There are many things that define us as people, over which we have no control. Some of these are obviously decided at a genetic level; colour of your eyes, skin tone…. the fact that I had dead straight hair until I was about 15 and then it went inextricably super-curly almost over night. We’re just born this way and there is no way to fight it. Even with ‘Frizz Ease’.

For many of us, the same goes for sporting allegiance.

As soon as I was old enough to be able to pick out colour and shape, It was pretty clear what life had in store for me. I was dressed in red and white stripes and I was from that moment, I was to be a Saints fan. Getting on for 40 years later and save for a single fleeting day of glory day back in the mid-70s that I can barely remember, I can can almost count my football genes as unsuccessful as my skintone genes (10 minutes outside in a sunny day and I’m generally sporting burns of the same palette as one of those aforementioned stripes).

Right now in the UK, we’re supposed to be in the football ‘Close Season’. All the leagues are done for another year, silverware distributed and players off rapidly gaining weight on their summer holidays whilst keeping half an ear for the mobile call from their agent to alert them to a pre-season move elsewhere.

The reality is of course is that as far as News goes, there is no such thing as a football close season. Arriving back at a London mainline station one afternoon this week to begin the final leg of my journey back to the coast, the giant TV News screen screamed the headline ‘£80m!’, the fee agreed for Cristiano Ronaldo’s transfer from Manchester United to Real Madrid. This, just days after the same buyers had agreed to pay A.C Milan £56m for the services of Kaka.

The next day, I watched a solitary Saints player walking to the ground – at the end of my street – for his preseason fitness tests. Tests which, unless something concrete changes in the next few weeks, might be somewhat redundant. Saints were forced into financial administration at the tail end of last season, an event triggered initially by exceeding an banking overdraft facility by £5k.

There are times when I forget how dense the information is surrounding specialist areas of knowledge and football is a perfect example. Growing up as a kid, we used to collect the the football stickers produced by the Italian company ‘Panini’ and try and get complete collections of the players, grounds and badges of all the top teams stuck into our albums. Of course in the process you gained an increasingly detailed and somewhat arcane knowledge of subject…. even now I don’t have to even think about these things, so ingrained are they in my consciousness.

Sometimes you’ll overhear a football conversation on a train. Someone will mention ‘City’. I can’t help myself wondering which ‘City’ they are talking about. Manchester ? Leicester ? Norwich ? Then you’ll hear something else that helps ‘… down at Dean Court…’. Ahh, ok so they’ve been to A.F.C. Bournemouth, which makes them much more likely to be Lincoln City fans. Or Chester City, Exeter City…. and it’s not until you turn to see them and see Maroon & Gold and know right away that it was actually Bradford City after all. They were Bantams*.

Last time, I talked about Geodata, adding descriptive information specifically related to ‘Places’ that might be found in text (for example geographic coordinates) and some of the opportunities that present themselves when you mix them cleverly into the user experience.

These additional bits of information we can call ‘Attributes’. For example, the city of Southampton, might look like this when described at a geographical level;

Southampton
<Latitude = “N 50° 54′ 0””>
<Longitude = “W 1° 24′ 0””>

That information in itself is enough to plot it onto a mapping application. However, there’s obviously more that we can add. For example, population.

Southampton
<Latitude = “N 50° 54′ 0””>
<Longitude = “W 1° 24′ 0””>
<Population = “246,201″>

Now we can plot this onto a map and also weight the the location pin by the size of city. Of course those vested in the subject will correctly recognise the rather facile nature of the above example and rightly point out that it is massively over simplified. Mapping information is something that is so well covered across the globe (for example in repositories like Geonames and by organisations like OS in the UK), that maintaining this sort of detailed data at a local level (‘Curating’) is just not necessary.

In his recent exemplary article, my colleague Chris Scott posted the question ‘Semantic Web ? What’s in it for me ?’ and whilst I don’t intend to retread what he describes in great detail, there is much in there that will help us here, as we’re beginning to make the journey towards the world of ‘Linked Data’.

What ‘Linked Data’ is beginning to do to a greater or lesser degree is to almost commoditise very high-level generic factual knowledge. Any of us can hook-up applications to ‘The Cloud’ and get hold of ‘attribute’ information which will helps us improve the user experience of our sites. All we need to do is to hold the linkage between us and it, the ‘Uniform Resource Indicator’ (‘URI’) and we can call the data whenever we need it.

However, publishers hold another very precious thing within their organisations; their own specialist information, their own highly valuable ‘Knowledgebase’. For example, what does the average UK newspaper hold in terms of specialist data on football ? Far more than exists currently within recognised Cloud resources for sure.

Looking back at the early paragraphs of this post, it is packed with footballing information, both ‘entities’ (in this case ‘People’ and ‘Organisations’), but also what we could refer to data being ‘attribute’ data of entities themselves.

I’m a Saints fan. In that case ‘The Saints’ could be said to be an ‘Nickname’ attribute for the entity ‘Southampton Football Club’, the same way as ‘The Bantams’ is of  ‘Bradford City Football Club’. When we can categorise an article as being about ‘Football/England’ and we identify ‘Saints’ as a term within the text, we are able to use the presence of that term to be suggest that it is also about the parent term, even if that is not actually present in the text directly. This collection of terms, we can call ‘Orgdata’ and something like club nicknames is barely scratching the surface of the attribute data that can be described against an entity like a football club.

This presents publishers with both choices and opportunities.

By locally curating their own knowledge – and adding their own specialist terms and attributes to the extraction, normalisation and knowledge management capabilities of Text Mining tools such as Nstein’s TME – they are able to additional flavour and richness to that data when they present it to web users. This not only helps build the overall user experience, but also helps enrich the actual content itself, greatly assisting the ability to package data for example, for syndication.

The opportunities of course do not end there. For many areas of specialist knowledge, there is not right now a ‘de facto’ trusted source, no Geonames or IMDB to refer to.

In the Semantic Web where Linked Data is an essential component part, is being that trusted source the next critical step towards making content pay its keep ?

Matt Mullen is an Industry Consultant at Nstein Technologies [http://www.nstein.com].

(* Yes, I realise you’d probably be able to disambiguate in that case by accent. Assuming you’re good at that sort of thing, natch)

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…

Il progetto GeoNames è una banca dati geografica, disponibile gratuitamente sotto licenza Creative Commons. Alcuni numeri dell’archivio: oltre 8 milioni di nomi geografici; 6,5 milioni di entità topografiche; 2,2 milioni di centri abitati.

Grazie a questi dati, è stato possibile estrarre le coordinate geografiche WGS84 (sistema utilizzato dal GPS), di tutti i comuni italiani e convertirle in formato KML per Google Earth.

Visualizza in Google Earth i Comuni raggruppati per Regione:

• Abruzzo
• Basilicata
• Calabria
• Campania
• Emilia Romagna
• Friuli Venezia Giulia
• Lazio
• Liguria
• Lombardia
• Marche
• Molise
• Piemonte
• Puglia
• Sardegna
• Sicilia
• Toscana
• Trentino Alto Adige
• Umbria
• Valle d’Aosta
• Veneto

We’re no longer recognising geonames in the Hansard text, nor are we producing KML files from sitting days.

Although it was an interesting experiment, it wasn’t useful enough in real world usage to enough people. Removing these experimental features means reparsing the source files is quicker.

We’re still working out what to roll out in terms of geographic search features.

One of the common problems with Web Mapping applications is that what end users regard as a place often does not match the ‘official’ place names in the commercial gazetteer data that web mapping services depend on for geocoding.  For example in London everyone knows where “Soho“, “Bloomsbury” and “Big Ben” are, but in reality these are not official place names.  These kind of unofficial place names are often referred to as “Vanity Areas”.  End users rightly expect that there web mapping application will take them to these places, but if we rely on commercial gazetteer data alone this is not enough.

Sp how can we fix this?  Well, Multimap have integrated GeoNames as an additional data source for address look-ups. You can see it in action not only on multimap.com, but also in the Multimap API. 

From the Multimap blog:

GeoNames is a global geographical database that contains over 6.5 million places, with 2 million alternative names in up to 200 languages, that is continuously updated by users around the world, through a friendly wiki interface. Any changes are integrated into the Multimap databases within 24 hours.

GeoNames contains geographic places such as mountains, seas, lakes, valleys, coasts, and places of interest. In addition, it also contains alternative names so you can find a place like ‘London’ in many different languages (Londres, Londra, Londýn, Londain, Londinium).

A great example cropped up recently with a customer I work with.  They had recently developed a new web mapping application and were demoing it to all their local sites.  They knew that one local web master always tested mapping applications by searching for the small hamlet in which they lived in.  This hamlet is so small it does not appear in any of the commercial gazetteers.  So they added this hamlet to Geonames before doing the demo.  When the web master saw the application and found their hamlet they said it was the best web mapping application they had seen!

It is also possible to integrate Geonames with Virtual Earth.  Johannes Kebeck has done a blog post on this. 

In my quest for following biketour (that this year I only spectate), I  dived into the new water of the web and been trying to keep swimming into the same direction

The intention was to have an online diary about what  is happening and happened with biketour, having context (mainly geo, as it is a travel project after all), but making it in way that most of it will “run automatically”

The history:

Well, last year I setup twitter accounts for the group and we use it internally and as a way of updating the website. While twitter is still the best free “tool” in what comes to multi-recipient “on-the-road” sms communication, it also works great for bridging that with the online world. When I resumed this year the “IT task” of biketour, one of my goals was to have twitter better integrated on the website and later on a blog.

Till now, one of the annoyances of twitter is it’s lack of a group feature. This makes the following/followers managing too repetitive, but also noticeable by offering no native combined feeds. One work around was to rely on 3rd parties to aggregate this streams.

I played already last year with Yahoo Pipes, and created a mashup of the organization process feeds. But this year I wanted to address other problems: getting the full text of each “tweet” (?) , and adding geo-references automatically whenever there would be locations mentioned.

Titter full text updates on a new stream :

This pipe is the result of my tests. It scraps , fetches each “tweet” permalink page for its full text , only when there’s “…” in the description (trying not to hammer more their poor servers). I made it ask for a RSS (not user account) because I wanted to feed it with another pipe that provides several accounts feeds, a solution around the close of “with friends”. I’m open to suggestions on how to improve it

Auto post stream geo-referenced (geonames) – for wordpress with geopress and FeedWordPress :

What about combining that feeds with the blog (wordpress)? And why not doing it automatically? That’s was possible with “FeedWordPress” (WP-o-Matic had some problems and FeedWordPress supports deleting at once all the posts imported, which is great for when you are still testing around).

But what if you could also leave all that work of geotagging each post in the hands of the “machines” ?  I am using geopress (geomashup was appealing but had more problems with themes and other plugins) for the geo part , and wanted to turn “tweets” that mention locations in a point in the database and attach a map in the bottom. It’s possible with simple text tags that you can insert on the post itself.

So, I went and tried patching up geonames rsstogeorss (being used a lot within other pipes) with (Find nearby populated place / reverse geocoding) to get the place name (a bit redundant, but geonames doesn’t identify the place found in rsstogeorss). Then, if anything found it would be added to the title and description.

I’m not so satisfied with this results:

• geonames results are worse than expected (and I wasn’t waiting for miracles), but the worse is that when you restrict it to a specific country it thinks that most items are referring to that country indeed. (maybe there’s something involved with feeding it with more than 20 items?)
• yahoo pipes engine itself seems to mess with non-ASCII . While I have something like “Santarém” showing up right in an element, when I copy it as a variable to build a string the text gets messed up

Would love to hear your impressions…

Εκείνο που σε συναρπάζει στην Πόλη είναι η κοσμοπολίτικη ατμόσφαιρα που σώζεται ακόμη και σήμερα, ακόμη και ανάμεσα στα παλιά ερειπωμένα σπίτια στο Σταυροδρόμι, το Ταρλάμπασι (που ιστορικά είχε μεγάλο αριθμό ελληνικού πληθυσμού) και στο Τεπέμπασι.

Ετσι, είναι πολύ φυσικό να θες να ξέρεις πώς ονομάζεται η Κωνσταντινούπολη σε διάφορες γλώσσες του κόσμου, αφού παντού βλέπεις ξένους που ζουν, εργάζονται εκεί ή απλώς την επισκέπτονται.

Ο δικτυακός τόπος geonames.de μας δίνει την ευκαιρία να το μάθουμε, αφού έχει συλλέξει πληροφορίες ακόμη και από γλώσσες άγνωστες, σπάνιες ή και τοπικές ακόμη διαλέκτους! Επέλεξε το πώς θα προφέρεις ή θα γράψεις τη λέξη “Κωνσταντινούπολη”, ανάμεσα στα … αμπχαζικά (Abkhaz, abk), τα κρεολικά της Αγίας Λουκίας (Saint Lucia Creole, acf), τα εξαφανισμένα αραμαϊκά (Aramaic, arc), τα γαελικά της Ιρλανδίας (Irish Gaelic, gle) ή ακόμη και τα ζουλού (Zulu, zul) !!! Τον κωδικό της κάθε γλώσσας θα τον βρεις εδώ. Ξεκινάω κι επαναλάμβανε μετά από κάθε λέξη

• eng | fra | nor | swe: Istanbul
• deu | ltz | nds: Istanbul / Iſtanbul
• glg | por | tgl: Istambul
• ast | spa: Estambul
• aze | crh: İstanbul / Истанбул
• arg: Estambul; Istambul
• bre: Kergustentin
• ces: Cařihrad; Konstantinopol
• epo: Istanbulo
• gle: Iostanbúl / Iostanbúl; Istambúil / Istambúil
• hau: Santambul
• hun: Isztambul
• isl: Istambúl
• kur: Îstembul / ئیسته‌مبول; Stenbol / سته‌نبۆل; Stembol / سته‌مبۆل
• lat: Constantinopolis; Byzantium
• lav: Stambula
• lit: Stambulas
• mol: Istambul / Истамбул
• nld: Istanboel
• non: Mikligarðr; Miklagarðr
• oci: Istambol
• pol: Stambuł
• slo: Istanbul / Истанбул
• slv: Carigrad
• som: Istanbuul
• sqi: Stambolli
• tuk: Ystambul / Ыстамбул
• tur: İstanbul
• uzb: Istanbul / Истанбул
• zza: Estamol
• chu: Цѣсарьградъ (Cěsarĭgradŭ); Цьсарьградъ (Cĭsarĭgradŭ); Царьградъ (Carĭgradŭ)
• chv | rus | ukr: Стамбул (Stambul)
• ava | tab: Истамбул (Istambul)
• abk: Сҭампыл (Sṭampəl)
• bel: Стамбул / Stambuł
• bul: Истанбул (Istanbul)
• che: Уьстмала (Üstmala)
• kaz: Ыстанбұл / Istanbul / ىستانبۇل; Ыстанбыл / Istanbıl / ىستانبىل
• kbd: Истамбыл (Istambəl)
• kir: Ыстамбул (Ystambul)
• srp: Истамбул / Istambul
• tat: Истанбул / İstanbul
• tgk: Истанбул (Istanbul) / استنبول (Istanbūl); Истомбул (Istombul) / استامبول (Istōmbūl)
• ara: إستانبول (Istānbūl); إسطنبول (Isṭanbūl); إسطانبول (Isṭānbūl)
• ckb: ئه‌سته‌مبوڵ / Estembuḻ
• fas: استانبول (Estānbūl); استامبول (Estāmbūl); استنبول (Estanbūl); اسلامبول (Eslāmbūl)
• pus: استانبول (Istānbol); ستامبول (Stāmbūl)
• snd: استنبول (Istanbūlu)
• uig: ئىستامبۇل / Istambul
• urd: استنبول (Istanbūl)
• syr: ܐܝܣܛܢܒܘܠ (Īsṭanbūl)
• heb: איסטנבול (Îsṭanbûl); איסטאנבול (Îsṭânbûl)
• lad: קושטה / Kushta
• yid: איסטאַנבול (Istanbul)
• ell-dhi: Κωνσταντινούπολη (Kōnstantinoýpolī); Ισταμπούλ (Istampoýl); Πόλη
• ell-kat: Κωνσταντινούπολις (Kōnstantinoýpolis); Ἰστανμπούλ (Istanmpoýl); Πόλις
• hye: Ստամբուլ (Stamboul)
• kat: სტამბოლი (Stamboli); სტამბული (Stambuli)
• hin: इस्तांबुल (Istāṁbul); इस्तांबूल (Istāṁbūl); इस्तानबुल (Istānbul)
• mar: इस्तंबुल (Istaṁbul); इस्तंबूल (Istaṁbūl)
• nep: इस्टानबुल (Isṭānbul)
• guj: ઇસ્તન્બુલ (Istanbul)
• pan: ਇਸਤਾਨਬੁਲ (Istānbul); ਅਸਤੰਬੋਲ (Astaṁbol)
• kan: ಇಸ್ತಾಂಬುಲ್ (Istāṁbul)
• tam: இஸ்தான்புல் (Istāmpūl)
• tel: ఇస్తాన్బుల్ (Istānbul)
• zho: Yīsītǎnbǎo
• jpn: Isutanburu; Isutanbūru
• kor: Iseutanbul
• tha: อิสตันบูล (Ittânbūn)

The School of Everything went international yesterday. We launched in New York at the NY Tech Meetup, which is terribly glamorous of course, but the exciting bit for me was the process back at Everything HQ of getting our new international locations system working.

We’ve implemented the open gazetteer source Geonames as our locations database, so rather than using the very UK-specific “postcode” lookup we’re now handling everything based on names of localities. You enter your location, such as “Clapham” or “Felixstowe”, we look it up in Geonames and assign you a location on the map. If Geonames picks the wrong Clapham, we’ve added a neat disambiguation tool so you can choose which Clapham is right for you.

The data is easy to change in the Geonames database (via their site), which means if your location isn’t listed currently, you can add it. We’re hoping that over time we can encourage lots of web projects to standardise on Geonames, so that in time we can refine it to be a really comprehensive, open geolocations system for everyone to share.

Take a look at www.schoolofeverything.com now, create a teacher profile, have a play with it and let me know what you think. And if you’ve got friends around the world who have something to teach, tell them about us!