Reflections on Tagging Part II.

My first reaction to tagging was surprise, followed shortly by a dose of joy.

 Although I am a longtime user of the Internet, IRC, IM, and many other communication tools on the Net, I was surprised not only that tagging could be such a powerful tool, but also that to a great extent I had been unaware of this.

For me, tagging solves two problems: firstly that my favourites can be stored externally and thus not dependant on a specific machine – changing machines or losing a hard-drive always seems to go with a loss of links to valued information. There are pictures, articles, and downloads that I no longer have, because I simply cannot remember how I found them. Even worse, I can’t even remember what they were.

Secondly, it solves a classification problem.

I sometimes struggle to decide under what category to save a new link, and this results either in a steadily growing taxonomy that becomes increasingly arcane and impenetrable with time, or to inconsistencies of where I put things.
Does something go under “Research” or “UC” or “KM”, and why did I have this folder called “NS”?

Storing multiple copies of links was a thought, but quite often Intranet links change, and it would become an administrative overhead to root out all the occurrences of a link each time.

Tagging potentially solves this because it is no longer bound to a canonical format on a specific machine, but rather takes on the nature of a relational database index, where a classification can be created dynamically by user-constructed query strings.

Unfortunately, the ability for sites like to handle Boolean search terms is at present very limited, and although sites like Connotea[1] allow a more structured search mechanism, they also do not yet allow a structured query language that is entirely user constructed.

At present I can use search with Boolean terms to logically AND tags and NOT tags, but I cannot deliberately exclude by period, language, origin, or person for example. To escape the overwhelming abundance and proliferation of the “soup”, I may for instance, need to exclude postings from a specific poster who I have identified to be prolific but untrustworthy. While this poster may have matched tags that I wish to include, I may still desire to exclude anything they have tagged, and to do this I need a meta-language that would look very much like a structured query language.

There seems to be some development along these lines with structured query languages such as “Squeal” (Spertus, 2007), WebSQL (Arocena, 2007), and Xcerpt (Furche, 2004).

However although they all have elements of it, none of those are specifically targeted at tag searching.

It cannot be long before a structured search language specifically encompassing tags  and meta-tags becomes available, and this would turn the “tag soup” into an instantly structured information subset – Of course that creates the dilemma of how and where one saves the search term itself for future use or reference.

Curiously, one of the very reasons that the “invisible” or “deep” web is opaque is because many large databases of information create classifications on the fly through user-constructed query strings of the kind I am suggesting. One hopes that tag searches would be open in a way that more is revealed, rather than driving everything into islands of information that are mostly hidden.

What I also found fascinating was that social media are curiously attractive, enjoyable, and emotionally “warm” in a way that traditional databases like EBSCO, EMERALD, and LEXUS/NEXUS are socially “cold”.  This “attractiveness” is seemingly unrelated to the level of actual knowledge acquisition or information quantity retrieved.

For example, the human-computing experiment called “ESP Game”[2] has already labeled over 10,000,000 images on the web by getting humans to work collaboratively without any tangible reward. The payoff for the individuals is somewhat in the act of participation in something socially useful – the identification of images in order to make them searchable, but is mainly in the simple pleasure that people get from playing with other people. The sensation of having an anonymous “partner” who is “in tune”, is strangely attractive, if not somewhat addictive.

The parallel between using other people’s discoveries as part of one’s own online heuristic, and normal human or even primate behaviour is to me, very striking.

All primate species appear to be highly motivated to, and to derive pleasure from, learning from others and leaving clues for others to find. In this way, social bookmarking appears to engage with some very ancient and well developed behaviour patterns, and thus fit snugly into the ergonomic requirements we have for information.

Perhaps it reveals a search for mutuality – people who like what I like, are interested in what interests me and are themselves therefore interesting to me.[i]

Rebecca Blood remarked that tagging led her to some surprising self-discovery, by looking post facto at what she had tagged, she came to realise that there were things that she was evidently interested in that she would not have previously said were her top interests. In some sense then, we are what we tag, or at least what we tag demonstrates actual interests as opposed to stated interests, and this self-revelation may be quite emancipatory, or at least informative.

On the negative side, there may be some serious privacy concerns. In a very real sense, you are what you seek – as was evidenced by the release of AOL search terms which enabled quick discovery of individual persons, even though their identities were anonymised.[3]

I am also not sure if it might actually amplify my biases by giving me an ability to screen out discordant information or see only agreeable information.

After having experimented with tagging, I am doubtful that canonical taxonomical systems will be replaced since these represent in effect a sort of hypothesis test in a truly scientific sense. We can pose what we think may be true, and by cementing this in a canonical classification, we open our claim to natural selection – will nature and reality prove it to be true or false, will it stand or fall. In these falsifiable claims – and a canonical taxonomy is indeed a truth claim in which we are able to put our beliefs to the test.


  1. “Squeal” (Spertus 2007) a structured query language for the web


  1. WebSQL (Arocena 2007)


  1. Xcerpt (Furche 2004) “declarative, rule-based query and transformation language for the Web”


[1] Connotea is located at and is published free of charge by the journal Nature.


[3] The release of AOL search strings allowed a researcher to quickly identify a Mrs.Thelma Arnold, even though she was identified only as “searcher #4417749”

[i] User of the participative labeling game at report a sense of please in finding a compatible partner that in itself serves as a reward.


Matthew Loxton is the director of Knowledge Management & Change Management at Mincom, and blogs on Knowledge Management. Matthew’s LinkedIn profile is on the web, and has an aggregation website at
Opinions are the author’s and not necessarily shared by Mincom, but they should be.


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