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Information Standards Lunch and Learn
1. Information
Standards
Lunch and Learn
Matt Johnson
July 21, 2011
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2. Objectives
Understand:
• What information
standards are
• Some fundamental
problems which they
can help solve
• What tools are used to
solve them
• How we can help you
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3. Stuff can
be hard to
find.
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4. Structured
information
helps you
find it.
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5. Who are you and why are you telling me
this?
•Program Manager,
Information Standards,
eServices
•Managing data in NGOE T3
application and across its
various integrations
•Expertise:
•web portal optimization
•content delivery
•content classification
•search optimization
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6. Problem: grouping like things together
Where do I
start?
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51. What is information architecture?
• “the structural design of
shared information
environments” (Morville/Rosenfeld)
• “the art and science of
organizing and labeling
websites, intranets, online
communities and software to
support usability” (IAI)
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52. What are information standards?
• Building blocks
• Fit to IA frame
• Formal or de
facto
• Global, industry,
enterprise
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57. What’s a taxonomy?
•Classification of things or
concepts
•Controlled vocabulary
•Hierarchical structure
•Used for enterprise
applications, public web
sites
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58. What’s a thesaurus?
• Groups like
things together
• Makes fine-
grain
distinctions
among like
things
• Contrasts like
with unlike
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59. What is Master Data Management
(MDM)?
“A set of processes and
tools that consistently
defines and manages
the non-transactional
data entities of
an organization”
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60. Information Standards activities
• Curate authoritative
enterprise metadata
• Establish best
practices
• Ensure currency and
quality
• Support knowledge
discovery
• Consult with
consumers
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61. Questions?
Talk to us!
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Notas del editor
A little more about your presenter. The scenarios I’m about to take you through illustrate common information problems encountered on the web and how implementing structured information can address them.
Say I’m planning on going to cooking school and need to buy some specialized equipment in order to be ready for class.Using this alphabetical list, where would I start to look for stuff? How could I group items in this list to make them more findable?
There’s something called “knives”, but there’s a bunch of different kinds of knives here, too …
Then there’s things I’d need to use with knives, like a butcher block …
Over and above knives, there’s a whole range of other tools I’d use for cutting food.In sum, there’s several different ways you might group items in this list, but which works best? Oriented to needs of user base
Here’s an example of successful grouping of kitchen appliances on bestbuy.com. Note the dual navigation (text- and image-based).
Here’s a search parameter matrix from Epicurious. By classifying different recipe attributes together, users have an easier time refining their search.
Say I’m visiting EMC’s Bangalore office and want to do some traveling. I have a car, so I Google driving directions from Bangalore to Madras.
Here’s my Google maps result. But hey – what are these two cities? I’m guessing they’re the same as what I typed in, but can I be sure?
What a visitor to India may not know is that in recent years many cities elected to change their official names. However, the older names are still used even by Indians in many cases. Google keeps track of the name changes, but in a way which may not be intuitive for the user.
Another example of multiple names for the same object: what would you call these things?
And what would you call these?
They’re more or less the same thing, right?
Except they go by very different names in different parts of the English-speaking world.
Here’s Air India’s solution to the Chennai-Madras conundrum: show both names in the label, and use a typeahead functionality to allow users to search either one. Not the most elegant solution, because of the data manipulation involved, but much more intuitive to the user.
And here’s how Wikipedia manages eggplant-aubergine:
Wikipedia typically does an outstanding job of linking alternative entry terms (“aubergine”) to authority documents (“eggplant”), and takes the additional helpful step of exposing the cross-references. Note, too, the link to the “Eggplant (Color)” article – another layer of semantic distinction, rendered very clearly.
Another important need is to distinguish among things that are really quite different but nonetheless look or sound the same. Looking at these two images, you wouldn’t think they had much in common, right?
Except that they’re homophones – differently spelled words representing different concepts which sound alike. This is a classic example from Library Science 101. Of course, it relates to spoken language, which is typically less relevant to what we do on the web.
A more sophisticated, text-based example of disambiguation is this one. What does this word mean?
Well, depending on context, it could be a fish …
… or a brand of beer …
… or a brand of shoes …
… or someone’s last name …
… or a musical instrument.
So if someone types “bass” into a search engine, how can we ensure relevant results?
Here’s one way: Corbis (online image DB) presents an option to users entering common ambiguous search terms to choose the appropriate qualifier and refine the result set accordingly.
Here’s an example of a real-world problem that I encountered which exemplifies a number of issues already discussed. I was getting ready to make cheese fondue …
… and cheese fondue requires gruyere, a special kind of Swiss cheese.
I’ve never bought gruyere before, but figure I’ll go to my neighborhood grocery store for it – they have a pretty big cheese section.
And, indeed, there are a lot of cheeses: I see cheddar cheese …
… American cheese …
… cottage cheese …
... and spray cheese …
… but no Gruyere. Well, that’s frustrating. Maybe it’s there and I’m just not seeing it.
So I see this guy. He’s an employee and seems pretty approachable, so I ask him where the Gruyere might be.
Unfortunately, he works in the produce section, so he doesn’t have any clue.
What I don’t know, and what he may not realize that I don’t know, is that there’s a whole other part of the store devoted to “specialty cheeses”. You know, the kinds that don’t come in aerosol cans.
If someone had, say, put a sign in Aisle 2 to direct me to the specialty cheeses, I wouldn’t have had to rely on asking someone who didn’t know the answer to my question. Instead, I figure I’ll try my luck at another store. My neighborhood grocery just lost a sale.
The cheese example may not look especially relevant to the web, but in fact it characterizes web experiences that we have all the time. Say I’m looking for product documentation on Powerlink. Faced with an array of menus, none of which says “documentation”, going to the support search box seems like the path of least resistance …
… except that the search box is kind of like the produce guy: it only knows answers relevant to its domain of knowledge – in this case, what it indexes.
And it happens documentation isn’t part of that index, so I don’t get the result I’m looking for.
What I don’t know, and what the site doesn’t know I don’t know, is that the documentation I’m looking for is available via a set of nav menus under the “Product” header. Because the information is distributed across multiple locations which don’t point at each other, I come away from my experience assuming what I’m looking for doesn’t exist …
… which is a fail all around. On Plink the experience of finding things is a problem. We’re working hard to improve findability on NGOE, using SbP pages, improved search, and structured data (T3).
The problem scenarios identified up to now are issues which the discipline of information architecture is intended to address.
In particular, they are problems which can be addressed by implementing information standards. Those standards become some of the building blocks on which a better site architecture and user experience can be built.
Ongoing feedback from usability engineers and user experience architects is essential to progressive improvement of information standards and tools used to apply them, and with that progressive improvements to the experience overall.
One tool which is regularly used to implement information standards (and a tool which you’ve heard a lot about in eServices) is taxonomy. But what is a taxonomy? Often people hear “taxonomy” and think of “taxes” …
… or “taxidermy” …
… but of course it doesn’t have anything to do with these.
A taxonomy is a tool for ensuring that we can have authoritative values and maintain relationships among them.
You may have used a thesaurus, which performs a similar function: grouping synonyms together, making fine-grain distinctions among them, and contrasting them with their opposites (antonyms).
Taxonomy is also an important tool to support MDM, as taxonomy hierarchies are a way of managing non-transactional data (say, product names, as opposed to service requests). We are hoping that the taxonomies built to support eServices and other EMC web properties may be leveraged as part of an enterprise-level “master chef” MDM initiative.
In summary, here’s what we do all day, all in aid of helping solve problems like the ones we’ve shown you in the past hour. If you have a problem you think we can help with, please don’t hesitate to ask!