archive.Joe Lamantia.com

The Lessons From Failure Series (curated by Christian Crumlish) kicked off today at Boxes and Arrows, leading with my meditation on being an entrepreneur and what it means to face failure as a member of a rigidly defined society, titled It Seemed Like The Thing To Do At The Time. Stay tuned for three further installments from talented fellow panelists.

Also, look for part two of my series on designing healthy user experiences for portals using the IA Building Blocks in early July. Part one – The Challenge of Dashboards and Portals – describing the structural and usability weaknesses of flat architectures, was published in December.

Many thanks to the hard working volunteers at B+A for creating a forum for these ideas and the community around them!

For regular readers wondering about the recent quiet here, a notice that Boxes and Arrows will shortly publish an article I’ve been working on for a while in the background, titled, “It Seemed Like the Thing To Do At the Time: The Power of State of Mind”. This is the written version of my panel presentation Lessons From Failure: Or How IAs Learn to Stop Worrying and Love the Bombs from the 2007 IA Summit in Las Vegas.

I’ve written about organizations and failure – Signs of Crisis and Decline In Organizations – in this blog before (a while ago, but still a popular posting), and wanted to consider the subject on a larger level. With the rapid spread of social software / social media and the rise of complex social dynamics in on-line environments, exploring failure at the level of an entire society is timely.

In The Fishbowl

Failed or failing societies are an excellent fishbowl for observers seeking patterns related to social media, for two reasons. First, the high intensity of failure situations reveals much of what is ordinarily hidden in social structures and patterns: Impending collapse leads people to dispense with carefully maintained social constructions.

One source of this heightened intensity is the greatly increased stakes of societal failure (vs. most other kinds), which often means sudden and dramatic disruptions to basic living and economic patterns, the decline of cities and urban concentrations, and dramatic population decrease. Another source is the very broad scope of the aftereffects; because a failing society involves an entire culture, the affects are comprehensive, touching everyone and everything.

Secondly, societies often command substantial qualitative and quantitative resources that can help them manage crisis or challenges, thereby averting failure. Smaller, less sophisticated entities lack the resource base of a complex social organism, and consequently cannot put up as much of a fight.

Examples of resources available at the level of a society include:

• Leaders and planners dedicated to focusing on the future
• Large amounts of accumulated knowledge and experience
• Sophisticated structures for decision making and control
• Mechanisms for maintaining order during crises
• Collective resilience from surviving previous challenges
• Substantial stores of resources such as food and materials, money, land
• Tools, methods, and organizations providing economies of scale, such as banking and commerce networks
• Systems for mobilizing labor for special purposes
• Connections to other societies that could provide assistance (or potential rescue)

Despite these mitigating resources, the historical and archeological records overflow with examples of failed societies. Once we read those records, the question of how these societies defined themselves seems to bear directly on quite a few of the outcomes.

I discuss three societies in the article: Easter Island, Tikopia, and my own small startup company. We have insight into the fate of Easter Island society thanks to a rich archeological record that has been extensively studied, and descriptions of the Rapa Nui society in written records kept by European explorers visiting since 1722. Tikopia of course is still a functioning culture. My startup was a tiny affair that serves as a useful foil because it shows all the mistakes societies make in a compressed span of time, and on a scale that’s easy to examine. The Norse colonies in North America and Greenland are another good example, though space constraints didn’t allow discussion of their failed society in the article.

Read the article to see what happens to all three!

Semi Random Assortment of Quotations

In the meantime, enjoy this sampling of quotations about failure, knowledge, and self, from some well-known – and mostly successful! – people.

“Technological change is like an axe in the hands of a pathological criminal.” – ALBERT EINSTEIN

“It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change.” – CHARLES DARWIN

“It is impossible for a man to learn what he thinks he already knows.” – EPICTETUS

“I have not failed. I’ve just found 10,000 ways that won’t work.” – THOMAS EDISON

“It is on our failures that we base a new and different and better success.” – HAVELOCK ELLIS

“Life is a process of becoming, a combination of states we have to go through. Where people fail is that they wish to elect a state and remain in it.” – ANAIS NIN

“We read the world wrong and say that it deceives us.” – RABINDRANATH TAGORE

“Whoever longs to rescue quickly both himself and others should practice the supreme mystery: exchange of self and other.” – SHANTIDEVA

“Failure is instructive. The person who really thinks learns quite as much from his failures as from his successes.” – JOHN DEWEY

The Pew Internet & American Life Project just released a report on tagging that finds 28% of internet users have tagged or categorized content online such as photos, news stories or blog posts. On a typical day online, 7% of internet users say they tag or categorize online content.

The authors note “This is the first time the Project has asked about tagging, so it is not clear exactly how fast the trend is growing.”
Wow – I’d say it’s growing extremely quickly. Though I am on record as a believer in the bright future of tag clouds, I admit I’m surprised by these results. The fact that 7% of internet users tag daily is what’s most significant: it’s an indication of very rapid adoption for the practice of tagging in many different contexts and many different kinds of audiences, given it’s brief history.

I’d guess this adoption rate compares to the rates of adoption for other new network-dependent or emergent architectures like P2P music sharing or on-line music buying.

You’re correct if you’re thinking there is a difference between tagging and tag clouds. And if you’ve read the report and the accompanying interview with Dr. Weinberger, you’ve likely realized that neither Dr. Weinberger’s interview nor the report specifically addresses tag cloud usage. But remember the First Principle of Tag Clouds: “Where there’s tags, there’s a tag cloud.” By definition, any item with an associated collection of tags has a tag cloud, regardless of whether that tag cloud is directly visible and actionable in the user experience. So that 7% of internet users who tag daily are by default creating and working with tag clouds daily.

It might be time for tag clouds to look into getting some sunglasses.

Col­lab­o­ra­tion is the lat­est ral­ly­ing cry of soft­ware ven­dors hop­ing to embed new gen­er­a­tions of enter­prise class tools and user expe­ri­ences into the fab­ric of the mod­ern work­place. Microsoft, IBM, and other firms expect that con­trol or lead­er­ship in the mar­ket for col­lab­o­ra­tion, whether by own­ing the archi­tec­ture, sys­tems, or other solu­tion com­po­nents, will be lucra­tive. A recent Rad­i­cati Group study (qual­ity uncon­firmed…) of the mar­ket size for enter­prise col­lab­o­ra­tion offered an esti­mate of $1.6 bil­lion now, grow­ing 10% annu­ally to $2.3 bil­lion in 2010.

Beyond the sub­stan­tial money to be made cre­at­ing, sell­ing, installing, and ser­vic­ing col­lab­o­ra­tion solu­tions lies the strate­gic advan­tage of mar­ket def­i­n­i­tion. The vendor(s) that own(s) the col­lab­o­ra­tion space expect(s) to become an inte­gral to the knowl­edge economy’s sup­port­ing envi­ron­ment in the same way that Ford and Gen­eral Motors became essen­tial to the sub­ur­ban­ized con­sumer archi­tec­tures of the post WWII era by serv­ing simul­ta­ne­ously as employ­ers, man­u­fac­tur­ers, cul­tural mar­keters, cap­i­tal reser­voirs, and auto­mo­bile sell­ers. Col­lab­o­ra­tion ven­dors know that achiev­ing any level of indis­pen­si­bil­ity will enhance their longevity by mak­ing them a neces­sity within the knowl­edge econ­omy.

It’s worth tak­ing a moment to call atten­tion to the impli­ca­tions: by defin­ing the user expe­ri­ences and tech­no­log­i­cal build­ing blocks brought together to real­ize col­lab­o­ra­tion in large enter­prises, these ven­dors will directly shape our basic con­cepts and under­stand­ing (our men­tal mod­els and cog­ni­tive frames) of col­lab­o­ra­tion. Once embed­ded, these archi­tec­tures, sys­tems, and busi­ness processes, and the social struc­tures and con­cep­tual mod­els cre­ated in response, will in large part define the (infor­ma­tion) work­ing envi­ron­ments of the future.And yes, this is exactly what these ven­dors aspire to achieve; the Microsoft Share­point Prod­ucts and Tech­nolo­gies Devel­op­ment Team blog, offers:

“Share­Point Prod­ucts and Tech­nolo­gies have become a key part of our strat­egy for deliv­er­ing a com­plete work­ing envi­ron­ment for infor­ma­tion work­ers, where they can col­lab­o­rate together, share infor­ma­tion with oth­ers, and find infor­ma­tion and peo­ple that can help them solve their busi­ness prob­lems.“
[From SHAREPOINT’S ROLE IN MICROSOFT’S COLLABORATION STRATEGY.]

And IBM’s mar­ket­ing is not pitched and deliv­ered in a man­ner as sweep­ing, but the impli­ca­tions are sim­i­lar, as in the overview IBM® Work­place™: Sim­ply a bet­ter way]:
“IBM Work­place™ Solu­tions are role-based frame­works to help cus­tomers apply IBM Work­place tech­nolo­gies faster and more pro­duc­tively… These solu­tions are designed to pro­vide ‘short-cuts’ for cre­at­ing a high per­for­mance role-based work envi­ron­ment, help­ing to accel­er­ate time-to-value.“

The Mod­els for com­mu­ni­ca­tion and rela­tion­ships built into our tools are very pow­er­ful, and often employed in other spheres of life. How many times have you started writ­ing a birth­day card for a friend, and found your­self instinc­tively com­pos­ing a set of bul­let points list­ing this person’s chief virtues, notable char­ac­ter traits, and the most impor­tant / amus­ing moments of your friend­ship. The creep­ing ubiq­uity of the rhetor­i­cal style of Pow­er­point (Tufte’s essay here) is just one exam­ple of the tremen­dous social impact of a habit­u­ated model of com­mu­nica­tive prac­tices that’s run amok.

What does the future hold, in terms of enter­prise ven­dor con­trol over every­day work­ing expe­ri­ences? I’ve writ­ten before on the idea that the days of the mono­lithic enter­prise sys­tems are num­bered, mak­ing the point along the way that these behe­moths are the result of a top-down, one-size-for-all approach. I think the same is true of the cur­rent approach to col­lab­o­ra­tion solu­tions and work­ing envi­ron­ments. And so I was happy to see Andrew McAfee of Har­vard Busi­ness School make sev­eral strong points about how enter­prise col­lab­o­ra­tion efforts will real­ize greater suc­cess by *reduc­ing* the amount of struc­ture imposed on their major ele­ments — roles, work­flows, arti­facts, and rela­tion­ships — in advance of actual use.

McAfee sees con­sid­er­able ben­e­fit in new approaches to enter­prise IT invest­ment and man­age­ment that reduce the top-down and imposed nature of enter­prise envi­ron­ments and solu­tions, in favor of emer­gent struc­tures cre­ated by the peo­ple who must work suc­cess­fully within them. McAfee advo­cates allow­ing staff to cre­ate the iden­ti­ties, struc­tures and pat­terns that will orga­nize and gov­ern their col­lab­o­ra­tion envi­ron­ments as nec­es­sary, in an emer­gent fash­ion, instead of fix­ing these aspects long before users begin to col­lab­o­rate.

McAfee says:
“When I look at a lot of cor­po­rate col­lab­o­ra­tion tech­nolo­gies after spend­ing time at Wikipedia, del.icio.us, Flickr, and Blog­ger I am struck by how reg­i­mented, inflex­i­ble, and lim­ited the cor­po­rate stuff seems, because it does some or all of the following:

• Gives users iden­ti­ties before they start using the tech­nol­ogy. These iden­ti­ties assign them cer­tain roles, priv­i­leges, and access rights, and exclude them from oth­ers. These iden­ti­ties almost always also place them within the exist­ing orga­ni­za­tional struc­ture and for­mal cor­po­rate hierarchy.
• Con­tains few truly blank pages. Instead, it has lots of templates–for meet­ings, for project track­ing, for doc­u­ments and reports, etc.
• Has tons of explicit or implicit work­flow– seqences [sic] of tasks that must be exe­cuted in order.

How much of this struc­ture is nec­es­sary? How much is valu­able? Well, the clear suc­cess sto­ries of Web 2.0 demon­strate that for at least some types of com­mu­nity and col­lab­o­ra­tion, none of it is.“

The crit­i­cal ques­tion is then “what types of com­mu­nity and col­lab­o­ra­tion require which approaches to cre­at­ing struc­ture, and when?” As any­one who’s used a poorly or overly struc­tured col­lab­o­ra­tion (or other enter­prise) tool knows, the result­ing envi­ron­ment is often anal­o­gous to a feu­dal soci­ety designed and man­aged by crypto-technical over­lords; one in which most users feel as if they are serfs bound to the land for in per­pe­tu­ity in order to sup­port the leisure-time and war-making indul­gences of a small class of share­hold­ing nobil­ity.

Answer­ing these ques­tions with con­fi­dence based on expe­ri­ence will likely take time in the range of years, and require numer­ous failed exper­i­ments. There’s a larger con­text to take into account: the strug­gle of enter­prise soft­ware ven­dors to extend their reach and longevity by dom­i­nat­ing the lan­guage of col­lab­o­ra­tion and the range of offer­ings is one part of a much broader effort by soci­ety to under­stand dra­matic shifts in our ways of work­ing, and the social struc­tures that are both dri­ven by and shape these new ways of work­ing. And so there are sev­eral impor­tant ideas and ques­tions under­ly­ing McAfee’s assess­ment that social sys­tem design­ers should under­stand.

One of the most impor­tant is that the notion of “col­lab­o­ra­tion” is con­cep­tual short­hand for how you work, who you work with, and what you do. In other words, it’s a dis­til­la­tion of your pro­fes­sional iden­tity. Your role in a col­lab­o­ra­tion envi­ron­ment defines who you are within that envi­ron­ment.

More impor­tantly, from the per­spec­tive of growth and devel­op­ment, your sys­tem assigned role deter­mines who you can *become*. Knowl­edge work­ers are val­ued for their skills, expe­ri­ence, pro­fes­sional net­works, pub­lic rep­u­ta­tions, and many other fluid, con­text depen­dent attrib­utes. And so lock­ing down their iden­ti­ties in advance strips them of a sub­stan­tial pro­por­tion of their cur­rent value, and simul­ta­ne­ously reduces their abil­ity to adapt, inno­vate, and respond to envi­ron­men­tal changes by shift­ing their think­ing or prac­tices. In plain terms, deter­min­ing their iden­ti­ties in advance pre­cludes the cre­ation of future value.

Another impor­tant under­ly­ing idea is the impor­tance of prop­erly under­stand­ing the value and util­ity of dif­fer­ing approaches to sys­tem­ati­za­tion in dif­fer­ing con­texts. McAfee’s assess­ment of the unhealthy con­se­quences of impos­ing too much struc­ture in advance is use­ful for social sys­tem design­ers (such as infor­ma­tion archi­tects and knowl­edge man­agers), because it makes the out­comes of implicit design strate­gies and assump­tions clear and tan­gi­ble, in terms of the neg­a­tive effects on the even­tual users of the col­lab­o­ra­tion envi­ron­ment. For com­plex and evolv­ing group set­tings like the mod­ern enter­prise, cre­at­ing too much struc­ture in advance points to a mis­placed under­stand­ing of the value and role of design and archi­tec­ture.

Fun­da­men­tally, it indi­cates an over­es­ti­ma­tion of the value of the activ­ity of sys­tem­atiz­ing (design­ing) col­lab­o­ra­tion envi­ron­ments to high lev­els of detail, and with­out recog­ni­tion for evo­lu­tion­ary dynam­ics. The design or struc­ture of any col­lab­o­ra­tion envi­ron­ment — of any social sys­tem — is only valu­able for how well it encour­ages rela­tion­ships and activ­ity which advance the goals of the orga­ni­za­tion and it’s mem­bers. The value of a designer in the effort to cre­ate a col­lab­o­ra­tive com­mu­nity lies in the abil­ity to cre­ate designs that lead to effec­tive col­lab­o­ra­tion, not in the num­ber or speci­ficity of the designs they pro­duce, and espe­cially not in the arti­facts cre­ated dur­ing design — the tem­plates, work­flows, roles, and other McAfee men­tioned above. To sim­plify the dif­fer­ent views of what’s appro­pri­ate into two arti­fi­cially seg­mented camps, the [older] view that results in the pre­ma­ture cre­ation of too much struc­ture val­i­dates the design of things / arti­facts / sta­tic assem­blies, whereas the newer view valu­ing min­i­mal and emer­gent struc­tures acknowl­edges the greater effi­cacy of design­ing dynamic sys­tems / flows / frame­works.

The overly spe­cific and rigid design of many col­lab­o­ra­tion sys­tem com­po­nents com­ing from the older design view­point in fact says much about how large, com­plex enter­prises choose to inter­pret their own char­ac­ters, and cre­ate tools accord­ingly. Too often, a desire to achieve total­ity lies at the heart of this approach.

Of course, most total­i­ties only make sense — exhibit coher­ence — when viewed from within, and when using the lan­guage and con­cepts of the total­ity itself. The result is that attempts to achieve total­ity of design for many com­plex con­texts (like col­lab­o­ra­tion within enter­prises large or small) rep­re­sent a self-defeating approach. That the approach is self-defeating is gen­er­ally ignored, because the pur­suit of total­ity is a self-serving exer­cise in power val­i­da­tion, that ben­e­fits power hold­ers by con­sum­ing resources poten­tially used for other pur­poses, for exam­ple, to under­mine their power.

With the chimera of total­ity set in proper con­text, it’s pos­si­ble to see how col­lab­o­ra­tion envi­ron­ments — at least in their most poorly con­ceived man­i­fes­ta­tions — will resem­ble vir­tual retreads of Tay­lorism, wherein the real accom­plish­ment is to jus­tify the effort and expense involved in cre­at­ing the sys­tem by point­ing at an exces­sive quan­tity of pre­de­ter­mined struc­ture await­ing habi­ta­tion and use by dis­en­fran­chised staff.

At present, I see two diver­gent and com­pet­ing trends in the realm of enter­prise solu­tions and user expe­ri­ences. The first trend is toward homo­gene­ity of the work­ing envi­ron­ment with large amounts of struc­ture imposed in advance, exem­pli­fied by com­pre­hen­sive col­lab­o­ra­tion suites and archi­tec­tures such as MSOf­fice / Share­point, or IBM’s Work­place.

The sec­ond trend is toward het­ero­gene­ity in the struc­tures inform­ing the work­ing envi­ron­ment, vis­i­ble as vari­able pat­terns and locuses of col­lab­o­ra­tion estab­lished by fluid groups that rely on adhoc assort­ment of tools from dif­fer­ent sources (Base­Camp, GMail, social book­mark­ing ser­vices, RSS syn­di­ca­tion of social media struc­tures, com­mu­ni­ties of prac­tice, busi­ness ser­vices from ASP providers, open source appli­ca­tions, etc.).

But this itself is a short term view, when sit­u­a­tion within a longer term con­text is nec­es­sary. It is com­mon for sys­tems or envi­ron­ments of all sizes and com­plex­i­ties to oscil­late cycli­cally from greater to lesser degrees of struc­ture, along a con­tin­uüm rang­ing from homo­ge­neous to het­ero­ge­neous. In the short term view then, the quest for total­ity equates to homo­gene­ity, or even efforts at dom­i­na­tion. In the long term view, how­ever, the quest for total­ity could indi­cate an imma­ture ecosys­tem that is not diverse, but may become so in time.

Apply­ing two (poten­tial) lessons from ecol­ogy — the value of diver­sity as an enhancer of over­all resilience in sys­tems, and the ten­dency of mono­cul­tures to exhibit high fragility — to McAfee’s points on emer­gence, as well as the con­tin­uüm view of shift­ing degress of homo­gene­ity, should tell us that col­lab­o­ra­tion solu­tion design­ers would be wise to do three things:

The end result should be an enter­prise approach to col­lab­o­ra­tion that empha­sizes the design of infra­struc­ture for com­mu­ni­ties that cre­ate their own struc­tures. Big ven­dors be wary of this enlight­ened point of view, unless you’re will­ing to respond in kind.

A few months ago I came across a presentation titled Organizations in Crisis and Decline, by Randall Dunham. After giving examples of organizations in crisis and decline that include Kmart, General Motors, United Airlines, and Michael Jackson. (interesting example of an enterprise…), Dunham goes on to summarize typical symptoms of crisis, the strategic consequences of decline, and 10 behaviors of unhealthy organizations.

I came across this while doing some research on how the structures and cultures of organizations influence modes of thinking, resilience, and decision making, so this is related to some of my postings on enterprise software. It might be a while before I have the chance to write up all the ideas, so I’ll share Dunham’s material now.

Why is this of note to IAs? Quite a few Information architects (practitioners, not just those with the title…) are actively looking for effective tools and modes of understanding to help frame and manage enterprise problems.

Understanding the signs of decline and crisis in organizations can help information architects and other change agents understand the environmental context of a situation in the critical early stages of setting expectations and roles, and before it’s “too late”, when everyone at the management table has strong opinions they must defend. In other words, before making a leap is into an active project, a planning and budgeting cycle, a strategic vision session, etc.

I see (at least) two very important aspects of a situation that Dunham’s warning signs could help identify; how healthy an organization is, and what latitude for activity and change is available. Building on this, these criteria can help identify situations to avoid or be wary of. Of course, organizations in crisis and decline can present opportunities as well as risks, but sometimes the ship is going down no matter how much you try to patch the holes…

For those without powerpoint, I’m going to present some of the material here as text, with acknowledgment that I’m borrowing directly from Dunham, who himself credits this source: Mische, M.A. (2001). Ten warning signs of strategic Decline. In Strategic Renewal: Becoming a High-Performance Organization (pp. 25-30). Upper Saddle River, NJ: Prentice Hall.
Typical Symptoms of Crisis/Decline

• Lower earnings & revenues
• Increased employee turnover
• Reduced market presence
• Decrease in customer satisfaction & interest
• Increasing costs & high structural costs

Strategic Consequences of Crisis/Decline

• Lower market value
• Inconsistent strategies
• Misalignment of internal strategies & external goals
• Diminished capacity to attract top talent
• Increased vulnerability

10 Behaviors that Signal Decline

• The organization exhibits a lack of understanding the environmental and economic realities confronting it, or is in denial
• The management of the organization is arrogant with regard to its view of the world & assessment of its internal competencies. Ex: Icarus Paradox
• The organization has lost perspective with respect to customers, products, suppliers, and competitors
• Management and employees have an insular focus or preoccupation with internal processes, internal measurements, and politics
• The organization has lost its sense of urgency and lacks an attitude of self-determination
• The organization is relying on historical and poorly conceptualized or inappropriate business strategies and traditional management methods to address new & different challenges
• The organization has the propensity to repeat mistakes and fails to learn from past experiences
• The organization has low or slow innovation practices and is late to market with new products/services
• The organization has a tendency to recycle marginally performing managers
• The organization relies exclusively on internal talent as a source of leadership

Key Factors that Contribute to Decline

• Age of the organization: Older, more established firms may rely on legacy practices
• Size of the organization: Large firms with many vertical levels can have trouble adapting
• Financial success and past performance: Past success can lead to desire to follow same path in hopes of future success
• Ownership and equity structure: Is there accountability at all times to outside agents?
• Environmental influences: External shocks
• Ability to learn and discern patterns: Lack of learning organization culture
• Certainty/uncertainty: Effectiveness of change management
• Leadership: Young & inexperienced without desire to learn

Success Can Drive Crisis

• The same processes that lead to success in an organization can also lead to failure
• This is because success promotes rigidity, resistance to change, and habitual response
• Biggest problem – people learn the ‘right’ way to solve a problem and do that over and over again, even if that way will no longer solve the problem

It’s true these are quite general. Naturally, the art is in knowing how to apply them as criteria, or interperet what you found. As a quick test of accuracy, I’ve used the behaviors and warning signs to retrospectively review several of the organizations I’ve seen from the inside. When those organizations showed several of the behaviors and warning signs at an aggregate level (not necessarily my group, but the whole enterprise) then the strategic consequence dunham mentioned were visible at the same time.

From a practical perspective, a rating scale or some indicators of relative degree would be very useful. In order to gauge whether to stay or go, you need to understand the intensity of the decline or crisis and what action you can take: for example, do you have time to go back to the cabin to save your handwritten screenplay before the ship sinks?

Though you may not have noticed it at first (I didn’t – they’re located a few steps off the front page), the recently launched design of NYTimes.com includes tag clouds. After a quick review, I think their version is a good example of a cloud that offers some increased capabilities and contextual information that together fall in line with the likely directions of tag cloud evolution we’ve considered before.

Specifically, the New York Times tag cloud:

NYtimes.com Tag Cloud

The NYTimes.com tag cloud shows the most popular search terms used by readers within three time frames: the last 24 hours, the last 7 days, and the last 30 days. Choosing search terms as the makeup for a cloud is a bit curious – but it may be as close to socially generated metadata as seemed reasonable for a first exploration (one that doesn’t require a substantial change in the business or publishing model).

Given the way that clouds lend themselves to showing multiple dimensions of meaning, such as change over time, I think the Times tag cloud would be more valuable if it offered the option to see all three time frames at once. I put together a quick cut and paste of a concept screen that shows this sort of layout:

Screen Concept: 3 Clouds for Different Time Frames

In an example of the rapid morphing of memes and definitions to fit shifting usage contexts (as in Thomas Vanderwal’s observations on the shifting usage of folksonomy) the NYTimes.com kept the label tag cloud, while this is more properly a weighted list: the tags shown are in fact search terms, and not labels applied to a focus of some kind by taggers.

It’s plain from the limited presence and visibility of clouds within the overall site that the staff at NYTimes.com are still exploring the value of tag clouds for their specific needs (which I think is a mature approach), otherwise I imagine the new design concept and navigation model would utilize and emphasized tag clouds to a greater degree. So far, the Times uses tag clouds only in the new “Most Popular” section, and they are offered as an alternative to the default list style presentation of popular search terms. This position within the site structure places them a few steps in, and off the standard front page-to-an-article user flow that must be one of the core scenarios supported by the site’s information architecture.

NYTimes.com User Flow to Tag Cloud

Still, I do think it’s a clear sign of increasing awareness of the potential strength of tag clouds as a way of visualizing semantic information. The Times is an established entity (occasionally serving as the definition of ‘the establishment’), and so is less likely to endanger established relationships with customers by changing its core product across any of the many channels used for delivery.

Questions of risk aside, tag clouds (here I mean any visualization of semantic metadata) couLd be a very effective way to scan the headlines for a sense of what’s happening at the moment, and the shifting importance of topics in relation to on another. With a tag cloud highlighting “immigration”, “duke”, and “judas”, visitors can immediately begin to understand what is newsworthy – at least in the minds of NYTimes.com readers.

At first glance, lowering the amount of time spent reading the news could seem like a strong business disincentive for using tag clouds to streamline navigation and user flow. With more consideration, I think it points to a new potential application of tag clouds to enhance comprehension and findability by giving busy customers powerful tools to increase the speed and quality of their judgments about what to devote their attention to in order to acheive understanding greater depth. In the case of publications like the NYTimes.com, tag clouds may be well suited for conveying snapshots or summaries of complex and deep domains that change quickly (what’s the news?), and offering rapid navigation to specific areas or topics.

A new user experience that offers a variety of tag clouds in more places might allow different kinds of movement or flow through the larger environment, enabling new behaviors and supporting differing goals than the current information architecture and user experience.

Possible Screen Flow Incorporating Clouds

Stepping back from the specifics of the design, a broader question is “Why tag clouds now?” They’re certainly timely, but that’s not a business model. This is just speculation, but I recall job postings for an Information Architect position within the NYTimes.com group on that appeared on several recruiting websites a few months ago – maybe the new team members wanted or were directed to include tag clouds in this design? If any of those involved are allowed to share insights, I’d very much like to hear the thoughts of the IAs / designers / product managers or other team members responsible for including tag clouds in the new design and structure.

And in light of Mathew Patterson’s comments here about customer acceptance of multiple clouds in other settings and contexts (priceline europe), I’m curious about any usability testing or other user research that might have been done around the new design, and any the findings related to tag clouds.

I believe the value of second generation clouds will be to offer ready navigation and access to deep, complex landscapes of meaning built up from the cumulative semantic information contained in many interconnected tag clouds. I’d like share some thoughts on this idea; I’ll split the discussion into two posts, because there’s a fair amount of material.

In a previous post on tag clouds, I suggested that the great value of first generation tag clouds is their ability to make concepts and metadata – semantic fields – broadly accessible and easy to understand and work with through visualization. I believe the shift in the balance of roles and value from first to second generation reflects natural growth in cloud usage and awareness, and builds on the two major trends of tag cloud evolution: enhanced visualization and functionality for working with clouds, and provision of extensive contextual information to accompany tag clouds.

Together, these two growth paths allow cloud consumers to follow the individual chains of understanding that intersect at connected clouds, and better achieve their goals within the information environment and outside. Fundamentally, I believe the key distinctions between first and second generation clouds will come from the way that clouds function simultaneously as visualizations and navigation mechanisms, and what they allow navigation of – landscapes of meaning that are rich in semantic content of high value.

For examples of both directions of tag cloud evolution coming together to support navigation of semantic landscapes, we can look at some of the new features del.icio.us has released in the past few months. I’ve collected three versions of the information architecture of the standard del.icio.us URL details page from the past seven months as an example of evolution happening right now.

The first version (screenshot and breakdown in Figure 1) shows the URL details page sometime before August 15th, 2005, when it appeared on Matt McAlister’s blog.

Figure 1: Del.icio.us URL Page – August 2005

The layout or information architecture is fairly simple, offering a list of the common tags for the url / focus, a summary of the posting history, and a more detailed listing of the posting history that lists the dates and taggers who bookmarked the item, as well as the tags used for bookmarking. There’s no cloud style visualization of the tags attached to this single focus available: at this time, del.icio.us offered a rendered tag cloud visualization at the aggregate level for the whole environment.

Environment and system designers know very well that as the scope and complexity of an environment increase – in this case, the number of taggers, focuses, and tags, plus their cumulative histories – it becomes more important for people to be explicitly aware of the context of any item in order to understand it properly. Explicit context becomes more important because they can rely less and less on implicit context or assumptions about context based on the universal aspects of the environment. This is how cloud consumers’ needs for clearly visible and accessible chains of understanding drives the features and capabilities of tag clouds. Later versions of this page addresses these needs in differing ways, with differing levels of success.

Figure 2 shows a more recent version of the del.licio.us history for the Ma.gnolia.com service. This screenshot taken about ten days ago in early March, while I was working on a draft of this post.

Figure 2: Del.icio.us URL Page – Early March 2006

Key changes from the first version in August to this second version include:

The most important change in this second version is the removal of the individual sets of tags from the Posting History. Separating the tags applied to the focus from associaton with the individual taggers that chose them strips them of an important layer of context. Removing the necessary context for the tag cloud breaks the chain of understanding (Figure 3) linking taggers and cloud consumers, and obscures or increases the costs of the social conceptual exchange that is the basic value of del.icio.us to its many users. In this version, cloud consumers consumers reading the URL details page can only find specific taggers based on the concepts they’ve matched with this focus by visiting or navigating to each individual taggers’ area within the larger del.icio.us environment one at a time.

Figure 3: Chain of Understanding

The switch to rendering the Common Tags block as a tag cloud is also important, as an indicator of the consistent spread of clouds to visualize semantic fields, and their growing role as navigation tools within the larger landscape.

The User Notes are a good example of an attempt to provide additional contextual information with (potentially) high value. User Notes are created by users exclusively for the purpose of providing context. The other forms of context shown in the new layout – the Posting History, Related Items – serve a contextual function, but are not created directly by users with this goal in mind. The difference between the two purposes for these items undoubtedly influences the way that people create them, and what they create: it’s a question that more detailed investigations of tagging practices will surely examine.

The third version of the same URL history page, shown in Figure 4, was released very shortly after the second, proving tag cloud evolution is happening so quickly as to be difficult to track deliberately on a broad scale.

Figure 4: Del.icio.us URL Page – March 2006 #2

This version changes the content and layout of the Posting History block, restoring the combined display of individual taggers who tagged the URL, with the tags they applied to it, in the order in which they tagged the URL for the first time.
The third version makes two marked improvements over the first and second versions:

These three different versions of the del.icio.us URL details page show that the amount and type of contextual information accompanying a single focus is increasing, and that the number of concrete navigable connections to the larger semantic landscape of which the focus is one element also increasing

Overall, it’s clear that clouds are quickly emerging as navigation tools for complex landscapes of meaning, and that cloud context has and will continue to become more important for cloud creation and use.

And so before discussing the context necesary for clouds and the role of clouds as navigation aids in more detail, it will be helpful to get an overview of landscapes of meaning, and how they arise.

Landscapes of Meaning
A landscape of meaning is a densely interconnected, highly valuable, extensive information environment rich in semantic content that is created by communities of taggers who build connected tag clouds. In the early landscapes of meaning emerging now, a connection between clouds can be a common tag, tagger, or focus: any one of the three legs of the Tagging Triangle required for a tag cloud (more on this below). Because tag clouds visualize semantic fields, connected tag clouds visualize and offer access to connected semantic fields, serving as bridges between the individual accumulations of meaning each cloud contains.

Connecting hundreds of thousands of individually created clouds and fields, as del.icio.us has enabled social bookmarkers to do by providing necessary tools and infrastructure, creates a very large information environment whose terrain or geography is composed of semantic information. Such a semantic landscape is a landscape constructed or made up of meaning. It is an information environment that allows people to share concepts or for social purposes of all kinds, while supported with visualization, contextual information, functionality, and far-ranging navigation capabilities.

The flickr Landscape
flickr is a good example of a landscape of meaning that we can understand as a semantic landscape. In a previous post on tag clouds, I considered the flickr all time most popular tags cloud (shown in Figure 5) in light of the basic structure of clouds:

“The flickr style tag cloud is …a visualization of many tag separate clouds aggregated together. …the flickr tag cloud is the visualization of the cumulative semantic field accreted around many different focuses, by many people. …the flickr tag cloud functions as a visualization of a semantic landscape built up from all associated concepts chosen from the combined perspectives of many separate taggers.”

Figure 5: The flickr All Time Most Popular Tags Cloud

From our earlier look at the structure of first generation tag clouds we know a tag cloud visualizes a semantic field made up of concepts referred to by labels which are applied as tags to a focus of some sort by taggers.
Based on our understanding of the structure of a tag cloud as having a single focus, the flickr cloud shows something different because it includes many focuses. The flickr all time most popular tags cloud combines all the individual tag clouds around all the individual photos in flickr into a single visualization, as Figure 6 shows.

Figure 6: The flickr Landscape of Meaning

This means the flickr all time most popular tags cloud is in fact a visualization of the combined semantic fields behind each of those individual clouds. It’s quite a bit bigger in scope than a traditional single focus cloud. Because the scope is so large, the amount of meaning it summarizes and conveys is tremendous. The all time most popular tags cloud is in fact a historic window on the current and historical state of the semantic landscape of flickr as a whole.

This is where context becomes critical to the proper understanding of a tag cloud. The cloud title “All time most popular tags” sets the context for this tag cloud, within the boundaries of the larger landscape environment defined and communicated by flickr’s user epxerience. Without this title, the cloud is meaningless despite the large and complex semantic landscape – all of the information environment of flickr – it visualizes so effectively, because cloud consumers cannot retrace a complete chain of understanding to correctly identify the cloud’s origin.

flickr – 1st Generation Landscape Navigation
The flickr cloud is a powerful navigation mechanism for quickly and easily moving about within the landscape of meaning built up by all those thousands and thousands of individual clouds. Still, because it is a first generation cloud, we cannot directly follow any of the many individual chains of understanding connecting this cloud’s tags back to specific taggers, or the concepts they associate with specific photos or focuses. In this visualization, the group’s understanding of meaning is more important than any individual’s understanding. And so the flickr cloud does not yet allow us comprehensive navigation of the underlying semantic landscape illustrated in Figure 6 (chains of understanding suggested in light green). The flickr cloud also remains a first generation tag cloud because users cannot control its context.

Figure 7: A Semantic Landscape

Even so, these navigational and contextual needs will help identify the way that users rely on clouds to work in landscapes of meaning.

Growth of Landscapes
Landscapes of meaning like flickr, del.icio.us, or the burgeoning number of social semantic business ventures debuting as I write – typically grow from the bottom up, emerging as dozens or thousands of individual tag clouds created for different reasons by different taggers coincidentally or deliberately interconnect and overlap, all of this happening through a variety of social mechanisms. Taggers typically create connected or overlapping tag clouds one at a time, adding tags, focuses, and taggers (by creating new accounts) in the ad hoc fashion of open networks and architectures. But first we should look at the Tagging Triangle to understand the most basic elements of a tag cloud.

The Tagging Triangle
To make a tag cloud, you have to have three elements: a focus, a tagger, and a(t least one) tag. I call this the Tagging Triangle, illustrated in Figure 8. In the most common renderings of familiar tag clouds, one or two of these elements are often implied but not shown: yet all three are always present.

This illustration shows a cloud of labels, not tags, because a rendered cloud is really a list of labels. The labels shown in most first generation clouds are often tags, but structurally they could also be a set of names for taggers, as in the del.icio.us posting history block proto-cloud we saw above, or a set of focuses as in the ‘Inverted Cloud’ I suggested.
Figure 8: The Tagging Triangle

An Example Landscape
A simple example of the growth of semantic landscapes leads naturally to the discussion of specific ways that tag clouds will enable navigation within large landscapes of meaning.

Figure 9 shows the tag cloud accreted around a single focus. This cloud includes some of the tags that Tagger 1 has used in total across all the tag clouds she’s created (those other clouds aren’t shown). We’ll assume that she’s created other clouds for other focuses.

Figure 9: A Single Tag Cloud

When a second person, Tagger 2, tags that same focus (again with a subset of the total set of all his tags), and some of those tags are the same as those used for this focus by Tagger 1, their individual tag clouds for this focus (shown by the dashed line in the cumulative tag cloud) connect via the common tags, and the cumulative cloud grows. If any of the tags from their total sets are the same, but are not used for this focus, they form another connection between the two taggers. Figure 10 shows two individual clouds connected in both these ways.

Figure 10: Two Connected Clouds

When a third tagger adds a third cloud with common tags and unique tags around the same focus, the cumulative cloud grows, and the number of both kinds of connections between tags and taggers grows. Figure 11 shows three connected clouds.

Figure 11: Connected Clouds

Every tag cloud visualizes a semantic field, and so the result of this bottom up growth is a series of interlinked semantic fields centered around a common focus, as Figure 12 shows. Since semantic fields are made of concepts, linked fields result in linked concepts.

Figure 12: Connected Semantic Fields

The total number and the variety of kinds of interconnections amongst these three taggers, their tags, and a single focus is remarkable. As this simple example shows, the total number and density of connections linking even a moderate size population of taggers, tags, and focuses could quickly become very large. This increased scale drives qualitative and quantitative topology changes in the network that permit a landscape of meaning to emerge from connected semantic fields.

Landscapes And Depth
The accumulation of connections and concepts creates a landscape of meaning with real depth; but it’s the depth of a landscape that drives its value. For this discussion, I’m defining depth loosely as the amount of semantic information or the density of the semantic field either across the whole landscape, or at a chosen point.

Value of course is a very subjective judgement. In participatory economies like that of del.icio.us, the value to individual users is predominantly one of loosely structured semantic exchange based on accumulation of collective value through shared individual efforts. From a business viewpoint, a group of investors and yahoo as a buyer saw considerable value in the emergent landscape and / or other kinds of assets

To make the idea of depth a bit clearer, Figure 13 illustrates two views of a semantic landscape built up by the overlap of tag clouds. The aerial view shows the contents, distribution, and overlap of a number of tag clouds around a set of focuses. The horizon view shows the depth of the semantic field for each focus, based on the amount of overlap or connection between the cloud around that focus and all the other clouds.

Figure 13: Semantic Landscape Depth Views

Of course this is only a conceptual way of showing the cumulative semantic information that makes up a landscape of meaning, so it does not address the relative value of this information. Plainly some indication of the quality of the semantic information in a landscape is critical important to measurements of both depth and value. Metrics for quality could come from a combination of assessment of the diversity and granularity of the tag population for the focus, benchmarks for the domain of the focus and taggers (healthcare industry), and an estimate on the maturity of the domain, the focus, and the tag clouds in the semantic landscape.
Looking ahead, it’s likely that accepted metrics for defining and describing the depth, value, and characteristics of semantic fields and landscapes will emerge as new combinations of some of the measurements used now in the realms of cognitive linguistics, set theory, system theory, topology, information theory, and quite a few other disciplines besides.

In Part Two
The second post in this series of two will follow several of the topics introduced here to conclusion, as well as cover some new topics, including:

• How chains of understanding shape needs for cloud context and navigation paths
• How the tagging triangle will define navigation within landscapes of meaning
• The emergence of stratification in landscapes of meaning
• The idea that clouds and landscapes have a shape which conveys meaning and value
• The kinds of contextual information and controls necessary for navigation and social exchanges

Watching Navigation Follow Chains of Understanding
I’ll close with a screencast put together by Jon Udell that captures a wide ranging navigation path through the del.icio.us landscape.

Lets build on the analysis of tag clouds from Tag Clouds Evolve: Understanding Tag Clouds, and look ahead at what the near future may hold for second generation tag clouds (perhaps over the next 12 to 18 months). As you read these predictions for structural and usage changes, keep two conclusions from the previous post in mind: first, adequate context is critical to sustaining the chain of understanding necessary for successful tag clouds; second, one of the most valuable aspects of tag clouds is as visualizations of semantic fields.

Based on this understanding, expect to see two broad trends second in generation tag clouds.
In the first instance, tag clouds will continue to become recognizable and comprehensible to a greater share of users as they move down the novelty curve from nouveau to known. In step with this growing awareness and familiarity, tag cloud usage will become:
1. More frequent
2. More common
3. More specialized
4. More sophisticated

In the second instance, tag cloud structures and interactions will become more complex. Expect to see:
1. More support for cloud consumers to meet their needs for context
2. Refined presentation of the semantic fields underlying clouds
3. Attached controls or features and functionality that allow cloud consumers to directly change the context, content, and presentation of clouds

Together, these broad trends mean we can expect to see a second generation of numerous and diverse tag clouds valued for content and capability over form. Second generation clouds will be easier to understand (when designed correctly…) and open to manipulation by users via increased functionality. In this way, clouds will visualize semantic fields for a greater range of situations and needs, across a greater range of specificity, in a greater diversity of information environments, for a greater number of more varied cloud consumers.

Usage Trends
To date, tag clouds have been applied to just a few kinds of focuses (links, photos, albums, blog posts are the more recognizable). In the future, expect to see specialized tag cloud implementations emerge for a tremendous variety of semantic fields and focuses: celebrities, cars, properties or homes for sale, hotels and travel destinations, products, sports teams, media of all types, political campaigns, financial markets, brands, etc.

From a business viewpoint, these tag cloud implementations will aim to advance business ventures exploring the potential value of aggregating and exposing semantic fields for a variety of strategic purposes:
1. Creating new markets
2. Understanding or changing existing markets
3. Providing value-added services
4. Establishing communities of interest / need / activity
5. Aiding oversight and regulatory imperatives for transparency and accountability.

Measurement and Insight
I think tag clouds will continue to develop as an important potential measurement and assessment vehicle for a wide variety of purposes; cloudalicious is a good example of an early use of tag clouds for insight. Other applications could include using tag clouds to present metadata in geospatial or spatiosemantic settings that combine GPS / GIS and RDF concept / knowledge structures.
Within the realm of user experience, expect to see new user research and customer insight techniques emerge that employ tag clouds as visualizations and instantiations of semantic fields. Maybe even cloud sorting?

Clouds As Navigation
Turning from the strategic to the tactical realm of experience design and information architecture, I expect tag clouds to play a growing role in the navigation of information environments as they become more common. Navigational applications comprise one of the first areas of tag cloud application. Though navigation represents a fairly narrow usage of tag clouds, in light of their considerable potential in reifying semantic fields to render them actionable, I expect navigational settings will continue to serve as a primary experimental and evolutionary venue for learning how clouds can enhance larger goals for information environments such as enhanced findability.

For new information environments, the rules for tag clouds as navigation components are largely unwritten. But many information environments already have mature navigation systems. In these settings, tag clouds will be one new type of navigation mechanism that information architects and user experience designers integrate with existing navigation mechanisms. David Fiorito’s and Richard Dalton’s presentation Creating a Consistent Enterprise Web Navigation Solution is a good framework / introduction for questions about how tag clouds might integrate into mature or existing navigation systems. Within their matrix of structural, associative and utility navigation modes that are invoked at varying levels of proximity to content, tag clouds have obvious strengths in the associative mode, at all levels of proximity to content, and potential strength in the structural mode. Figure 1 shows two tag clouds playing associative roles in a simple hypothetical navigation system.

Figure 1: Associative Clouds

I also expect navigation systems will feature multiple instances of different types of tag clouds. Navigation systems employing multiple clouds will use combinations of clouds from varying contexts (as flickr and technorati already do) or domains within a larger information environment to support a wide variety of purposes, including implicit and explicit comparison, or views of the environment at multiple levels of granularity or resolution (high level / low level). Figure 2 illustrates multiple clouds, Figure 3 shows clouds used to compare the semantic fields of a one focus chosen from a list, and Figure 4 shows a hierarchical layout of navigational tag clouds.

Figure 2: Multiple Clouds

Figure 3: Cloud Comparison Layout

Figure 4: Primary / Secondary Layout

Structural and Behavioral Trends
Let’s move on to consider structural and behavioral trends in the second generation of tag clouds.
Given the success of the simple yet flexible structure of first generation tag clouds, I expect that second generation clouds will not substantially change their basic structure. For example, tag clouds will not have to change to make use of changing tagging practices that enhance the semantic depth and quality of tags applied to a focus, such as faceted tagging, use of qualifiers, hierarchical tagging, and other forms. James Melzer identifies some best practices on del.icio.us that make considerable sense when the focus of a semantic field is a link. His recommendations include:

• Source your information with via:source_name or cite:source_name
• Create a parent categories, and thus a rudimentary hierarchy, with parent_tag/subject_tag
• Mention publications names with in:publication_name
• Flag the type of resource with .extension or =resource_type
• Use a combination of general and specific tags on every bookmark to provide both clustering and differentiation
• Use synonyms or alternate forms of tags
• Use unique or distinctive terms from documents as tags (don’t just use major subject terms)

The two element structure of first generation tag clouds can accommodate these tagging practices. However, with a semantic field of greater depth and richness available, the interactions, behaviors, and presentation of tag clouds will evolve beyond a static set of hyperlinks.

Cloud consumers’ need for better context will drive the addition of features and functionality that identify the context of a tag cloud explicitly and in detail. For example, clouds created by a defined audience will identify that audience, whether it be system administrators, freelance web designers, DJ’s, or pastry chefs rating recipes and cooking equipment and provide indication of the scope and time periods that bound the set of tags presented in the cloud. Flickr and others do this already, offering clouds of tags covering different intervals of time to account for the changing popularity of tags over their lifespan.

Moving from passive to interactive, tag clouds will allow users to change the cloud’s semantic focus or context with controls, filters, or other parameters (did someone say ‘sliders’ – or is that too 5 minutes ago…?). I’ve seen several public requests for these sorts of features, like this one: “It would be great if I could set preferences for items such as time frame or for tags that are relevant to a particular area etc or even colour the most recent tags a fiery red or remove the most recent tags.” Figure 5 shows a tag cloud with context controls attached.

Figure 5: Context Controls

Figure 6: Behavior Controls

Diversifying consumer needs and goals for way finding, orientation, information retrieval, task support, product promotion, etc., will bring about inverted tag clouds. Inverted tag clouds will center on a tag and depict all focuses carrying that tag.

Figure 7: Inverted Clouds Show Conceptually Related Focuses

In the vein of continued experiment, tag clouds will take increased advantage with RIA / AJAX and other user experience construction methods. Following this, tag clouds may take on some of the functions of known navigation elements, appearing as sub-menus / drop down menus offering secondary navigation choices.

Figure 8: Clouds As Drop Menus

Along the same lines, tag clouds will demonstrate more complex interactions, such as spawning other tag clouds that act like magnifying lenses. These overlapping tag clouds may offer: multiple levels of granularity (a general view and zoom view) of a semantic field; thesaurus style views of related concepts; parameter driven term expansion; common types of relationship (other people bought, by the same author, synonyms, previously known as, etc.)

Figure 9: Magnifying Clouds

Genres
Looking at the intersection of usage and behavior trends, I expect tag clouds will evolve, differentiate, and develop into standard genres. Genres will consist of a stable combination of tag cloud content, context, usage, functionality, and behavior within different environments. The same business and user goals that support genres in other media and modes of visualization will drive the development of these tag cloud genres. One genre I expect to see emerge shortly is the search result.

Conclusions
Reading over the list, I see this is an aggressive set of predictions. It’s fair to ask if I really have such high expectations for tag clouds? I can’t say tag clouds will take over the world, or even the Internet. But I do believe that they fill a gap in our collective visualization toolset. The quantity, quality, and relevance of semantic information in both real and virtual environments is constantly increasing. (In fact, the rate of increase is itself increasing, though that is a temporary phenomenon.) I think tag clouds offer a potential to quickly and easily support the chain of understanding that’s necessary for semantic fields across diverse kinds of focuses. There’s need for that in many quarters, and I expect that need to continue to grow.

For the moment, it seems obvious that tag clouds will spend a while in an early experimental phase, and then move into an awkward adolescent phase, as features, applications and genres stabilize in line with growing awareness and comfort with clouds in various settings.

I expect these predictions to be tested by experiments will play out quickly and in semi or fully public settings, as in the example of the dialog surrounding 83 degrees usage of a tag cloud as the sole navigation mechanism on their site that Rashmi Sinha’s post The tag-cloud replaces the basic menu – Is this a good idea? kicked off recently.

My answer to this question is that replacing all navigation menus with a tag cloud is only a good idea under very limited circumstances. It’s possible that 83 Degrees may be one of these limited instances. Startups can benefit considerably from any positive attention from the Web’s early adopter community (witness Don’t Blow Your Beta by Michael Arrington of Techcrunch).

The page’s designer said, “In this case it was done as a design/marketing effort and not at all for UI”. Since attracting attention was the specific purpose, I think the result is a success. But it’s still an experimental usage, and that’s consistent with the early stage of evolution / development of tag clouds in general.

I’m looking forward to what happens next…

Zeldman jokingly called tag clouds “the new mullets” last year. At the time, I think he was taken a bit by surprise by the rapid spread of the tag cloud (as many people were). A big year later, it looks like this version of the world’s favorite double duty haircut will stay in fashion for a while. Zeldman was discussing the first generation of tag clouds. I have some ideas on what the second generation of tag clouds may look like that will conclude this series of two essays. These two pieces combine ideas brewing since the tagging breakout began in earnest this time last year, with some predictions based on recent examples of tag clouds in practice.

Update: Part two of this essay, Second Generation Tag Clouds, is available.

This first post lays groundwork for predictions about the second generation of tag clouds by looking at what’s behind a tag cloud. I’ll look at first generation tag clouds in terms of their reliance on a “chain of understanding” that semantically links groups of people tagging and consuming tags, and thus underlies tagging and social metadata efforts in general. I’ll begin with structure of first generation tag clouds, and move quickly to the very important way that tag clouds serve as visualizations of semantic fields.

Anatomy of a Tag Cloud
Let’s begin with the familiar first generation tag cloud. Tag clouds (here we’re talking about the user experience, and not the programmatic aspects) commonly consist of two elements: a collection of linked tags shown in varying fonts and colors to indicate frequency of use or importance, and a title to indicate the context of the collection of tags. Flickr’s tags page is the iconic example of the first generation tag cloud. Screen shots of several other well known tag cloud implementations show this pattern holding steady in first generation tagging implementations such as del.icio.us and technorati, and in newer efforts such as last.fm and ma.gnolia.
Wikipedia’s entry for tag cloud is quite similar, reading, “A tag cloud (more traditionally known as a weighted list in the field of visual design) is a visual depiction of content tags used on a website. Often, more frequently used tags are depicted in a larger font or otherwise emphasized, while the displayed order is generally alphabetical… Selecting a single tag within a tag cloud will generally lead to a collection of items that are associated with that tag.”

In terms of information elements and structure, first generation tag clouds are low complexity. Figure 1 shows a schematic view of a first generation tag cloud. Figures 2 through 5 are screenshots of well-known first generation tag clouds.

Figure 1: Tag Cloud Structure

Figure 2: last.fm

Figure 3: technorati

Figure 4: del.icio.us

Figure 5: Ma.gnolia

Tag Clouds: Visualizations of Semantic Fields
The simple structure of first generation tag clouds allows them to perform a very valuable function without undue complexity. That function is to visualize semantic fields or landscapes that are themselves part of a chain of understanding linking taggers and tag consumers. This is a good moment to describe the “chain of understanding”. The “chain of understanding” is an approach I use to help identify and understand all the different kinds of people and meaning, and the transformations and steps involved in passing that meaning on, that must work and connect properly in order for something to happen, or an end state to occur. The chain of understanding is my own variation / combination of common cognitive and information flow mapping using a scenario style format. I’ve found the term resonates well with clients and other audiences outside the realm of IA.

How does the chain of understanding relate to tag clouds? The tags in tag clouds originate directly from the perspective and understanding of the people tagging, but undergo changes while becoming a tag cloud. (For related reading, see Rashmi Sinha’s A social analysis of tagging which examines some of the social mechanisms underlying the activity of tagging.) Tag clouds accrete over time when one person or a group of people associate a set of terms with a focus of some sort; a photo on flickr, a URL / link in the case of del.icio.us, an album or song for last.fm. As this list shows, a focus can be anything that can carry meaning or understanding. The terms or tags serve as carriers and references for the concepts each tagger associates with the focus. Concepts can include ideas of aboutness, origin, or purpose, descriptive labels, etc. While the concepts may change, the focus remains stable.

What’s key is that the tag is a reference and connection to the concept the tagger had in mind. This connection requires an initial understanding of the focus itself (perhaps incorrect, but still some sort of understanding), and the concepts that the tagger may or may not choose to associate with the focus. And this is the first step in the chain of understanding behind tag clouds, as shown in Figure 6.

Figure 6: Origin: Focus and Concepts

As a result, tag clouds are more than collection of descriptive or administrative terms attached to a link, or other sort of focus. The tag is a sort of label that references a concept or set of concepts. A cloud of tags is then a collection of labels referring to a cluster of aggregated concepts. The combination of tags that refer to concepts, with the original focus, creates a ‘semantic field’. A semantic field is the set of concepts connected to a focus, but in a form that is now independent of the originating taggers, and available to other people for understanding. In this sense, a semantic field serves as a form of reified understanding that the taggers themselves – as well as others outside the group that created the semantic field – can now understand, act on, etc. (This speaks to the idea that information architecture is a discipline strongly aimed at reification, but that’s a different discussion…). Figure 7 shows this second step in the chain of understanding; without it, there is no semantic field, and no tag cloud can form. And now because this post is written from the viewpoint of practical implications for tag cloud evolution, I’m going to hold the definition and discussion of a semantic field and focus, before I wander off track into semiotics, linguistics, or other territories. The most important thing to understand is that *tag clouds comprise visualizations of a semantic field*, as we’ve seen from the chain of understanding.
Figure 7: Semantic Field

I believe tag clouds are revolutionary in their ability to translate the concepts associated with nearly anything you can think of into a collectively visible and actionable information environment, an environment that carries considerable evidence of the original understandings that precede and inform it. In a practical information architecture sense, tag clouds can make metadata – one of the more difficult and abstract of the fundamental concepts of the digital universe for the proverbial person on the street – visible in an easily understood fashion. The genius of tag clouds is to make semantic concepts, the frames of understanding behind those concepts, and their manifestation as applied metadata tangible for many, many people.

Figure 8: Semantic Field As Tag Cloud

With this notion of a tag cloud as a visualization of a semantic field in mind, let’s look again at an example of a tag cloud in practice. The flickr style tag cloud (what I call a first generation tag cloud) is in fact a visualization of many tag separate clouds aggregated together. Semantically then, the flickr tag cloud is the visualization of the cumulative semantic field accreted around many different focuses, by many people. In this usage, the flickr tag cloud functions as a visualization of a semantic landscape built up from all associated concepts chosen from the combined perspectives of many separate taggers.

To summarize, creating a tag cloud requires completion of the first three steps of the chain of understanding that supports social metadata. Those steps are:
1. Understanding a focus and the concepts that could apply that focus
2. Accumulating and capturing a semantic field around the focus
3. Visualizing the semantic field as a tag cloud via transformation
The fourth step in this chain involves users’ attempts to understand the tag cloud. For this we must introduce the idea of context, which addresses the question of which original perspectives underlie the semantic field visualized in a tag cloud, and how those concepts have changed before or during presentation.

How Cloud Consumers Understand Tag Clouds
Users need to put a given tag cloud in proper context in order to understand the cloud effectively. Their end may goals may be finding related items, surveying the thinking within a knowledge domain, identifying and contacting collaborators, or some other purpose, but it’s essential for them to understand the tags in the cloud to achieve those goals. Thus whenever a user encounters a tag cloud, they ask and answer a series of questions intended to establish the cloud’s context and further their understanding. Context related questions often include “Where did these tags come from? Who applied them? Why did they choose these tags, and not others? What time span does this tag cloud cover?” Context in this case means knowing enough about the conditions and environment from which the cloud was created, and the decisions made about what tags to present and how to present them. Figure 9 summarizes the idea of context.

Figure 9: Cloud Context

Once the user or consumer places the tag cloud in context, the chain of understanding is complete, and they can being to use or work with the tag cloud. Figure 10 shows the complete chain of understanding we’ve examined.
Figure 10 Chain of Understanding

In part two, titled “Second Generation Tag Clouds”, I’ll share some thoughts on likely ways that the second generation of tag clouds will evolve in structure and usage in the near future, based on how they support a chain of understanding that semantically links taggers and tag cloud consumers. Context is the key for tag cloud consumers, and we’ll see how it affects the likely evolution of the tag cloud as a visualization tool.

Update: Part two Second Generation Tag Clouds is available

Using the automotive industry and an analogous variety of software mega-packages with three-letter acronyms as examples, we’ve been discussing the death of the traditional enterprise for a few weeks. We’ve observed that enterprise efforts relying on massive top-down approaches become inefficient and wasteful, if not counter-productive. They also either fail to support the health of the individuals or groups involved – customers, users, sellers, employers – or in fact directly reduce the relative health of these parties. With Conway’s Law as a guide, we discovered that the structure or form of an organization influences or determines the nature and quality of the things the organization creates.
This all concerns the past: so now it’s time to look ahead, at the new enterprise. Of course, scrying the future inevitably relies on a mixture of hand waving, vague pronouncements, and the occasional “it’s not possible yet to do what this implies” to point the way forward. What’s often lacking is a present-tense example to serve as clear harbinger of the future to come. I came across an example today, drawn from the debate surrounding the proposition that the U.S. Army is close to a breaking point. In an episode of On Point titled Are US Forces Stretched Too Thin?, several panelists (names not available from the program website yet) made three telling points about the Army that show it as an organization in transition from the old model enterprise into a new form, albeit one whose outlines remain fuzzy. I’ll paraphrase these points:

To support this practice, company commanders created a forum for sharing innovations amongst themselves, called CO Team: CompanyCommand. The description reads, “CompanyCommand.com is company commanders-present, future, and past. We are in an ongoing professional conversation about leading soldiers and building combat-ready units. The conversation is taking place on front porches, around HMMWV hoods, in CPs, mess halls, and FOBs around the world. By engaging in this ongoing conversation centered around leading soldiers, we are becoming more effective leaders, and we are growing units that are more effective. Amazing things happen when committed leaders in a profession connect, share what they are learning, and spur each other on to become better and better.”
It’s the third point that gives us a clue about the nature of the new enterprise. CompanyCommand.com is an example of a ‘knowledge marketplace’ created and maintained by an informal network within an organization. Knowledge marketplaces are one of the components of what McKinsey calls The 21st Century Organization. Knowledge marketplaces allow knowledge buyers “to gain access to content that is more insightful and relevant, as well as easier to find and assimilate, than alternative sources are.”
McKinsey believes that these markets – as well as companion forms for exchanging valuable human assets called talent markets – require careful investment to begin functioning.
“…working markets need objects of value for trading, to say nothing of prices, exchange mechanisms, and competition among suppliers. In addition, standards, protocols, regulations, and market facilitators often help markets to work better. These conditions don’t exist naturally – a knowledge marketplace is an artificial, managed one – so companies must put them in place.”
On this, I disagree. CompanyCommand is an example of a proto-form knowledge marketplace that appears to be self-organized and regulated.
Moving on, another component of the new enterprise identifed by McKinsey is the formal network. A formal network “…enables people who share common interests to collaborate with relatively little ambiguity about decision-making authority – ambiguity that generates internal organizational complications and tension in matrixed structures.”
In McKinsey’s analysis, formal networks contrast with informal social networks in several ways. Formal networks require designated owners responsible for building common capabilities and determining investment levels, incentives for membership, defined boundaries or territories, established standards and protocols, and shared infrastructure or technology platforms.
My guess is that CompanyCommand again meets all these formal network criteria to a partial extent, which is why it is a good harbinger of the forms common to the new enterprise, and a sign of an organization in transition.
Can you think of other examples of new enterprise forms, or organizations in transition?
In the next post in this series, we’ll move on from the structure of the new enterprise to talk about the new enterprise experience, trying to track a number of trends to understand their implications for the user experience of the new enterprise environment.

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