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Chris Dijkshoorn On the fly collection integration supported by the crowd
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DigiBird: on the fly collection integration using crowdsourcing

Apr 15, 2017

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Page 1: DigiBird: on the fly collection integration using crowdsourcing

Chris Dijkshoorn

On the fly collection integration supported by the crowd

Page 2: DigiBird: on the fly collection integration using crowdsourcing

‣ Crowdsourcing tasks are undertaken in isolation

‣ It takes time to collect data

‣ It demands continuous promotional effort

‣ It is challenging for institutions to incorporate the results of crowdsourcing into their existing infrastructure

Crowdsourcing Challenges

Page 3: DigiBird: on the fly collection integration using crowdsourcing

valorisation project

May 2016 to November 2016

DigiBird project

Chris Dijkshoorn Cristina Bucur Lora Aroyo

Maarten Brinkerink Sander Pietersen Saskia Scheltjens

Page 4: DigiBird: on the fly collection integration using crowdsourcing

Crowdsourced collections

Collections

Crowdsourced metadata

Sounds Artworks Images Videos

Page 5: DigiBird: on the fly collection integration using crowdsourcing

‣ Every institution has its own system

‣ No visibility similar initiatives

DigiBird solution

‣ Create a hub

‣ Provide on the fly integration

‣ Use a shared vocabulary

Challenge 1: Crowdsourcing tasks are undertaken in isolation

Page 6: DigiBird: on the fly collection integration using crowdsourcing

Why use vocabulary terms instead of text?

Page 7: DigiBird: on the fly collection integration using crowdsourcing

Why use vocabulary terms instead of text?

Grote trap

Page 8: DigiBird: on the fly collection integration using crowdsourcing

Thesauri can bridge collection

IOC World Bird List

‣ 33,801 terms

‣ Structured using Simple Knowledge Organization System (SKOS)

‣ (Semi) persistent identifiers

Importance shared vocabulary

Page 9: DigiBird: on the fly collection integration using crowdsourcing

Goals

‣ Make results available on the fly

‣ Provide insights in progress

DigiBird pipeline

Page 10: DigiBird: on the fly collection integration using crowdsourcing

Data retrieval

Request formulation

Data integration

Response formulation

Query filter Merel

Request search Merel

Request parameter Turdus merula

Query concept ioc:Turdus_merula

DigiBird pipeline example: retrieve information about a blackbird

- ===

-

rec ===

dc:creator

creator ===

dc:creator

creator ===

dc:creator

JSON result list SPARQL result list SPARQL result list

Return JSON, JSON-LD, N-Quads or Turtle

JSON result list

Page 11: DigiBird: on the fly collection integration using crowdsourcing

‣ Crowdsourcing relies on voluntary contributions

‣ Unpredictable when people will contribute

How DigiBird helps

‣ Monitor progress

Challenge 2: It takes time to collect data

Page 12: DigiBird: on the fly collection integration using crowdsourcing

‣ Organise events

‣ Market initiatives

DigiBird solution

‣ Generate challenging tasks (2.0?)

Challenge 3: It demands continuous promotional effort

Page 13: DigiBird: on the fly collection integration using crowdsourcing

‣ Data siloes

‣ Trust in data

DigiBird solutions

‣ Provide a way to directly access data

‣ Different output formats

‣ Refine and review contributions (2.0?)

Challenge 4: It is challenging for institutions to incorporate the results of crowdsourcing into their existing infrastructure

Page 14: DigiBird: on the fly collection integration using crowdsourcing
Page 15: DigiBird: on the fly collection integration using crowdsourcing

Monitoring

Species view

Annotation wall

Source code is available

‣ https://github.com/rasvaan/digibird_api

‣ https://github.com/rasvaan/digibird_client

DigiBird website

Page 16: DigiBird: on the fly collection integration using crowdsourcing

‣ Use standardised vocabularies

‣ Get persistent identifiers

‣ Document how to access your data

‣ Realise effort is required to create a mature codebase

‣ Some code does not age well

How to make the life of a programmer easier