The document discusses transcribing and making accessible the diaries of George Leslie Adkin through crowdsourcing. It describes the process used to digitize the diaries and photographs, create conceptual entities for each diary entry, and link them with related people, places and topics. While crowdsourcing could help with transcription, integrating the data and developing an effective display platform presents challenges given the large scope and complexity of the project. More work is needed to formalize the project and determine the most appropriate roles for crowdsourcing versus in-house work.

1. “Choir attempted that beautiful
anthem “Oh, Radiant Morn” –
made a hash of it”
Making a hash of the Adkin Diary transcriptions
Adrian Kingston
Collections Information Manager, Digital Assets and Development
Museum of New Zealand Te Papa Tongarewa
@adriankingston
Crowdsourcing for the Digital Humanities and Cultural Heritage Sector
Victoria University of Wellington, 23 April 2013

3. Wed. Apr. 23.
Worked at Swamp–Cow p[addock] fence. Bulliman took
48 heavy fat ewes at 15/-. In evening Father + I drove
down to Levin No L[icense] Democratic Vote Campaign
committee meeting. Father voted to chair + self
appointed secretary. Discussed campaign.

4. Background
 George Leslie Adkin; Farmer, photographer, geologist, explorer,
archaeologist, ethnologist.
 1 man, 41 diaries, 59 years, Over 21000 days
 Thousands of negatives and prints, some albums
 Initial deadline, launch of @life100yearsago ,a project of
WW100
 Did everything ourselves. We resourced most of this project
with a curator (Kirstie Ross) and a monkey with a keyboard
 Figure out process (imaging, cropping, loading, transcription
guidelines),
 Figure out content (data structure, quirks of Adkin, glossaries
etc.)
 Project? What project?
 Very early days.

5. Process
 Assess album condition
 Photograph album pages
 Crop pages to days
 Create narrative for day
 Load “day” images to EMu “day” narrative
 Transcribe
 Add associated subjects, people, places (from authority files
and controlled vocabularies)
 Add context to narrative entries for month
 Some parts semi-automated, some completely manual; some
need no special skills, others do

6. Received a letter + referee’s report from Dr
Chilton, Editor “Trans[actions of the] NZ
Inst[itute], on my paper on Tararuas = “my
theories based on too slender evidence and
debatable evidence + also in part erroneous (?
GLA). I decided to withdraw the paper as it is
evidently unsuitable for publication in
“Transactions”
http://collections.tepapa.govt.nz/theme.aspx?irn=4294

7. Framework
 Using existing framework; EMu, Collections Online
 CIDOC CRM for building and expressing relationships
 Days are conceptual entities, not physical. Framework allows
for this
 Links to physical entities, diaries, photographs, albums
 Links to people, places, topics
 However, scale of content of really starting to highlight issues of
display in Collections Online.

10. What we’ve learnt
 So much content, so much data
 More than just one man’s story, a huge data source on NZ life
 So much potential for a number of fields of research
 Our existing data structure works really well
 Transcription only one part
 To get most out of the content, need the links, need the rich
conceptual model
 Context needed, or at least useful, for the reader
 Existing display not so hot
 Enlivens the collection, a step beyond just digitisation and
transcription

12. Issues
 Size of the project is daunting, but the transcription seems
manageable to do through crowdsourcing
 There are a number of existing platforms that look great, but
how to deal with matching to our structure, vocabularies,
authorities?
 Could use automated in text authority mining, but would need
to then match back to authorities and structure
 Beyond scope of crowdsourcing? But does that diminish the
value of the “data”?
 Could come later though, are we getting too hung up on
quality?

14. Our potential crowd
 By starting it ourselves, we have some content available to
promote the crowdsourcing.
 Already had unsolicited volunteers
 The content is interesting: NZ history, early 20th Century
courtship, farming, geology, religion, war, politics, weather…
 Horowhenua locals interested in local history, and one of their
famous sons
 History students and educators
 Bring students closer to primary material, work with cursive
handwriting, highlight the importance of accuracy in relation to
data, personal biography
 Learning history through a first hand account
 Plan B is do war years with interns

15. We decided to go into town to lunch so I piloted
the party to Kirkcaldie + Stains where we had a
good dinner… Will wanted to know if one could
have all the courses for 2/-. I told him it was not
customary to indulge in more than six but that if
he wanted to tackle the lot we would have to
leave him at it. Olive ordered dishes she did not
want + Alice also got a bit mixed up.
http://collections.tepapa.govt.nz/theme.aspx?irn=4095

16. Where to
 Can’t do with existing (human) resource
 Transcription only one part of the project
 Need to figure what parts need to be crowdsourced, what can’t
 Transcription will enable the adding the contextual and semantic
relationships and links to other sources
 Options for automating the above
 Or, with a focussed crowd and a finite project, maybe we don’t need
a new platform, could provide training and use existing tools
 Can’t crowdsource the display platform. Or can we? Crowdfund it?
 Make data available for analysis, visualisation, research, fun
 Need to formalise the project
 Lots to figure out

17. In evening rode down to see Maud – showed
her some books but there seemed to be a lack
of sympathy between us + the evening was a
failure.
http://collections.tepapa.govt.nz/theme.aspx?irn=4080

18. See
 Adkin diaries of Collections Online
 @adkin_diary on Twitter
 @life100yearsago on Twitter
Questions?
 Kirstie Ross, Curator Modern New Zealand
 Adrian Kingston, Collections Information Manager
 Philip Edgar, Manager Digital Collections and Access