Designing the Garden: Getting Grounded in Linked Datadownloads.alcts.ala.org/mw_ac/ac15_linked_data_riley_garden.pdf · Designing the Garden: Getting Grounded in Linked Data #rwlod

Designing the Garden: Getting

Grounded in Linked Data

#rwlod

Jenn Riley (@jenlrile)

Associate Dean, Digital Initiatives

McGill University

"Full fathom five thy father lies,

Of his bones are coral made,

Those are pearls that were his eyes,

Nothing of him that doth fade,

But doth suffer a sea-change,

into something rich and strange,

Sea-nymphs hourly ring his knell,

Ding-dong.

Hark! now I hear them, ding-dong, bell.”

--Shakespeare, The Tempest

#rwlod Beyond the Looking Glass, ALCTS Preconference 2015


Photo by Liam Moloney, https://flic.kr/p/7Qux27, CC BY-SA

1. It’s not “our” data and “their” data – it’s one big graph.


It’s about the connections

https://linkedjazz.org/network/

Graph-based world views


http://ebiquity.umbc.edu/blogger/2015/06/06/querying-rdf-data-with-text-annotated-graphs/

Connecting things together


dbpedia:Willia

m_Shakespeare

1615-04-23

1564-04-26

dbpedia:Str

atford-

upon-Avon

dbpedia-owl:

birthDateworldcat-

work:10745266

81

fast:1069678

# Political

Refugees

“Tragicomedy’

“Shakespeare’s

Comedy of the

Tempest”

schema:

genre

viaf:9699404

8

# William

Shakespeare

foaf:person

rdf:

type

schema:

CreativeWork

rdf:

type

� Creating so much data!

� Where the scope of “library data” ends

� What it is and isn’t “our job” to do

� Making “complete” descriptions ourselves

� Mapping data from “other” vocabularies into “library”

vocabularies

This means we can stop worrying about…


� Learning other metadata cultures

� Being Linked Data ecosystem good citizens

� How the technology and the data can most effectively work

together

� Making connections between things

� Understanding other vocabularies and communities

And start worrying about…


2. We can expect more intelligence in the system.


http://hangingtogether.org/?p=4167; September 2014


Guido Reni (1575-1642)

Hercules Killing the Hydra of Lerna

c. 1620-1621

oil on canvas

commissioned along with other

scenes from the mythology of

Hercules in 1617 by Ferdinando

Gonzaga, for a room in the Villa

Favorita in Mantua, Italy inv. 535

Musée du Louvre, Paris, France

� Mine usage data to enhance relevance and utility in discovery

� Start from the most relevant information and provide easy

means for quick expansion on demand

� Coherently display conflicting information

� Give indications of provenance of information

What systems must do for users


If we’re serious about

information literacy, we have to

give our users tools and then

trust them.


� Flag dead ends for review and action

� Normalize most string-based data

� Highlight potentially conflicting information

� Hide complexity (URIs, etc)

� Mine and show candidate connections for review

What systems must do for metadata maintainers


� Choosing one authoritative “correct” assertion in the face of

conflicting data

� Whether or not a given source meets a certain standard for

authority

� Authorized headings, access points

� And textual justifications for them

� A large proportion of the data cleanup tasks we used to do

� For example, the formatting of strings

� But we can expect a new set of these to emerge!



� How to enhance system algorithms

� How users best interact with complicated information

� Methods for automated metadata creation and cleanup

� Getting large amounts of new data into the system



3. The information age has provided

a new definition of “authority.”


� Current narrative:

� Libraries create good

metadata!

� Because we’re trained to do so

� We’re consistent and follow

rules

� That’s what makes good data

� Other people create bad data

� Because it’s not consistent

� Using a well build record

structure is a key part of good

metadata

� But…

� We don’t read the books we

catalogue

� We don’t typically have expertise in

the subjects of the works we

describe

� Sometimes we don’t even read or

speak the language those works use

� Our perspective is pretty different

from our users’

� Number of things to describe is

quickly expanding and our budgets

are shrinking

Let’s take a good, hard look at our “authoritative” data


� Remember, we’re looking at more intelligent systems in the LD

world

� That can deal with inconsistency, masking it or cleaning it up

� The LD graph allows us to not worry about metadata structures

� So consistency and rules are no longer the primary drivers of

good metadata

� Which means we can turn large swaths of the creation of

metadata over to domain experts

Wait, it’s not about consistency and rules?



https://www.digitalcommonwealt

h.org/search/commonwealth:5h7

3q9544

If we’re serious about good

metadata, we need to start from

expert information.


We need this guy


http://www.betterlivingthroughbeowulf.com/scholars-lose-themselves-in-their-research/

And we need these folks too!


Photo by veggiesosage, https://flic.kr/p/5WjAsK, CC-BY-NC-ND

Really, it’s going to be OK

https://xkcd.com/386/


The Linked Data community cares about provenance


http://www.w3.org/standards/techs/provenance#w3c_all

� Deep research on materials for which there’s already a

knowledgeable community

� Descriptions being “complete”

� Making sure everything is “right”



� Mining the data that’s already out there

� Promoting voices of those who engage with content

� How usable systems can be built to generate Linked Data from

activities real people already partake in

� Seeding basic information for the rare and unique materials we

hold that have never been released

� Connecting data from communities operating in different

languages



4. Our job is to tend the garden.


Metadata is an ecosystem

Photo by Temari 09, https://flic.kr/p/6UskT1, CC-BY-NC

The garden needs tending

Photo by Center for International Forestry Research, https://flic.kr/p/dbx1Gt,CC-BY-NC-ND

A new model – making connections

https://thenounproject.com/term/connection/25392/

� “Original cataloguing” and “copy cataloguing”

� Getting data into “our systems”

� Doing all the work that needs to be done the first time we think

about a specific item



� Understanding the Linked Data environment

� Locating large and useful datasets

� Understanding vocabularies developed elsewhere

� Finding good people that can analyze relationships and make

new connections



� The data and systems are all in the cloud

� Library-based discovery less important but likely still around for a

while

� Several ways systems can navigate the graph

� Crawling

� Dereferencing

� Query federation

� (See http://linkeddatabook.com/editions/1.0/#htoc84)

So how will Linked Data systems work?

� This is all the way it should work

� It’s going to be a while before we get there

� Big effort needed to start connecting up these data sets

� Data sets and tools will get better as we start using the data in

this way and demand more

� The library community can help to shape this evolution, but only

if we fully understand and engage with the assumptions and

mechanisms in play in the Linked Data community

Reality check


� This will be hard. But that won’t stop us.

� We need to redefine our baseline.

� We need to rethink what new models mean for us.

� And, most importantly, we need to put the right people in

positions to work through these issues and get the details

settled.

A sea-change? Most definitely.


We got this.

� [email protected]

� @jenlrile

� These presentation slides:

http://www.jennriley.com/presentations/alaannual2015/riley-

garden.pptx

Thank you!


Documents

Designing the Garden: Getting Grounded in Linked Datadownloads.alcts.ala.org/mw_ac/ac15_linked_data_riley_garden.pdf · Designing the Garden: Getting Grounded in Linked Data #rwlod