Category Archives: semantic web

culture | information architecture | KO | semantic web

Serendipity and large video collections

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Estimated reading time 2–2 minutes

I enjoyed this blog post: On Serendipity. Ironically, it was recommended to me, and I am now recommending it!

Serendipity is rarely of use to the asset manager, who wants to find exactly what they expect to find, but is a delight for the consumer or leisure searcher. People sometimes cite serendipity as a being a reason to abandon classification, but in my experience classification often enhances serendipity and can be lost in simple online search systems.

For example, when browsing an alphabetically ordered collection in print, such as an encyclopedia or dictionary, you just can’t help noticing the entries that sit next to the one you were looking for. This can lead you to all sorts of interesting connections – for example, looking up crescendo, I couldn’t help noticing that crepuscular means relating to twilight, and that there is a connection between crepe paper and the crepes you can eat (from the French for “wrinkly”), but crepinette has a different derivation (from the French for “caul”). What was really interesting was the fact that there was no connection, other than an accident of alphabetical order. I wasn’t interested in things crepuscular, or crepes and crepinettes, and I can’t imagine anyone deliberately modelling connections between all these things as “related concepts”.

Wikipedia’s “random article” function is an attempt to generate serendipity alogrithmically. On other sites the “what people are reading/borrowing/watching now” functions use chronological order to throw out unsought items from a collection in the hope that they will be interesting. Twitter’s “trending topics” use a combination of chronological order and statistics on the assumption that what is popular just now is intrinsically interesting. These techniques look for “interestingness” out of what can be calculated and it is easy to see how they work, but the semantic web enthusiasts aim to open up to automated processing the kind of free associative links that human brains are so good at generating.

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information architecture | KO | libraries and museums | search | semantic web

Online Information Conference – day two

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Estimated reading time 6–10 minutes

Linked Data in Libraries

I stayed in the Linked Data track for Day 2 of the Online Information Conference, very much enjoying Karen Coyle‘s presentation on metadata standards – FRBR, FRSAR, FRAD, RDA – and Sarah Bartlett‘s enthusiasm for using Linked Data to throw open bibliographic data to the world so that fascinating connections can be made. She explained that while the physical sciences have been well mapped and a number of ontologies are available, far less work has been done in the humanities. She encouraged humanities researchers to extend RDF and develop it.

In the world of literature, the potential connections are infinite and very little numerical analysis has been done by academics. For example, “intertextuality” is a key topic in literary criticism, and Linked Data that exposes the references one author makes to another can be analysed to show the patterns of influence a particular author had on others. (Google ngrams is a step in this direction, part index, part concordance.)

She stressed that libraries and librarians have a duty of care to understand, curate, and manage ontologies as part of their professional role.

Karen and Sarah’s eagerness to make the world a better place by making sure that the thoughtfully curated and well-managed bibliographic data held by libraries is made available to all was especially poignant at a time when library services in the UK are being savaged.

The Swedish Union Catalogue is another library project that has benefited from a Linked Data approach. With a concern to give users more access to and pathways into the collections, Martin Malmsten asked if APIs are enough. He stressed the popularity of just chucking the data out there in a quick and dirty form and making it as simple as possible for people to interact with it. However, he pointed out that licences need to be changed and updated, as copyright law designed for a print world is not always applicable for online content.

Martin pointed out that in a commercialised world, giving anything away seems crazy, but that allowing others to link to your data does not destroy your data. If provenance (parametadata) is kept and curated, you can distinguish between the metadata you assert about content and anything that anybody else asserts.

During the panel discussion, provenance and traceability – which the W3C is now focusing on (parametadata) – was discussed and it was noted that allowing other people to link to your data does not destroy your data, and often makes it more valuable. The question of what the “killer app” for the semantic web might be was raised, as was the question of how we might create user interfaces that allow the kinds of multiple pathway browsing that can render multiple relationships and connections comprehensible to people. This could be something a bit like topic maps – but we probably need a 13-year-old who takes all this data for granted to have a clear vision of its potential!

Tackling Linked Data Challenges

The second session of day two was missing Georgi Kobilarov of Uberblic who was caught up in the bad weather. However, the remaining speakers filled the time admirably.

Paul Nelson of Search Technologies pointed out that Google is not “free” to companies, as they pay billions in search engine optimisation (SEO) to help Google. Google is essentially providing a marketing service, and companies are paying huge amounts trying to present their data in the way that suits Google. It is therefore worth bearing in mind that Google’s algorithms are not resulting in a neutral view of available information resources, but are providing a highly commercial view of the web.

John Sheridan described using Linked Data at the National Archives to open up documentation that previously had very little easily searchable metadata. Much of the documentation in the National Archives is structured – forms, lists, directories, etc. – which present particular problems for free text searches, but are prime sources for mashing up and querying.

Taxonomies, Metadata, and Semantics: Frameworks and Approaches

There were some sensible presentations on how to use taxonomies and ontologies to improve search results in the third session.
Tom Reamy of KAPS noted the end of the “religious fervour” about folksonomy that flourished a few years ago, now that people have realised that there is no way for folksonomies to get better and they offer little help to infrequent users of a system. They are still useful as a way of getting insights into the kind of search terms that people use, and can be easier to analyse than search logs. A hybrid approach, using a lightweight faceted taxonomy over the top of folksonomic tags is proving more useful.

Taxonomies remain key in providing the structure on which autocategorisation and text analytics is based, and so having a central taxonomy team that engages in regular and active dialogue with users is vital. Understanding the “basic concepts” (i.e. Lakoff and Rosch’s “basic categories”) that are the most familiar terms to the community of users is vital for constructing a helpful taxonomy and labels should be as short and simple as possible. Labels should be chosen for their distinctiveness and expressiveness.

He also pointed out that adults and children have different learning strategies, which is worth remembering. I was also pleased to hear his clear and emphatic distinction between leisure and workplace search needs. It’s a personal bugbear of mine that people don’t realise that looking for a hairdresser in central London – where any one of a number will do – is not the same as trying to find a specific shot of a particular celebrity shortly after that controversial haircut a couple of years ago from the interview they gave about it on a chat show.

Tom highlighted four key functions for taxonomies:

  • knowledge organisation systems (for asset management)
  • labelling systems (for asset management)
  • navigation systems (for retrieval and discovery)
  • search systems (for retrieval)

He pointed out that text analytics needs taxonomy to underpin it, to base contextualisation rules on. He also stressed the importance of data quality, as data quality problems cause the majority of search project failures. People often focus on cool new features and fail to pay attention to the underlying data structures they need to put in place for effective searching.

He noted that the volumes of data and metadata that need to processed are growing at a furious rate. He highlighted Comcast as a company that is very highly advanced in the search and data management arena, managing multiple streams of data that are constantly being updated, for an audience that expects instant and accurate information.

He stated that structure will remain the key to findability for the foreseeable future. Autonomy is often hailed as doing something different to other search engines because it uses statistical methods, but at heart it still relies on structure in the data.

Richard Padley made it through the snow despite a four-hour train journey from Brighton, and spoke at length about the importance of knowledge organisation to support search. He explained the differences between controlled vocabularies, indexes, taxonomies, and ontologies and how each performs a different function.

Marianne Lykke then talked about information architecture and persuasive design. She also referred to “basic categories” as well as the need to guide people to where you want them to go via simple and clear steps.

Taxonomies, Metadata, and Semantics in Action

I spoke in the final session of the day, on metadata life cycles, asset lifecycles, parametadata, and managing data flows in complex information “ecosystems” with different “pace layers”.

Neil Blue from Biowisdom gave a fascinating and detailed overview of Biowisdom’s use of semantic technologies, in particular ontology-driven concept extraction. Biowisdom handle huge complex databases of information to do with the biological sciences and pharmaceuticals, so face very domain-specific issues, such as how to bridge the gap between “hard” scientific descriptions and “soft” descriptions of symptoms and side-effects typically given by patients.

In the final presentation of the day, Alessandro Pica outlined the use of semantic technologies by Italian News agency AGI.

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libraries and museums | semantic web

Online Information Conference 2010

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Estimated reading time 3–4 minutes

Despite the recession, tube strikes, and snow, there was a fine collection of speakers, exhibitors, and delegates at a smaller than usual Online Information Conference and Exhibition this year.

Librarians seem to be getting heavily into Linked Data, while the corporate sector is still mainly concerned with business intelligence and search.

On day one I enjoyed the practical explanations of how Linked Data principles have been made to work at The Guardian, The Press Association, the Dutch Parliament, and the ALISS health project in Scotland.

Linked Data tags are a form of metadata that can be used to automatically generate content aggregations for web pages. This means that not only can you re-use your own content, increasing its lifespan, but you can gather cheap content that is openly available online. This is very familiar territory to me, as we used to build products in the same way back in the 90s, the difference being that we didn’t have much of an external web to link to back then. In the meantime, using a linkable, interoperbale format for your tags has very many benefits, and whether your focus is primarily for content within or beyond a firewall, the arguments for using standards that have the potential to link to the wider world seem very compelling. I can’t see any logical reasons not to standardise the format your metadata is held in (technical and practical issues are another matter), although standardising the semantic content of the metadata is a far more difficult problem.

It was reassuring to hear that everyone else is struggling with the problems of who mints IDs and URIs, who settles arguments about what exactly the IDs refer to – especially across domains – and who resolves and manages mappings. Such issues are difficult to resolve within a firewall, out there on the Web they become vast. The W3C is starting to work on provenance standards (the parametadata or meta-metadata), a pet worry of mine, because I am certain we need to get that layer of semantic information into our tags as soon as possible if we are going to be able to advance the semantic web beyond crunching databases together.

In the meantime, Linked Data is working very well especially for mashups and information visualisations. I particularly liked the Dutch Parliament’s “Attaquograms” – a diagram showing how often MPs were interrupted in debates and how much they interrupted others, although it doesn’t appear to have changed their behaviour yet. I also enjoyed The Guardian’s “league tables” of MPs’ performance. When MPs protested that such analyses ignored qualitative issues, The Guardian pointed out that if MPs advocate such data crunching as a way to judge schools and hospitals, then it must be good enough to apply to MPs themselves.

Andy Hyde from the ALISS project is working on ways to use Linked Data to help people manage their health, especially for patients with long term conditions such as diabetes. He stressed the importance of involving the users in any information project and addressing them on their terms, stating “The most collaborative tool we have is the cup of tea”.

My only concern about using Linked Data to pull in Wikipedia content, is whether the audience will start recognising it. If every website that mentions a topic has the same Wikipedia content attached to it, won’t people get bored? Perhaps there are just so many people out there contributing, so many varieties of alogrithmic aggregations, and so much content to read, it will never happen!

There is a related Guardian technology blog post.

I will post summaries of days two and three shortly.

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cataloguing | semantic web

Linking classification schemes via rdf

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< 1 minute

I was delighted to read an excellent blog post by Dan Brickley about the value of opening up classifications. It is lovely to read something like this from a technical expert who understands the power of innovation and new technology, but who also recognises the value of the information contained in classifications.

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semantic web

Financial sector ontologies

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Estimated reading time 1–2 minutes

I went to a Semantic Web meetup event on Tuesday where Mike Bennett of the EDM introduced an ontology for managing financial sector information that he has been developing.

It is always reassuring to discover that people working in completely different industries are facing the same challenges. Handling multiple viewpoints and the need to keep provenance of terminology well defined and clear was a key theme, as terms like “equities” can mean very different things in different contexts. Mike defined his own “archetypes” and used an “upper ontology” to act as an umbrella to connect other ontologies. I was particularly interested in the discussion of solutions for managing synonyms, one of which included a quite sophisticated use of RDF.

It was also interesting to hear Mike’s explanations of his use of taxonomies within the ontology and of the ingenious ways he finds to present his ideas to business people who don’t speak OWL!


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culture | Digital Asset Management | semantic web

Librarians rock! Metadata will take over the world

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Estimated reading time 3–4 minutes

The last presentation at the DAM conference back in June was by a very interesting DAM specialist – Mark Davey – of Cliffe Associates and Digital Asset Mangement.org.uk who spoke engagingly about the increasing pervasiveness of metadata and how it is opening up a whole new world of connections and possibilities.

Internet of Things

He talked about the emerging Internet of Things and how this will – essentially – be enabled by metadata. The more sophisticated our metadata management, the more use we will be able to make of links and connections. The semantic web is a bold attempt to link information resources, but if the semantic web and the Internet of Things can be linked, the web leaps out into the real world in unprecedented ways and this, according to Davey, is why librarians rock! It is the people who understand how metadata works who will be forging the links that will create an integrated Internet of Services. A smart fridge could send you text messages telling you what you need to buy when you are in the shops (although I worry about mine scolding me for eating too many cakes!), but there are many more business-focussed applications. For example, RFID tags are being used by Hollywood prop and costume hire companies to help them keep track of and retrieve stock. The location data is useful in that case to physically find missing items, but knowing where customers take their purchases may have all sorts of interesting implications for marketing. A car rental company could plot on a map where people have driven their cars. This would be a fun image in a brochure, but could support business decisions such as where to open branches or whether to provide more small cars for city trips or bigger cars for long distances.

The current Internet is not fit for purpose, because nobody agreed any standards, but if we can start developing standards, we can set digital assets and metadata free so that they can interact with each other in a machine-brokered way. This could be incredibly powerful – everything could end up everywhere! Ways to monetise this new world could involve micro payments – you are watching a video, you see a product you like, you click on it and behind the scenes your credit card or online account is charged and the product is shipped to your door. Meanwhile, the sales team know that you bought that product because it was in that particular scene in the film, they know where you live, and they know what else you have been buying.

Hive minds

This all seems rather scary. On the one hand, people are already referring to the distributed cognition aspects of social networking sites as the hive mind – we are, perhaps, creating some kind of Borg-like merging of identities into one big digital stew. Individuals could find themselves subsumed into a digitally imposed conformity to some overriding norm due to the panoptic, big brotherish combination of AI, RFID and CCTV, especially when you factor in neuromarketing and automated classification of behaviour (which will be subjects of future posts). On the other hand, people have always worried about the homogenising effects of anything that brings people together and the misuse of surveillance.

(I think in practice, metadata alone is just a tool that can be used for good or ill, like a knife. The Internet of Services is likely to be patchy, with some very worthy projects – applications in medicine where scarce resources like organs for transplants needed to be tracked and delivered and surgeons kept informed – and some just for fun – like the Tales of Things Project, where you can add memories, as metadata, to objects.)

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Digital Asset Management | semantic web

Content Identifiers for Digital Rights Persistence

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Estimated reading time 4–6 minutes

This is another write-up from the Henry Stewart DAM London conference.

Identity and identification

Robin Wilson discussed the issue of content identifiers, which are vitally important for digital rights management, but yet tend to be overlooked. He argued that although people become engaged in debates about titles and the language used in labels and classification systems, people overlook the need to achieve consensus on basic identification.

(I was quite surprised, as I have always thought that people would argue passionately about what something should be called and how using the wrong terminology affects usability, but that they would settle on machine-readable IDs quite happily. Perhaps it is the neutrality of such codes that makes the politics intractable. If you have invested huge amounts of money in a database that demands certain codes, you will argue that those codes are used by everyone else to save you the costs of translation or acquiring a compatible system, and there are no appeals to usability, or brokerage via editorial policy, that can be made. It simply becomes a matter of whoever shouts the loudest gets to spend the least money in the short term. )

Robin argued that the only way to create an efficient digital marketplace is to have a trusted authority oversee a system of digital identifiers that are tightly bound within the digital asset, so they cannot easily be stripped out even when an asset is divided, split, shared, and copied. The authority needs to be trusted by consumers and creators/publishers in terms of political neutrality, stability, etc.

(I could understand how this system would make it easier for people who are willing to pay for content to see what rights they need to buy and who they should pay, but I couldn’t see how the system could help content owners identify plagiarism without an active search mechanism. Presumably a digital watermark would persist throughout copies of an asset, provided that it wasn’t being deliberately stripped, but if the user simply decided not to pay, I don’t see how the system would help identify rights breaches. Robin mentioned in conversation Turnitin’s plagiarism management, which has become more lucrative than their original work on content analysis, but it requires an active process instigated by the content owner to search for unauthorised use of their content. This is fine for the major publishers of the world, who can afford to pay for such services, but is less appealing to individuals, whether professional freelances or amateur content creators, who would need a cheap and easy solution that would alert them to breaches of copyright without their having to spend time searching.)

The identifiers themselves need to be independent of any specific technology. At the moment, DAM systems are often proprietary and therefore identifiers and metadata cannot easily flow from one system to another. Some systems even strip away any metadata associated with a file on import and export.

Robin described five types of identifier currently being used or developed:

  • Uniform Resource Name (URN)
  • Handle System
  • Digital Object Identifier
  • Persistent URL (PURL)
  • ARK (Archival Resource Key).

He outlined three essential qualities for identifiers – that they be unique, globally registered, and locally resolved.

So why don’t we share?

Robin argued that it is easier for DAM vendors to build “safe” systems that lock all content within an enterprise environment, only those with a public service/archival remit tend to be collaborative and open. DAM vendors resist a federated approach online and prefer to use a one-to-one or directly intermediated transaction model. Federated identifier management services exist but vendors and customers don’t trust them. The problem is mainly social, not technological.

One of the problems is agreeing to share the costs of services, such as infrastructure, registration and validation, governance and development of the system, administration, and outreach and marketing.

(Efforts to standardise may well benefit the big players more than the small players and so there is a strong argument for them bearing the initial costs and offering support for smaller players to join. Once enough people opt in, the system gains critical mass and it becomes both easier to join and costs of joining become less of an unquantifiable risk – you can benefit from the experiences of others. The semantic web is currently attempting to acquire this “critical mass”. As marketers realise the potential of semantic web technology to make money, no doubt we will see an upsurge in interest. Facebook’s “like” button may well be heralding the advent of the ad-driven semantic web, which will probably drive uptake far faster than the worthy efforts of academics to improve the world by sharing research data!)

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semantic web

Are you a semantic romantic?

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Estimated reading time 8–12 minutes

The “semantic web” is an expression that has been used for long enough now that I for one feel I ought to know what it means, but it is hard to know where to start when so much about it is presented in “techspeak”. I am trying to understand it all in my own non-technical terms, so this post is aimed at “semantic wannabes” rather than “semantic aficionados”. It suggests some ways of starting to think about the semantic web and linked open data without worrying about the technicalities.

At a very basic level, the semantic web is something that information professionals have been doing for years. We know about using common formats so that information can be exchanged electronically, from SGML, HTML, and then XML. In the 90s, publishers used “field codes” to identify subject areas so that articles could be held in databases and re-used in multiple publications. In the library world, metadata standards like MARC and Dublin Core were devised to make it easier to share cataloguing data. The semantic web essentially just extends these principles.

So, why all the hype?

There is money to be made and lost on semantic web projects, and investors always want to try to predict the future so they can back winning horses. The recent Pew Report (thanks to Brendan for the link) shows the huge variety of opinions about what the semantic web will become.

On the one extreme, the semantic evangelists are hoping that we can create a highly sophisticated system that can make sense of our content by itself, with the familiar arguments that this will free humans from mundane tasks so that we can do more interesting things, be better informed and connected, and build a better and more intelligent world. They describe systems that “know” that when you book a holiday you need to get from your house to the airport, that you must remember to reschedule an appointment you made for that week, and that you need to send off your passport tomorrow to renew it in time. This is helpful and can seem spookily clever, but is no more mysterious than making sure my holiday booking system is connected to my diary. There are all sorts of commercial applications of such “convenience data management” and lots of ethical implications about privacy and data security too, but we have had these debates many times in the past.

A more business-focused example might be that a search engine will “realise” that when you search for “orange” you mean the mobile phone company, because it “knows” you are a market analyst working in telecoms. It will then work out that documents that contain the words “orange” and “fruit” are unlikely to be what you are after, and so won’t return them in search results. You will also be able to construct more complex questions, for example to query databases containing information on tantalum deposits and compare them with information about civil conflicts, to advise you on whether the price of mobile phone manufacture is likely to increase over the next five years.

Again, this sort of thing can sound almost magical, but is basically just compiling and comparing data from different data sets. This is familiar ground. The key difference is that for semantically tagged datasets much of the processing can be automated, so data crunching exercises that were simply too time-consuming to be worthwhile in the past become possible. The evangelists can make the semantic web project sound overwhelmingly revolutionary and utopian, especially when people start talking in sci-fi sounding phrases like “extended cognition” and “distributed intelligence”, but essentially this is the familiar territory of structuring content, adding metadata, and connecting databases. We have made the cost-benefit arguments for good quality metadata and efficient metadata management many times.

On the other extreme, the semantic web detractors claim that there is no point bothering with standardised metadata, because it is too difficult politically and practically to get people to co-operate and use common standards. In terms familiar to information professionals, you can’t get enough people to add enough good quality metadata to make the system work. Clay Shirky in “Ontology is overrated” argued that there is no point in trying to get commonalty up front, it is just too expensive (there are no “tag police” to tidy up), you just have to let people tag randomly and then try to work out what they meant afterwards. This is a great way of harvesting cheap metadata, but doesn’t help if you need to be sure that you are getting a sensible answer to a question. It only takes one person to have mistagged something, and your dataset is polluted and your complex query will generate false results. Shirky himself declares that he is talking about the web as a whole, which is fun to think about, but how many of us (apart from Google) are actually engaged in trying to sort out the entire web? Most of us just want to sort out our own little corner.

I expect the semantic web to follow all other standardisation projects. There will always be a huge “non-semantic” web that will contain vast quantities of potentially useful information that can’t be accessed by semantic web systems, but that is no different from the situation today where there are huge amounts of content that can’t be found by search engines (the “invisible web” or “dark web”) – from proprietary databases to personal collections in unusual formats. No system has been able to include everything. No archive contains every jotting scrawled on a serviette, no bookshop stocks every photocopied fanzine, no telephone directory lists every phone number in existence. However, they contain enough to be useful for most people most of the time. No standard provides a perfect universal lingua franca, but common languages increase the number of people you can talk to easily. The adoption of XML is not universal, but for everyone who has “opted in” there are commercial benefits. Not everybody uses pdf files, but for many people they have saved hours of time previously spent converting and re-styling documents.

So, should I join in?

What you really need to ask is not “What is the future of the semantic web?” but “Is it worth my while joining in right now?”. How to answer that question depends on your particular context and circumstances. It is much easier to try to think about a project, product, or set of services that is relevant to you than to worry about what everyone else is doing. If you can build a product quickly and cheaply using what is available now, it doesn’t really matter whether the semantic web succeeds in its current form or gets superseded by something else later.

I have made a start by asking myself very basic questions like:

  • What sort of content/data do we have?
  • How much is there?
  • What format is it in at the moment?
  • What proportion of that would we like to share (is it all public domain, do we have some that is commercially sensitive, but some that isn’t, are there data protection or rights restrictions)?

If you have a lot of data in well-structured and open formats (e.g. XML), there is a good chance it will be fairly straightforward to link your own data sets to each other, and link your data to external data. If there are commercial and legal reasons why the data can’t be made public, it may still be worth using semantic web principles, but you might be limited to working with a small data set of your own that you can keep within a “walled garden” – whether or not this is a good idea is another story for another post.

A more creative approach is to ask questions like:

  • What content/data services are we seeking to provide?
  • Who are our key customers/consumers/clients and what could we offer them that we don’t offer now?
  • What new products or services would they like to see?
  • What other sources of information do they access (users usually have good suggestions for connections that wouldn’t occur to us)?

Some more concrete questions would be ones like:

  • What information could be presented on a map?
  • How can marketing data be connected to web usage statistics?
  • Where could we usefully add legacy content to new webpages?

It is also worth investigating what others are already providing:

  • What content/data out there is accessible? (e.g. recently released UK government data)
  • Could any of it work with our content/data?
  • Whose data would it be really interesting to have access to?
  • Who are we already working with who might be willing to share data (even if we aren’t sure yet what sort of joint products/projects we could devise)?

It’s not as scary as it seems

Don’t be put off by talk about RDF, OWL, and SPARQL, how to construct an ontology, and whether or not you need a triple store. The first questions to ask are familiar ones like who you would like to work with, what could you create if you could get your hands on their content, and what new creations might arise if you let them share yours? Once you can see the semantic web in terms of specific projects that make sense for your organisation, you can call on the technical teams to work out the details. What I have found is that the technical teams are desperate to get their hands on high quality structured content – our content – and are more than happy to sort out the practicalities. As content creators and custodians, we are the ones that understand our content and how it works, so we are the ones who ought to be seizing the initiative and starting to be imaginative about what we can create if we link our data.

A bit of further reading:
Linked Data.org
Linked Data is Blooming: Why You Should Care
What can Data.gov.uk do for me?

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