structured data mp may 2012

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Structured Data: None / Some / All Mad*Pow User Experience, May 2012

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Structured Data Talk for Experience Design Group, May 2012

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Structured Data: None / Some / All

Mad*Pow User Experience, May 2012

1995-2012 = Gazillions of Websites

Our design problem was an evolution of visual literacy

— Readers were trained to find information in printed books/magazines/newspapers

— Digital publications lack physical context

— Location and scope of information was invisible

Mad*Pow | May 2012 | 2

Clients = Publishers Users = Readers

Our Design Task was to connect Readers to content

— Adapt graphic language – type, color, image – from the page to the screen

— Create navigation systems that help users understand what they can find on a website

— Communicate the structure of content in flexible repeatable units

Mad*Pow | May 2012 | 3

2012=Massive Pattern of Nodes

2012=Nodes with Geo Context

Today Users are

— Convinced they can find what they want “on the Internet”

— Producing & managing dematerialized content: photos, videos, music, email, compound documents

— Creators & consumers with storage/creation and retrieval/consumption needs

— Looking for something all the time

Mad*Pow | May 2012 | 6

Today Users want to

— Record, share, publish

— Be convinced, amused, in control

— Find, sort, sift and copy

— Mix, reorder and arrange

They don’t explicitly know what metadata is

They are solving problems by implicitly manipulating metadata

Mad*Pow | May 2012 | 7

Today’s IA/UX Problem

Every IA/UX problem is a Metadata Continuum

— No Structure Vacuum Raw

— Some Structure Marsh Eatable

— Complete Structure Field Cooked

Mad*Pow | May 2012 | 8

Unstructured Data

Data Vacuum: no metadata has been added to items

Even Data Vacuums include content & context

The 50-year-old Information Retrieval / Library Science trade-off:

— Precision: finding only what you are looking for

— Recall: not missing anything that might contain what you are looking for

Mad*Pow | May 2012 | 9

Data with no structure: Names

— A character-string a person, place or thing is known by

— People have many names: professional names, familiar

names, legal names

— Places and things have many names in different

languages

— As data, a name presents a major problem:

IT IS NOT UNIQUE

— For example: “paul kahn”

Mad*Pow | May 2012 | 10

There are many “paul kahn”s

Mad*Pow | May 2012 | 11

Paul W. Kahn, author and Law

Professor at Yale

University,

New Haven CT

Dr. Paul Kahn, Urologist in

Plantation FL

Paul Kahn, writer, editor,

psychological

counselor and

disability rights

advocate in Newton MA

Roshi Paul Genki Kahn

Spiritual

Director of Zen

Garland in

Wyckoff, NJ

Paul Kahn serving in Iraq

What are most people searching for?

Mad*Pow | May 2012 | 12

Who is searching?

Mad*Pow | May 2012 | 13

Mad*Pow | May 2012 | 14

Use algorithms to surface what users might want

to see (and what we want them to see)

Where did I put that document?

The tools we use:

— Personal Memory

— Folder names

— Desktop search

What kinds of structure can we present?

Mad*Pow | May 2012 | 15

Implicit metadata:

— Document type

— File name

— Document content

LATCH (+): Organize information for understanding & ease of use

Mad*Pow | May 2012 | 17

Location

Alphabet

Time

Category

Hierarchy

+ Common Focus

Richard Saul Wurman

INFORMATION ANXIETY 2

Semi-Structured Data

Data Marsh: some metadata without predefined language or requirements

— Tagging : users add uncontrolled keywords

— Profile: users intentionally add metadata about themselves

— Time / Location stamps: where and when

— Tracking: users unintentionally add metadata about themselves as interactions are tracked

Mad*Pow | May 2012 | 18

Aggregation/Reproduction Sites

— Sites that aggregate user-provided content Slideshare / YouTube / Dailymotion / Vimeo / SoundCloud / Flickr

— Sites where users create and republish content to social networks LinkedIn / Facebook / Twitter

Mad*Pow | May 2012 | 19

Mad*Pow | May 2012 | 20

— Search

— Feature

— Categories + Time

— Common Focus

Mad*Pow | May 2012 | 21

Implicit metadata:

— Sort criteria

— Time/Date stamp

— Document type

(2010 version)

Mad*Pow | May 2012 | 22

Mad*Pow | May 2012 | 23

Structured Data

Mad*Pow | May 2012 | 24

Data Fields: where metadata has been explicitly added

to items according to an agreed-upon standard

— The Content is made to fit a pre-defined structure

— The required parts of the structure are completed

— Each metadata dimension qualifies and reinforces the

meaning of the content

— Many kinds of relationships can be harvested

Mad*Pow | May 2012 | 25

Mad*Pow | May 2012 | 27

Map of the Market

Mad*Pow | May 2012 | 28

NY Times Immigration Explorer

Mad*Pow | May 2012 | 30

Structured data ≠ Usable data

Mad*Pow | May 2012 | 31

Mad*Pow | May 2012 | 32

Open Paths data from my iPhone

Mad*Pow | May 2012 | 33

Would the world be a better place if

— Everything had a unique ID?

— Every digital object with a unique ID contained

structured data?

How does structured data affects quality of life questions?

Mad*Pow | May 2012 | 34

A Proverb for User Centered Design

— Hwa is thet mei thet hors wettrien

the him self nule drinken

— Who can give water to the horse

that will not drink of its own accord?

Old English Homilies, circa 1175

Mad*Pow | May 2012 | 35

Structured Data Value Proposition

— People want to find things, they don’t want to “learn” how to find things

— People understand how to use Structured Data

— No one wants to create Structured Data

— It is our task to leverage the Structured Data people already understand

Mad*Pow | May 2012 | 36