For life sciences brands and digital marketers, getting digital content to market faster and improving control starts with having the right foundation. Get on the path to better content governance with best practices for metadata and taxonomy.

1. Proprietary and Confiden/al. © 2018 Op/mity Advisors
Veeva
2018 DAM for
Life Sciences Forum
John Horodyski, Partner
Op/mity Advisors

2. Agenda
Welcome
and
Introduc/ons
Metadata
Taxonomy
Best
Prac/ces
Conclusion
01
02
03
04
05

3. 3
John Horodyski
Partner, Informa/on Management
John Horodyski is a Partner with Op/mity Advisors with execu/ve management strategy
experience in Informa/on Management including Digital Asset Management (DAM),
Content Strategy, Metadata and Taxonomy design, Content Management, Governance,
and Rights Management.
John has provided strategic direc/on and consul/ng for a variety of Fortune 100 and 500
clients from Consumer Packaging Goods, Media & Entertainment, the Pharmaceu/cal
industry, and the Insurance industry.
John is also an adjunct faculty member at San Jose State University where he teaches a
graduate course in Digital Asset Management. In addi/on to regular training & public
speaking on digital media and metadata, John is a Board Member/Metadata Editor of the
Journal Of Digital Media Management, and is a monthly DAM contributor to CMS Wire.
In May 2016, John published the book, Inform, Transform, Outperform: Digital Content
Strategies to Op<mize Your Business for Growth.

4. Metadata
02

5. 5
Metadata Ma]ers
• Descrip/ve,
Administra/ve,
and
Structural
(Technical)
depic)on
of
an
asset
• Cri)cal
for
any
organiza)on
looking
to
be8er
manage
and
leverage
its
content
• Metadata
strategy
must
consider
people,
process
and
technology
• Metadata
is…
• The
backbone
of
your
company’s
content
• The
lifeblood
of
your
DAM
• A
snapshot
in
)me
• #metadatama8ers
• #ilovemetadata
• #metadataisnotanalterna)vefact
Metadata
is
the
spirit
of
an
intellectual
or
crea)ve
asset
…
it’s
everything
you
have.

6. These are Good Times
for Metadata
6

7. “This is just metadata
— there is no content
involved”
– Sen. Dianne Feinstein
7

8. 8
What
is
metadata?
It
is
data
about
data.
It
refers
to
the
descrip)ve
elements
that
define
and
describe
an
asset.
Metadata
may
be
broken
down
into
three
main
categories
(NISO):
Metadata
DESCRIPTIVE
METADATA
describes
a
resource
for
purposes
such
as
discovery
and
iden)fica)on
(i.e.,
informa)on
you
would
use
in
a
search).
It
can
include
elements
such
as
)tle,
subject,
creator,
date,
loca)on
and
keywords.
STRUCTURAL
(TECHNICAL)
METADATA
indicates
how
compound
objects
are
put
together
(for
example,
file
format,
file
dimension,
file
length,
size,
dimensions,
etc.).
ADMINISTRATIVE
METADATA
provides
informa)on
that
helps
manage
an
asset.
Two
common
subsets
are
rights
management
metadata
(which
deals
with
intellectual
property
rights)
and
preserva4on
metadata
(which
contains
informa)on
needed
to
archive
and
preserve
an
asset.
1
2
3

9. These
are
Good
Times
for
Metadata
…

10. These
are
Good
Times
for
Metadata
…

11. 11
1. CONTRIBUTOR
2. COVERAGE
3. CREATOR
4. DATE
5. DESCRIPTION
6. FORMAT
7. IDENTIFIER
8. LANGUAGE
9. PUBLISHER
10. RELATION
11. RIGHTS
12. SOURCE
13. SUBJECT
14. TITLE
15. TYPE
Dublin Core
An en/ty responsible for making contribu/ons to the resource
The spa/al/temporal topic of the resource, the spa/al applicability of the resource, or the jurisdic/on under
which the resource is relevant
An en/ty primarily responsible for making the resource
A point or period of /me associated with an event in the lifecycle of the resource
An account of the resource
The file format, physical medium, or dimensions of the resource
An unambiguous reference to the resource within a given context
A language of the resource
An en/ty responsible for making the resource available
A related resource
Informa/on about rights held in and over the resource
Related resource from which the describe resource is derived
Topic of the resource
Name given to the resource
Nature or genre of the resource

12. Proprietary
and
Confiden)al.
©
Op)mity
Advisors,
2016
12
These
are
Good
Times
for
Metadata
…
Cat
Kitten
Feline
Kitty
Felis
Catus
House
Cat

13. 13
Control & Consistency
Good metadata is all about your assets, access, and users
SEARCH
&
RETRIEVAL
IN
DIGITAL
ASSET
MANAGEMENT
(DAM)
• More
than
40%
of
)me
is
wasted
searching
for
exis)ng
assets
and
recrea)ng
them
when
they
aren’t
found
• Very
expensive
–
in
lost
produc)vity
and
frustra)on
in
non-­‐discovery
• The
key
is
good
metadata
–
your
data
wants
to
be
found
MAKE
MACHINES
SMART
—
AUTOMATE
PROCESSES
• Content
iden)fica)on,
reuse
and
management
• Workflow
automa)on
• Ar)ficial
intelligence
(AI)
and
machine
learning
RIGHTS
MANAGEMENT
• Rights
tracking,
enforcement,
and
compliance
–
more
effec)ve
rights
enforcement
resul)ng
in
stronger
revenue
reten)on
• Compliance
is
cri)cal
to
pharmaceu)cal
industry
and
content
strategy

14. 14
Language is always in a state of change
The
best
way
to
plan
for
future
change
is
to
apply
an
effec)ve
layer
of
metadata
governance
for
your
DAM
system.
There
is
more
to
maintaining
the
metadata
than
just
maintaining
the
taxonomy
and
metadata
specifica)ons
…
you
must
manage
the
change.
It
is
es)mated
that
every
year,
800
neologisms
(new
words
and
phrases)
are
added
to
the
English
language.
So
li8le
of
our
modern
language
is
wri8en
in
stone;
it
is
always
evolving.

15. 15
Governance
New
words
added
to
Oxford
English
Dic)onary
(OED)
:
1. LOLcat
—
pictures
of
cats
you
find
all
over
the
Internet
accompanied
with
funny
cap)ons,
typically
with
misspellings
and
incorrect
grammar
2. Five-­‐second
rule
—
makes
people
feel
be8er
for
ea)ng
food
that’s
fallen
on
the
floor;
this
rule
says
it
will
be
uncontaminated
if
it’s
only
been
five
seconds
3. Mahoosive
—
excep)onally
big
4. Digital
footprint
—
the
informa)on
about
you
that
can
be
found
online
5. Duck
face
—
an
exaggerated
pou)ng
expression,
ohen
made
for
a
selfie
6. Man
crush
—
non-­‐sexual
admira)on
one
man
has
for
another

16. 16
Governance
New
words
added
to
Oxford
English
Dic)onary:
1. Askhole
(n)
—
someone
who
asks
many
stupid,
pointless,
or
obnoxious
ques)ons
2. Nonversa)on
(n)
—
a
completely
worthless
conversa)on;
small
talk
3. Errorist
(n)
—
someone
who
repeatedly
makes
mistakes,
or
is
always
wrong
4. Aherclap
(n)
—
the
last
person
who
claps
aher
everyone
else
has
stopped

17. Taxonomy
03

18. These
are
Good
Times
for
Metadata
…

19. These
are
Good
Times
for
Metadata
…
“This
is
just
metadata
-­‐
there
is
no
content
involved”
–
Sen.
Dianne
Feinstein

20. These
are
Good
Times
for
Metadata
…
“This
is
just
metadata
-­‐
there
is
no
content
involved”
–
Sen.
Dianne
Feinstein

21. These
are
Good
Times
for
Metadata
…
“This
is
just
metadata
-­‐
there
is
no
content
involved”
–
Sen.
Dianne
Feinstein

22. These
are
Good
Times
for
Metadata
…
“This
is
just
metadata
-­‐
there
is
no
content
involved”
–
Sen.
Dianne
Feinstein

23. These
are
Good
Times
for
Metadata
…
“This
is
just
metadata
-­‐
there
is
no
content
involved”
–
Sen.
Dianne
Feinstein

24. These
are
Good
Times
for
Metadata
…
“This
is
just
metadata
-­‐
there
is
no
content
involved”
–
Sen.
Dianne
Feinstein

25. 25
THE CHALLENGE
Taxonomy Intro
• Enhances and improves search
• Single vocabulary reinforces “one voice” – content is classified consistently
• Overall scheme for organizing informa/on is to solve a business problem
based on user needs and to show correla/ons between subjects
Taxonomy is required for meaningful informa/on management
and is cri/cal to effec/ve findability.
Taxonomy is the science
of classifying informa/on
into groups or classes
that share similar
characteris/cs
• ANSI / NISO Z39.19-­‐2005
• “A collec/on of controlled
vocabulary terms organized
into a hierarchical structure.”

26. 26
Taxonomy
Hierarchical Structure
• Have
content
at
every
level
—
empty
categories
present
empty
value
to
users
• 4
-­‐
5
levels
deep
in
most
cases
• Have
balance
breadth
and
depth
—
users
must
work
harder
to
use
a
taxonomy
3
categories
broad
and
9
deep
than
to
use
one
that
is
7
wide
and
2
deep
Future
Proofing
-­‐
Can
you
reach
your
objec)ve
within
2
–
3
clicks?

27. 27
The
three
key
ques/ons
you
need
to
answer
are:
1. What
problems
do
you
need
to
solve?
2. Who
is
going
to
use
the
metadata,
and
for
what?
3. What
kinds
of
metadata
are
important
for
those
purposes?
Building a Metadata Strategy
KEY
QUESTIONS
Now
that
the
founda)on
has
been
set
with
defini)ons
and
key
concepts,
you
can
get
to
work
on
building
an
effec)ve
metadata
strategy.

28. 28
Metadata … What to Do Next?
1. Build the Right Team
• Librarians are cri/cal to success
2. Make the Business Case
3. Requirements Gathering
-­‐ Stakeholder interviews / Content audit / Use case scenarios
4. Metadata Specifica/ons
5. Workflow
6. QA & UA Tes/ng
7. Governance

29. 29
DAM Good Things to Consider
1. Compliance & Rights Management
2. Naming Conven/ons
3. Op/mize your Metadata Model
4. DAM is the core of Marke/ng Technology
5. User Educa/on and Training Materials -­‐ Metadata drives the DAM and Search
6. Enterprise / Global Taxonomy
7. Governance

30. Best Prac/ces
04

31. 31
Best Prac/ces
Content is no longer the only king; the user is also worthy
UX & UI -­‐ how your customers want to interact with content before DAM design
Ensure you are building the right system for the right users
Achieve maturity in incremental stages with feedback loops, user tes/ng and evalua/ons
Accept that it won’t be perfect

32. Conclusion
05

33. Metadata
Forward
Think
beyond
the
here
and
now
of
your
metadata.
Get
connected.
DAM is a program, not a project
DAM is a human endeavor
Implement good governance

34. Washington, D.C. • Berlin • Brussels • London • Los Angeles • Minneapolis • New England • New York • Zürich
@Op/mity
op/mityadvisors
Op/mity
op/mityadvisors.com
Thank you!
Thank you for your valuable /me.
For further informa/on, please contact:
John Horodyski
Direct: +1 (917) 656-­‐2956
John.Horodyski@op/mityadvisors.com
Op/mity Advisors
183 Madison Ave, Suite 1205
New York, NY 10016

35. 35
Reference Materials
Taxonomy / Metadata Solu/ons (Product Websites)
Autonomy
h8p://www.autonomy.com/
Controlled
Vocabulary
h8p://www.controlledvocabulary.com/products/index.html
Data
Harmony
h8p://www.dataharmony.com
Mul)tes
h8p://www.mul)tes.com
SchemaLogic
h8p://www.schemalogic.com
Tagasauris
h8p://www.tagasauris.com/
Term
Tree
h8p://www.termtree.com/au
Wordmap
h8p://www.wordmap.com/
A2Z
Keywordin
h8p://a2zkeywording.com/
(keywording
sohware)
Keyword
Compiler
h8p://www.keywordcompiler.com/(keywording
sohware)
COMMERCIAL
Ge8y
Trust
(not
Ge8y
Images)
Geography
h8p://www.ge8y.edu/research/tools/vocabulary/tgn/
Art
&
Architecture
h8p://www.ge8y.edu/research/tools/vocabulary/aat/

36. 36
Reference Materials
Taxonomy / Metadata Solu/ons (Product Websites)
Data
Documenta)on
Ini)a)ve
h8p://www.ddialliance.org/
Dublin
Core
h8p://purl.oclc.org/dc/
NAICS
h8p://www.census.gov/epcd/www/naics.html
IEEE
LOM
h8p://ltsc.ieee.org/wg12/
(Educa)on)
ISO
h8p://www.iso.org/iso/home/standards.htm
(metadata,
taxonomy)
IPTC
h8p://www.iptc.org/site/subject-­‐codes/
(News)
MPEG-­‐7
h8p://mpeg.chiariglione.org/standards/mpeg-­‐7/mpeg-­‐7.htm
MIX
h8p://www.loc.gov/standards/mix/
(Images)
ONIX
h8p://www.editeur.org/15/Previous-­‐Releases/
(Book
Industry)
PBCore
h8p://pbcore.org/index.php
(Media)
PRISM
h8p://www.idealliance.org/specifica)ons/prism/
(Publishing)
SOC
h8p://www.bls.gov/soc/
(Occupa)onal
categories)
SMPTE
h8p://www.smpte-­‐ra.org/mdd/
(Mo)on
Pictures)
Wikipedia
h8p://en.wikipedia.org/wiki/Metadata_standards

37. 37
Reference Materials
• Duval,
E.,
Hodgins,
W.,
Su8on,
S.,
and
Weibel,
S.
(2002).
Metadata
principles
and
prac)cali)es.
D-­‐Lib
Magazine,
8
(4).
h8p://www.dlib.org/dlib/april02/weibel/04weibel.html
• Gill,
T.,
Gilliland,
A.,
and
Woodley,
M.
Baca,
M.
(ed.).
(n.d.).
Introduc)on
to
metadata:
Pathways
to
digital
informa)on,
Online
edi)on,
version
2.1.
Los
Angeles:
J.
Paul
Ge8y
Trust
/
Ge8y
Standards
Program.
h8p://www.ge8y.edu/research/conduc)ng_research/standards/intrometadata/pdf.html
• NISO
Press.
(2004).
Understanding
metadata.
Bethesda,
MD:
Na)onal
Informa)on
Standards
Organiza)on
[NISO]
h8p://www.niso.org/standards/resources/UnderstandingMetadata.pdf
• Chagoya,
F.
(2010).
Metadata:
Principles,
prac)cal
applica)on,
best
prac)ces,
op)miza)on
and
workflow.
Journal
of
Digital
Asset
Management,
6(5),
257–261.
h8p://www.palgrave-­‐journals.com/dam/archive/index.html
• Tonkin,
E.,
&
Hewson,
A.
(2010).
Building
blocks
of
metadata:
What
can
we
learn
from
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Interna)onal
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Dublin
Core
and
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0(0),
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h8p://dcpapers.dublincore.org/pubs/ar)cle/view/1041
Taxonomy / Metadata Solu/ons (Product Websites)