Personal InfoCloud

Personal

The first step or home base, is more of a state for beginning, is the the personal space and repository. Sadly, this is the ugly step child that is very often missed in many tools/service offerings. The place were a person has a view of their resources, which is mapped in their context and needed representations to make sense with the least effort. This is the view with things they need to see surface (from their perspective and from others) and from where they jump to interacting with information, objects, tasks, and others.

Sparks (Ideas Shared)

The first step often comes from asking questions simply and easily and quick easy responses, or sharing quick notes and ideas that get feedback and interest. Many times this is done efficiently in micro sharing services like similar to Twitter but with a grasp of needs organizations have (Socialtext Signals or Socialcast are solid options to consider). But, other options, including blogs and discussion forums have the capability of doing this as well.

With sparks of ideas they need to have the ability to be found so to be responded to, aggregated, or even shared to ensure the right people see them and can interact. There is a wide breadth of types of things that flow through micro sharing services, but many will resonate, inform, or inspire others. But, quite often they get solid conversations flowing across a broad cross section of people and locations.

Campfire (Gathering of Others with Interest)

From the spark of inspiration many others with interest or affinity gather to discuss and the spark turns into a campfire. Stories are told and fuel is added to the fire. Honing of the ideas and gather inspiration, information, and content from broad sources and view is then curated and honed to some degree.

The tools needed for the campfire stage must allow from much broader conversation than the limited spark stage. Limiting the room around the campfire to those with strong interest and affinity helps keep the focus, but also these people will likely have the deepest reserves of fodder for the conversation and a wide variety of perspectives and resources they can tap ready at hand. Longer conversation and curating all that is gathers are the prime focus. Curation through tagging is often incredibly helpful (being able to tag so to aggregate and curate ideas from the sparks stage is highly important).

Bonfire (Broader Interest Gathering)

Once the ideas have been fleshed out and framed to some degree and curated to control scope the discussion turns into a bonfire. Bonfires, while much larger still need to be controlled and maintained or they get out of control and things get dangerous. At this stage broad viewing for healthy feedback and discussion, including highlighting things that have been missed, what works well, what doesn't work well, etc. are the key focus. This is the time to get understanding and direction that hones and shapes everything that is possible. It is also used to add to what has been gathered and curated in the campfire stage so to iterate on it.

Torch (Honing for Broad Use & Replication)

Lastly, is the torch stage. This is easy to handle, easy to replicate, and is safe. This requires Real Collaboration to work through the conflicting ideas and negotiate as well as intelligently work toward one final output. These final outputs can be white papers, new processes, new guidelines, new products, etc. But, the point is there is one (just like artists collaborating on a statue there is only one statue, not many and all through differences have been worked through to one salient solution).

We Can't Find Anything

There is nothing more common that I hear from an organization about their intranet and internal information services than, "We can't find anything." (Some days I swear this is the mantra that must be intoned for an organization to become real.)

There are many reasons and potential solutions for improving the situation. Some of these involve improved search technologies, some improved search interfaces, or But, understanding the cost of this inefficiency is where I find it is valuable to start.

The first step after understanding you have this problem is to measure it, but most organizations don't want to pay for that they are just looking for solutions (we all know how this turns out). The best method I find is walking through the broad understandings of the cost of inefficiencies.

The Numbers...

At Interop 2009 I presented "Next Generation Search: Social Bookmarking and Tagging". This presentation started off with a look at the rough numbers behind the cost of search in the enterprise (see the first 16 slides). [I presented a similar presentation at the SharePoint Saturday DC event this past week, but evaluated SharePoint 2010's new social tagging as the analysis focus.]

Next Generation Search: Social Bookmarking and Tagging

View more presentations from Thomas Vander Wal.

Most of the numbers come from Google white papers on search, which gets some of their numbers from an IDC white paper. I also have a white paper that was never published and is not public that has slightly more optimistic numbers, based on the percentage of time knowledge workers search (16% rather than the Google stated ~25% of a knowledge workers time is spent searching). There are a few Google white papers, but the Return on Information: adding to your ROI with Google Enterprise Search from 2009 is good (I do not endorse the Google Search Appliance, but am just using the numbers used to state the problem).

I focus on being optimistic and have I yet to run into an organization that claims to live up to the optimistic numbers or total cost of inefficiency.

• Few organization claim they have 80 percent of or better success with employees finding what they need through search
• That is 80 percent success rate
• Or, 1 in 5 searches do not find what is they were seeking
• A sample organization with 500 searches per day has 100 failures
• An average knowledge worker spends 16% of their time searching
• 16% of a 40 hour work week is 1.25 hours spent searching
• 20% (spent with unsuccessful searches) of 1.25 hours a week is 15 minutes of inefficient productivity
• At an average salary of $60,000 per year that leads to $375 per person of inefficient productivity
• Now take that $375 per knowledge worker and multiply it by how many knowledge workers you have in an organization and the costs mount quickly
• An organization with 4,500 knowledge workers is looking at a inefficiency cost of $1,687,500 per year.
• Now keep in mind your knowledge workers are you most efficient at search
• Many organizations as a whole are running at 40% to 70% success rate for search

We Know We Have a Costly Problem

This usually is enough to illustrate there is a problem and gap with spending time resolving. The first step is to set a baseline inside your organization. Examine search patterns, look at existing taxonomies (you have them and use them to some degree, yes?) and work to identify gaps, look at solutions like tagging (folksonomy) to validate the taxonomy and identify gaps (which also gives you the terms that will likely close that gap). But get a good understanding of what you have before you take steps. Also understand the easy solutions are never easy without solid understanding.

Evaluating what, if any taxonomy you have is essential. Understand who is driving the taxonomy development and up keep. Look at how to get what people in the organization are seeking in the words (terms) they use intend to find things (this is often far broader than any taxonomy provides).

Past Attendees have Said...

“A few hours and a few hundred dollar saved us tens of thousands, if not well into six figures dollars of value through improving our understanding” (Global insurance company intranet director)

From an in-house workshop…
“We are only an hour in, can we stop? We need to get many more people here to hear this as we have been on the wrong path as an organization” (National consumer service provider)

“Can you let us know when you give this again as we need our [big consulting firm] here, they need to hear that this is the path and focus we need” (Fortune 100 company senior manager for collaboration platforms)

“In the last 15 minutes what you walked us through helped us understand a problem we have had for 2 years and a provided manner to think about it in a way we can finally move forward and solve it” (CEO social tool product company)

Is the Workshop Only for Designers?

No, the workshop is aimed at a broad audience. The focus of the workshop gets beyond the tools’ features and functionality to provide understanding of the other elements that make a giant difference in adoption, use, and value derived by people using and the system owners.

The workshop is for user experience designers (information architects, interaction designers, social interaction designers, etc.), developers, product managers, buyers, implementers, and those with social tools running already running.

Not Only for Enterprise

This workshop with address problems for designing social tools for much better adoption in the enterprise (in-house use in business, government, & non-profit), but web facing social tools.

The Workshop will Address…

Designing for social comfort requires understanding how people interact in a non-mediated environment and what realities that we know from that understanding must we include in our design and development for use and adoption of our digital social tools if we want optimal adoption and use.

• Tools do not need to be constrained by accepting the 1-9-90 myth.
• Understanding the social build order and how to use that to identify gaps that need design solutions
• Social comfort as a key component
• Matrix of Perception to better understanding who the use types are and how deeply the use the tool so to build to their needs and delivering much greater value for them, which leads to improved use and adoption
• Using the for elements for enterprise social tool success (as well as web facing) to better understand where and how to focus understanding gaps and needs for improvement.
• Ways user experience design can be implemented to increase adoption, use, and value
• How social design needs are different from Web 2.0 and what Web 2.0 could improve with this understanding

More info...

For more information and registration to to Viget Lab's Social Design for the Enterprise page.

I look forward to seeing you there.

Lessons To Learn

Sadly, the new social functionality has broken much of worked well as an ambient social tool. More problematic was LinkedIn did not seem to grasp what it had: so to build on top of very good start, but it seemingly looked at Facebook for inspiration, but Facebook does not seem to be aware of good social interaction design practices.

When building social tools for broad audiences (more than 3,000 people) — which open services on the web are — there is a progression of 3 things that must be accounted for in the planning stages: 1) Velocity; 2) Volume; 3) Relevance.

As social tools start getting used they go through a progression one of them are these three stages of concern. Velocity of information is how quickly information is added by the community and has turn over on the in the frameworks. Volume is the mass of information that accumulates over time that will force how information is shared, found, and used. Relevance becomes essential when there is large volume and filtering is needed for information flows and for allowing people using the service to have a manageable stream of information that is relevant to their needs.

Many social services can go through these three stages in a few short months if they have 50,000 users or more. LinkedIn does not seem to have considered getting to and beyond the first stage in their planning.

Social Interaction at Scale & Volume

As LinkedIn has added social features they have created more streams of information in their flow. More streams lead to more velocity of information. This can be good if the basic concepts for understanding monitoring these streams as well as providing methods for moving things out of the flow so they can be acted upon or set into a personal task flow.

It seems as if the new social features are aimed at the roughly 80 percent that have 100 or fewer connections, not the moderate or heavy connectors who are the unpaid evangelists that have helped LinkedIn grow. Not understanding the value various segments bring to a service and how to satisfy those groups is rather short sighted

Social Tsunami on Homepage

The one thing that started the frustration with LinkedIn’s shift was the flood of unrelated social items on the homepage. Much of the social content shared is personal ID focused and not group or work focused (even when shared in groups or work related settings - a quick look at activity summaries regularly shows this).

One of the task flows I had with LinkedIn was to accept a connection or get notification of a connection then go to their profile page and download their vCard. The social tsunami that took over the front page of LinkedIn made that task all-but impossible. Part of it is the velocity of information running through the front page for connections increased, velocity the design did not account for.

Additionally, the new social components started eating up valuable real estate on that page and had no simple interaction design convention for minimizing, hiding, or turning off that module of functionality from the page.

Eventually the ability to turn off notifications to the social tools was added to the Settings page, but there is no notification of that functionality on where the problem exists, the pages where this container shows up (we learned this in software design in the early 90s). Also problematic is the social elements are clustered by task/tool relevance and not person or subject. Including pivots could greatly improve this as well as allow for shifting context by the person using LinkedIn.

Focal prioritization is essential to include in initial planning, as this becomes critical when dealing with the relevance stage or even handling a scaling volume of information. Each person using a service is going to have a slightly different set of priorities for relevance and focus. This is going to require some malleability of the system interface to allow for personal optimization of their relevance and streams.

This is not emergent behavior but the reality of what happens when systems scale. LinkedIn is built “;like a classic chamber meeting where networking is orchestrated”;, as stated by Margaret Rosas. Sadly, LinkedIn is not built for flexibility that is needed as systems scale to or beyond the volume stage. It is built as if this was a surprise, which prior to 18 months ago LinkedIn’s careful approach was much smoother with their growth of features and functionality.

LinkedIn changed its layout and structure of its pages to account for the coming new functionality, which is quite smart. But it did so in a manner that seemed to consider all notifications and functionality should have the same focus.

If you remove notifications, there is no ambient notification to let you know there is really any activity. The front page is part portal and part dashboard, but the distinct concepts around these two approaches seem to have baffled the interaction designers and developers.

LinkedIn: Social Node or Social Hub?

LinkedIn also seems quite schizophrenic as to its social purpose. It has built part of the social framework as if the rest of the web only allowed limited interaction with it, which it would make it just a node on a network. This destination framework does not account for people having any other service that provides social features that could easily be shared in or out.

The other side of LinkedIn is a hub, which information flows though. Inbound status messages from other services show up in LinkedIn’s pages as to the “applications”, but using connecting identity in a manner that permits not having Twitter messages I read elsewhere show up in LinkedIn would be more than helpful (yes, part of this is OAuth, which Twitter and many other have not deemed valuable yet (come on Twitter this is not rocket surgery). The applications and information it allows in is limited to a relatively small number of services. Having a small number of services integrated should allow for contextual relevance of the objects, but that would be assuming again LinkedIn was well thought through. This interaction with services would also benefit form LinkedIn offering OpenID as well as OAuth integration to ease the pain and security.

LinkedIn does not have an open API as of yet (this should have happened when they launched status and some other social elements). The LinkedIn API for status would allow LinkedIn to be a sharing out hub as well as the partially capable in-bound hub it already is. LinkedIn is a business focussed social environment, but has not realized its DNA is business based and there are task flows and workflows to enable that would make a lot of sense.

LinkedIn Forgot the “Me” in Social

All social begins with me. Social interaction is about an individuals intentions, actions, and their activities. What things a person wants to share with others and how interact with is one part of the social framework. Another other is consumption and working with the flows of content generated by others. LinkedIn did a decent job with flow until it started adding the more social features in the last 18 months. What LinkedIn did know (focus and purpose) they now show little grasp of understanding as their features have created more flow and more velocity for the information ebbing through the service with no planning for it. It takes very little understanding of social tools to know that this will likely happen and there are interaction elements that are going to be required to handle this, for example moving things out of the flow.

Many people want to see those they have just connected with, things they just published/shared and responses. There is also the desire to hold on to things that are relevant to the individual. This holding on to things requires a means to favorite or put it in place where things can be collected and worked on later. These things could be single comments in group discussions, people’s names/profiles who are surfacing, notifications, etc.

With the velocity of information increasing in LinkedIn the capability to perform a task and drop back into the flow where you were is gone. Any decent interaction designer for social tools knows this reality and had a stack of solutions to set in place from the outset.

Social Context in Groups

The math of social software for people is the mostly the one-to-one relationships and being able to see those. But, social software occasionally is about communicating to groups.

LinkedIn added group discussions, but did this as if the last 10 to 15 years in forums and groupware platforms never existed. The group discussions are not threaded nor do they offer the option to turn on threading for the discussions (this has been default for off-the-shelf forums for over 8 years at least). Also lacking is the capability to hold on to and collect valuable items found in discussions, let alone a means to personally contextualize them.

Another thing LinkedIn fails to grasp is contextual relationships to people in the discussions. For example, if someone I know has started or commented in a group discussion the service should highlight this. There is a potentially higher social contextual relevance for that piece of information. When information starts turning from a stream into a flood this becomes insanely important.

Once this reality of contextualizing is realized, there are a couple of options that are likely to be needed quite quickly after. One is adding new people in the discussion that we interact with; this context could be surfaced in the discussion or used to augment the rational surfaced in the recommendations.

Email from groups should not be from the organization name of the group as that looks like it is from the organization. I get official information from organizations, but lacking the understanding of contextual information for e-mail makes an even greater mess of e-mail and group interactions when this is lazily designed. The “from” should begin with LinkedIn group or some other notation.

Context for Events

When LinkedIn added events, I started getting invitations to attend them. But, the wording of the invites made it sound like they were personal invitations, which is not the context they were intended. It took quite a few rather embarrassing e-mails for many events, if they were really requesting my attendance or if it was just an announcement of the event. Understanding a modicum of social interaction and social etiquette would have saved those embarrassing e-mails.

Events also launched with many bugs (many have been ironed out, but most were of the rather blatant variety). One downside of events is there are already an over abundance of event tools, which work rather well (this is a really tough tool set to get right and build). Nearly everybody I talk to has wondered why LinkedIn did not use something like Confabb to license it or buy it (there are many event services available), rather than using their own resources on something that is not up to the level of competing products. Lastly, with regard to events, while the recommendation for connections is good in LinkedIn, the recommendations for events is absolutely horrid. If that is who LinkedIn thinks I am I need a new service now.

Models for Messaging Flows

One of the things that has been flawed in LinkedIn for quite some time is messaging flows. I liked that they pushed messaging out into e-mail and I could respond to a person from my e-mail. One thing that is missing is LinkedIn not updating their messaging flows. Looking in LinkedIn it is quite often impossible to sort out. When I stated I continually have this problem, Jess Leccetti stated, “I’ve had that exact problem! I thought it was my comp being buggy!” Messaging across various media channels is tough and most often fractured. But, when offering a solution it is important to get it right.

Profile Comments Go In...

Finally LinkedIn added the capability to for people using the service to add their own private comments on to other’s profiles. This is a great addition as it allows the means to add context to files. Sadly, it does not seem to surface that information in any other manner other than going to the individual pages.

This lack of functionality outside each profile page is really mind blowing, as it leaves out the capability for using it for tagging, contextual grouping, search aggregation, and use these aggregations for sharing up dates or filtering what is shared. There are emergent activities that could evolve out of these functionalities, but again this seems to not be well thought through.

One approach is a nice simple personal tagging or labeling interaction layer with clickable aggregation interface option. This would allow simply applying glue to personally thread items together through light aggregation. The current comment system only creates islands of context that have chasms between it and other relevant or related items.

Next Steps

LinkedIn needs to get some people in that grasp social interaction design. They purportedly have some, but I am not sure they have influence or the depth of knowledge needed (either is problematic). The LinkedIn service seems to be proof something is horribly wrong along these lines.

LinkedIn also seems to be a victim of not sorting-out what it wants to be. If it wants to be a Facebook for business, the route they are taking is not going to work well for the business users as it is greatly lacking solid functionality and cohesive interaction design with task flows enabled. LinkedIn needs to be LinkedIn and not a Facebook for business.

As many on Twitter have stated, one seemingly viable option is LinkedIn’s social additions of the last 18 months should all be thrown out and simply start over. The only piece that seems to have much positive feedback is the Q&A section, which is not something that I have interest in, but seems to work passably for others.

More coherently, a real reality check is needed at LinkedIn. They must to stop adding features and functionality until they learn to fix what they have added. They need to begin with understanding how social interaction happens, how it scales, and how people need it to work at scale. Stop looking at Facebook for what features to add. LinkedIn has some deep value as a work and business focussed social site, but that is going to require a different focus that what has been applied in the last year to 18 months.

I have deep fear that LinkedIn views what is happening is emergent (emergence happens when things are used in an unpredictable manner: whether wholly unpredictable or unpredictable in that context). What is happening in LinkedIn is not emergent. It is quite predictable: This is what happens at scale with social systems and their information flows.

A grasp of social systems and their uses at various levels of scale (and potential for various interactions and needs) is really needed at LinkedIn. The slowness to act (or, sadly, react as if this was an unknown potential) and fix what they have is not a great sign of encouragement for the organization. Hopefully having Reid Hoffman back as CEO and with Jeff Wiener as President can pull this into focus and set things on a sane path.

Overview/Intro

One of my areas of focus is around social tools in the workplace (enterprise 2.0) is social bookmarking. Sadly, is does not have the reach it should as it and wiki (most enterprise focused wikis have collective voice pages (blogs) included now & enterprise blog tools have collaborative document pages (wikis). I focus a lot of my attention these days on what happens inside the organization’s firewall, as that is where their is incredible untapped potential for these tools to make a huge difference.

One of the things I see on a regular basis is tagging interfaces on a wide variety of social tools, not just in social bookmarking. This is good, but also problematic as it leads to a need for a central tagging repository (more on this in a later piece). It is good as emergent and connective tag terms can be used to link items across tools and services, but that requires consistency and identity (identity is a must for tagging on any platform and it is left out of many tagging instances. This greatly decreases the value of tagging - this is also for another piece). There are differences across tools and services, which leads to problems of use and adoption within tools is tagging user interface (UI).

Multi-term Tag Intro

The multi-term tag is one of the more helpful elements in tagging as it provides the capability to use related terms. These multi-term tags provide depth to understanding when keeping the related tag terms together. But the interfaces for doing this are more complex and confusing than they should be for human, as well as machine consumption.

In the instance illustrated to the tag is comprised or two related terms: social and network. When the tool references the tag, it is looking at both parts as a tag set, which has a distinct meaning. The individual terms can be easily used for searches seeking either of those terms, but knowing the composition of the set, it is relatively easy for the service to offer up "social network" when a person seeks just social or network in a search query.

One common hindrance with social bookmarking adoption is those familiar with it and fans of it for enterprise use point to Delicious, which has a couple huge drawbacks. The compound multi-term tag or disconnected multi-term tags is a deep drawback for most regular potential users (the second is lack of privacy for shared group items). Delicious breaks a basic construct in user focussed design: Tools should embrace human methods of interaction and not humans embracing tech constraints. Delicious is quite popular with those of us malleable in our approach to adopt a technology where we adapt our approach, but that percentage of potential people using the tools is quite thin as a percentage of the population.. Testing this concept takes very little time to prove.

So, what are the options? Glad you asked. But, first a quick additional excursion into why this matters.

Conceptual Models Missing in Social Tool Adoption

One common hinderance for social tool adoption is most people intended to use the tools are missing the conceptual model for what these tools do, the value they offer, and how to personally benefit from these values. There are even change costs involved in moving from a tool that may not work for someone to something that has potential for drastically improved value. The "what it does", "what value it has", and "what situations" are high enough hurdles to cross, but they can be done with some ease by people who have deep knowledge of how to bridge these conceptual model gaps.

What the tools must not do is increase hurdles for adoption by introducing foreign conceptual models into the understanding process. The Delicious model of multi-term tagging adds a very large conceptual barrier for many & it become problematic for even considering adoption. Optimally, Delicious should not be used alone as a means to introduce social bookmarking or tagging.

We must remove the barriers to entry to these powerful offerings as much as we can as designers and developers. We know the value, we know the future, but we need to extend this. It must be done now, as later is too late and these tools will be written off as just as complex and cumbersome as their predecessors.

If you are a buyer of these tools and services, this is you guideline for the minimum of what you should accept. There is much you should not accept. On this front, you need to push back. It is your money you are spending on the products, implementation, and people helping encourage adoption. Not pushing back on what is not acceptable will greatly hinder adoption and increase the costs for more people to ease the change and adoption processes. Both of these costs should not be acceptable to you.

Multi-term Tag UI Options

Compound Terms

I am starting with what we know to be problematic for broad adoption for input. But, compound terms also create problems for search as well as click retrieval. There are two UI interaction patterns that happen with compound multi-term tags. The first is the terms are mashed together as a compound single word, as shown in this example from Delicious.

The problem here is the mashing the string of terms "architecture is politics" into one compound term "architectureispolitics". Outside of Germanic languages this is problematic and the compound term makes a quick scan of the terms by a person far more difficult. But it also complicates search as the terms need to be broken down to even have LIKE SQL search options work optimally. The biggest problem is for humans, as this is not natural in most language contexts. A look at misunderstood URLs makes the point easier to understand (Top Ten Worst URLs)

The second is an emergent model for compound multi-term tags is using a term delimiter. These delimiters are often underlines ( _ ), dots ( . ), or hyphens ( - ). A multi-term tag such as "enterprise search" becomes "enterprise.search", "enterprise_search" and "enterprise-search".

While these help visually they are less than optimal for reading. But, algorithmically this initially looks to be a simple solution, but it becomes more problematic. Some tools and services try to normalize the terms to identify similar and relevant items, which requires a little bit of work. The terms can be separated at their delimiters and used as properly separated terms, but since the systems are compound term centric more often than not the terms are compressed and have similar problems to the other approach.

Another reason this is problematic is term delimiters can often have semantic relevance for tribal differentiation. This first surface terms when talking to social computing researchers using Delicious a few years ago. They pointed out that social.network, social_network, and social-network had quite different communities using the tags and often did not agree on underlying foundations for what the term meant. The people in the various communities self identified and stuck to their tribes use of the term differentiated by delimiter.

The discovery that these variations were not fungible was an eye opener and quickly had me looking at other similar situations. I found this was not a one-off situation, but one with a fair amount of occurrence. When removing the delimiters between the terms the technologies removed the capability of understanding human variance and tribes. This method also breaks recommendation systems badly as well as hindering the capability of augmenting serendipity.

So how do these tribes identify without these markers? Often they use additional tags to identity. The social computing researchers add "social computing", marketing types add "marketing", etc. The tools then use their filtering by co-occurrence of tags to surface relevant information (yes, the ability to use co-occurrence is another tool essential). This additional tag addition help improve the service on the whole with disambiguation.

Disconnected Multi-term Tags

The use of distinct and disconnected term tags is often the intent for space delimited sites like Delicious, but the emergent approach of mashing terms together out of need surfaced. Delicious did not intend to create mashed terms or delimited terms, Joshua Schachter created a great tool and the community adapted it to their needs. Tagging services are not new, as they have been around for more than two decades already, but how they are built, used, and platforms are quite different now. The common web interface for tagging has been single terms as tags with many tags applied to an object. What made folksonomy different from previous tagging was the inclusion of identity and a collective (not collaborative) voice that intelligent semantics can be applied to.

The downside of disconnected terms in tagging is certainty of relevance between the terms, which leads to ambiguity. This discussion has been going on for more than a decade and builds upon semantic understanding in natural language processing. Did the tagger intend for a relationship between social & network or not. Tags out of the context of natural language constructs provide difficulties without some other construct for sense making around them. Additionally, the computational power needed to parse and pair potential relevant pairings is somethings that becomes prohibitive at scale.

Quoted Multi-term Tags

One of the methods that surfaced early in tagging interfaces was the quoted multi-term tags. This takes becomes #&039;research "social network" blog' so that the terms social network are bound together in the tool as one tag. The biggest problem is still on the human input side of things as this is yet again not a natural language construct. Systematically the downside is these break along single terms with quotes in many of the systems that have employed this method.

What begins with a simple helpful prompt...:

Still often can end up breaking as follows (from SlideShare):

Comma Delimited Tags

Non-space delimiters between tags allows for multi-term tags to exist and with relative ease. Well, that is relative ease for those writing Western European languages that commonly use commas as a string separator. This method allows the system to grasp there are multi-term tags and the humans can input the information in a format that may be natural for them. Using natural language constructs helps provide the ability ease of adoption. It also helps provide a solid base for building a synonym repository in and/or around the tagging tools.

While this is not optimal for all people because of variance in language constructs globally, it is a method that works well for a quasi-homogeneous population of people tagging. This also takes out much of the ambiguity computationally for information retrieval, which lowers computational resources needed for discernment.

Text Box Per Tag

Lastly, the option for input is the text box per tag. This allows for multi-term tags in one text box. Using the tab button on the keyboard after entering a tag the person using this interface will jump down to the next empty text box and have the ability to input a term. I first started seeing this a few years ago in tagging interfaces tools developed in Central Europe and Asia. The Yahoo! Bookmarks 2 UI adopted this in a slightly different implementation than I had seen before, but works much the same (it is shown here).

There are many variations of this type of interface surfacing and are having rather good adoption rates with people unfamiliar to tagging. This approach tied to facets has been deployed in Knowledge Plaza by Whatever s/a and works wonderfully.

All of the benefits of comma delimited multi-term tag interfaces apply, but with the added benefit of having this interface work internationally. International usage not only helps build synonym resources but eases language translation as well, which is particularly helpful for capturing international variance on business or emergent terms.

Summary

This content has come from more than four years of research and discussions with people using tools, both inside enterprise and using consumer web tools. As enterprise moves more quickly toward more cost effective tools for capturing and connecting information, they are aware of not only the value of social tools, but tools that get out the way and allow humans to capture, share, and interact in a manner that is as natural as possible with the tools getting smart, not humans having to adopt technology patterns.

Broken Interaction Design on Buttons or Tabs

As the image shows the Share, Favorite, Playlists, and Flag buttons or tabs all have similar design treatment, but they do not have the same actions when you click on them. Three of the items (Share, Playlists, and Flag) all act as tabs that open up a larger area below them to provide more options and information. But, the Favorites acts like a button that when clicked it marks the item as a favorite.

This is incredibly poor interaction design as all the items should act in the same manner. If the items do not have the same action properties they really should not look the same and be in the same action space. Favorites should be a check box or a binary interface for on and off. That interaction patter more closely matches the Rate section and seems like it should have been there rather than showing a lack of understanding interaction design basics and confusing people using the site/service.

Social Sites Seem to Share a Lack of Interaction Understanding

This should have been a no brainer observation for a design manager or somebody with a design sanity check. YouTube is far from the the only site/service doing this. Nearly all of the services are not grasping the basics or are broadly applying design patterns to all user scenarios when they really do not fit all scenarios and user types (nearly every service I talk to know exactly the use type a person fits into but never takes this into account in optimization of design patterns that match that use need). Facebook really falls into this hole badly and never seems to grasp they are really making a mess of things the more features and functionality they are bringing into their service without accounting for the design needs in the interface.

My seemingly favorite site to nit pick is LinkedIn which I use a lot and has been a favorite, but their social interaction additions and interactive interfaces really need much better sanity checks and testing before they go into production (even into the beta interface). LinkedIn is really trying to move forward and they are moving in the right direction, but they really need better design thinking with their new features and functionality. Their new design is ready to handle some of the new features, but the features need a lot more refining. The new design shows they have a really good grasp that the interface needs to be a flexible foundation to be used as a framework for including new features, which could benefit from treating them as options for personalization. LinkedIn has pulled back many of the social features and seems to be rethinking them and refining them, but they really need some good sanity checks before rolling them out again.

Social Interaction in Enterprise Tools

The befuddled interaction understanding is not germane to commercial or consumer public social web sites, but it also plagues tools aimed at the enterprise. This is not overly surprising as many of the social enterprise (enterprise 2.0) tools and services are copying the public web tools and services to a large degree. This is a good thing, as it puts the focus on ease of use, which has been horribly missing in business focussed tools for far too long. But, the down side for enterprise focussed tools is they are not for the public web they are for business users, who most often do not have familiarity with the conventions on the public web and they have a large cognitive gap in understanding what the tools do and their value. There is less time for playing and testing in most business people's worklife. This means the tools need to get things right up front with clear understanding of the use needs of the people they are building for in business. This seems to be lacking in many tools as there is much copying of poor design that really needs to be tested thoroughly before launching. Business focussed tools are not hitting the same people as are on the web, which will work through poor design and functionality to see what things do. It is also important to consider that there are a wide variety of types of people using these tools with varying needs and varying interaction understandings (this will be another blog post, actually a series of posts that relate to things I have been including in workshops the last six months and presenting the last couple).

Response to Taxonomy and Tags

Josh, thanks for the link. If the world of language were only this simple that this worked consistently. The folksonomy is a killer resource, but it lacks structure, which it crucial to disambiguating terms. There are algorithmic ways of getting close to this end, but they are insanely processor intensive (think days or weeks to churn out this structure). Working from a simple flat taxonomy or faceted system structure can be enabled for a folksonomy to adhere to.

This approach can help augment tags to objects, but it is not great at finding objects by tags as Apple would surface thousands of results and they would need to be narrowed greatly to find what one is seeking.

There was an insanely brilliant tool, RawSugar [(now gone thanks to venture capitalists pulling the plug on a one of a kind product that would be killer in the enterprise market)], that married taxonomy and folksonomy to help derive disambiguation (take appleseed as a tag, to you mean Johnny Appleseed, appleseed as it relates to gardening/farming, cooking, or the anime movie. The folksonomy can help decipher this through co-occurrence of terms, but a smart interface and system is needed to do this. Fortunately the type of system that is needed to do this is something we have, it is a taxonomy. Using a taxonomy will save processor time, and human time through creating an efficient structure.

Recently I have been approached by a small number of companies who implemented social bookmarking tools to develop a folksonomy and found the folksonomy was [initially] far more helpful than they had ever imagined and out paced their taxonomy-based tools by leaps and bounds (mostly because they did not have time or resources to implement an exhaustive taxonomy (I have yet to find an organization that has an exhaustive and emergent taxonomy)). The organizations either let their taxonomist go or did not replace them when they left as they seemed to think they did not need them with the folksonomy running. All was well and good for a while, but as the folksonomy grew the ability to find specific items decreased (it still worked fantastically for people refinding information they had personally tagged). These companies asked, "what tools they would need to start clearing this up?" The answer a person who understands information structure for ease of finding, which is often a taxonomist, and a tool that can aid in information structure, which is often a taxonomy tool.

The folksonomy does many things that are difficult and very costly to do in taxonomies. But taxonomies do things that folksonomies are rather poor at doing. Both need each other.

Complexity Increases as Folksonomies Grow

I am continually finding organizations are thinking the social bookmarking tools and folksonomy are going to be simple and a cure all, but it is much more complicated than that. The social bookmarking tools will really sing for a while, but then things need help and most of the tools out there are not to the point of providing that assistance yet. There are whole toolsets missing for monitoring and analyzing the collective folksonomy. There is also a need for a really good disambiguation tool and approach (particularly now that RawSugar is gone as a viable approach).