openID, webdav, SPARUL (Sparql update), tabulator, foaf+ssl; describes how it would address issues such as privacy, data silos, data ownership.

37. Using Standards to Normalize Domain Specific Metadata (pdf) Andrew Mello, Lisa Rein

Automatically enhancing and normalising data streams using semantics (e.g. using RDFA) can enhance the user experience (not clear to me how! maybe I’m just tired though). Describes a marketing application that generates short term social networks by getting users to play games and otherwise interact with a brand to check how a specific marketing campain is going.

38. OpenMicroBlogging Evan Prodromou, Founder of Wikitravel and Identi.ca

Push messages to different services using oAuth and open microblogging protocol (http post messages). Also service discovery using oauth discovery. federated model. Interesting analogy with email and previous data silos.

39. Capturing, Using, and Storing Users’ Locations (pdf) Dan Melinger, Socialight

List of specific questions for discussion on p2-3, mostly about privacy and usability (and understandability) aspects of capturing, sharing and using the user’s location information.

40. Industry Challenges for Social and Professional Networks (pdf) Renato Iannella, National ICT Australia (NICTA)

Describes some issues with social networks (lockin, spamming, privacy issues, confusing UIs, not suitable for mobile). Looking for a ’social networks interop roadmap’ XG for requirements gathering for social networks interop (standards for data portability, policy expression, network migration).

41. Social Networks – Challenges of Ubiquitous Web Access (pdf) Vadym Kramar, Markku Korhonen, Jori Karppinen, Pehr Brahe Software Laboratory (PBOL)

Describes some usecases around the application of mobile technology and the web: context awareness, device cself-configuration and browser experience. Argues that there are already W3C standards in all 3 areas, but more guidance is needed on how to implement them.

42. World Peace Using Social Networks Will Holcomb

A planned project describing a way of creating trustable digital identifiers with xml signatures, unique identifiers and trusted signers.