bhl technical director's report, mar. 2014

BHL Technical Director’s Report

William Ulate

New York Botanical Garden March 10, 2014

22.00

40.00

84.86 94.6

105.85

120.09

132.86

9.2 16.4

31.8 35.4 38.9 41.9 42.8

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20

40

60

80

100

120

140

Oct-08 Oct-09 Oct-10 Oct-11 Oct-12 Oct-13

Pages (Millions) and Volumes (in Thousands) included in BHL

Volumes (K)

Pages (M)

More Online Content

Technical Group at MBG

Mike Lichtenberg Developer

Trish Rose-Sandler Data Analyst

William Ulate Technical Director

Technical Support

MBG IT Division • Manage servers, systems and

telecommunications. • Installs software needed And others: • MBL • Internet Archive • BHL-Australia • BHL-Europe

Technical Advisory Group

Technical Support

• BHL-Australia

• BHL-Europe

• MBL

Projects

• Global Names

• Art of Life

• Purposeful Gaming

• Digging into Data

Scientific Name Extraction • TaxonFinder algorithm in production since

2008 – More than 100 million candidate name strings

– More than 1.5 million unique, verified names

– Available through UI, APIs, Data Exports & Internet Archive

• New collaboration with Global Names project – Improved algorithm, better precision & recall

– More data with TaxonFinder and Neti Neti!

– http://gnrd.globalnames.org/

Taxon Names

BEFORE Name Instances 101,591,803 101,288,804 Unique Names 7,498,554 7,464,924 Verified Names 1,905,507 1,902,803 EOL Names 63,130,350 62,963,582 EOL Pages 13,579,868 13,532,684 AFTER Name Instances 151,222,182 150,066,425 Unique Names 29,246,382 29,091,767 Verified Names 10,153,165 10,109,540 EOL Names 87,791,695 87,135,089 EOL Pages 15,466,713 15,342,867

Article-level metadata

Chapter-level metadata

Treatment-level metadata

Part-level metadata

Articles in the BHL UI

See also:

Related Titles

Art of Life

Art of Life

Art of Life

Art of Life

Art of Life

Art of Life

Macaw

https://github.com/cajunjoel/macaw-book-metadata-tool

Reviewing Metadata

Reviewing Metadata

Manually built:

1,714 sets

89,457 images

Purposeful Gaming

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OCR Improvements

• Gaming

• Transcription

OCR Improvements • Transcription

• Purposeful Gaming

• Looking at…

– Crowdsource Markup

Purposeful Gaming DIGITALKOOT

• Joint project run by the National Library of Finland and Microtask to index the library's enormous archives so that they are searchable on the Internet for easier access to the Finnish cultural heritage.

.

Purposeful Gaming DIGITALKOOT

• Launched on Feb 8 2011, nearly 110 000 participants completed over 8 million word fixing tasks by Nov 29 2012

• DigiTalkoot enabled volunteers to participate in this fixing work by playing games.

• .

Purposeful gaming and BHL: engaging the public in improving and

enhancing access to digital texts

• IMLS Grant Program: National Leadership Grants for Libraries

• Partners: – Missouri Botanical Garden – Harvard University – Cornell University – New York Botanical Garden

• P.I.: Trish Rose-Sandler, Missouri Botanical Garden • Dates: Dec 2013 – Nov. 2015

Project objectives and benefits

• Test new means of crowdsourcing to support the enhancement of content in BHL

• Demonstrate if digital games are an effective tool for analyzing and improving digital outputs from OCR and transcription

• Benefits of gaming include: – improved access to content by providing richer and more

accurate data; – an extension of limited staff resources; and – exposure of library content to communities who may not

know about the collections otherwise.

OCR Improvements

German text interpreted by the OCR process as:

“unb auf ben ©elnrgen be6 fublic{)en”

OCR Improvements

Different resulting texts from parsing the phrase: “und auf den Gebirgen des südlichen Deutschlands”

(“and on the mountains of southern Germany”)

IA OCR OCR 2 Transcription

1

Transcription

2

1 unb und und und Ok

2 den ben den den Ok

3 ©elnrgen ©ebirgen Bebirgen Gebirgen X

4 be6 des de5 des Chk

5 fublic{)en fublichen Füdlichen Südlichen X

6 £)eittfc{)(anb6 Deutfchlanbs Deutfchlands Deutschlands X

Purposeful Gaming

Currently…

• Evaluating Transcription Tools…

• Setting up the Workflow for

iDigBio’s aOCR Hackathon

• Improve OCR parsing of labels with clear metrics (datasets, output formats, scoring algorithm)

• Libraries of regular expr. to clean up each field (different error correction for latitude/longitude coordinates than personal names or herbarium catalog numbers)

• Tool for classifying segments of the image before submitting to OCR

• Do a first pass of OCR to clean images before sending them to a second, 'real' pass of OCR

iDigBio’s CITScribe Hackathon

1. Interoperability betweenpublic participation tools and biodiversity data systems,

2. Transcription quality assessment/quality control (QA/QC) and the reconciliation of replicatetranscriptions,

3. Integration of optical character recognition (OCR) into thetranscription workflow

4. User engagement

NfN & iDigBio’s CITScribe Hackathon

• Jason Best’s DarwinScore

• Ben Brumfield’s Handwriting Gibberish Detector

• Dictionaries to improve crowdsourcing consensus (e.g., names of collectors, scientific names)

• Word Clouds created using n-gram scoring, faceting, and Solr for indexing + Carrot2 for specimen selection (visualize and explore of the use with a word of interest from the word cloud) and a data cleaning step (highlight infrequent words by the system).

NESCent EOL-BHL Research Sprint

There is no place like home: Defining “habitat” for biodiversity science Robert D. Stevenson UMass Boston, Dept. of Biology, 100 Morrissey Blvd., Boston, MA 02125-3393 Carl Nordman (Natureserve) and Evangelos Pafilis Hellenic Centre for Marine Research, P.O. Box 2214, Heraklion, 71003, Crete, Greece

NESCent EOL-BHL Research Sprint

Assessing Risk Status of Mexican Amphibians Through Data Mining. Esther Quintero and Bárbara Ayala National Commission for Knowledge and Use of Biodiversity (CONABIO) and Anne Thessen Marine Biological Laboratory and Arizona State University

Planning for global change: using species interactions in conservation Nicole F. Angeli, Emma P. Gomez, Margot A. Wood, Applied Biodiversity Sciences Program, Texas A&M University, College Station, Texas nangeli1@jhu.edu Tweet me @auratus_nicole and Javier Otegui University of Colorado-Boulder

There is no place like home: Defining “habitat” for biodiversity science Robert D. Stevenson UMass Boston, Dept. of Biology, 100 Morrissey Blvd., Boston, MA 02125-3393 Carl Nordman (Natureserve) Evangelos Pafilis Hellenic Centre for Marine Research, P.O. Box 2214, Heraklion, 71003, Crete, Greece http://epafilis.info/ , vagpafilis@gmail.com

Evolution in the usage of anatomical concepts in the biodiversity literature

Todd Vision (tjv@bio.unc.edu), Prashanti Manda (manda.prashanti@gmail.com), and Dongye Meng (dmeng@cs.unc.edu)

University of North Carolina at Chapel Hill

NESCent EOL-BHL Research Sprint

Evolution in the usage of anatomical concepts in the biodiversity literature Todd Vision (tjv@bio.unc.edu), Prashanti Manda (manda.prashanti@gmail.com), and Dongye Meng University of North Carolina at Chapel Hill

Some preliminary observations…

• Our API seemed to work fine

• Access via a taxon (or a group), for example: “I want to harvest all pages with names from this taxon (Chordata) or this common name (Vertebrate)”.

• Groups started getting results after 2.5 days.

• The structure of BHL was explained so researchers could understand the title, item, page and part levels and define what they wanted. Ex: one group was looking for terms in the titles and the parts’ titles.

• Some others said they would Harvest the OCR from IA although they will not be able to harvest the text on a page by page granularity (only item level).

NESCent EOL-BHL Research Sprint

There is no place like home: Defining “habitat” for biodiversity science Robert D. Stevenson UMass Boston, Dept. of Biology, 100 Morrissey Blvd., Boston, MA 02125-3393 Carl Nordman (Natureserve) and Evangelos Pafilis Hellenic Centre for Marine Research, P.O. Box 2214, Heraklion, 71003, Crete, Greece

Mining Biodiversity

Mining Biodiversity

• Mining Biodiversity: Enriching Biodiversity Heritage with Text Mining and Social Media

• One of the international projects that won in the third round of the 2013 Digging Into Data Challenge

• Promote the development of innovative computational techniques to apply into big data in the humanities and social sciences – The National Centre for Text Mining (UK) – Missouri Botanical Garden (US) – Dalhousie University's Big Data Analytics

Institute (Canada) – Social Media Lab (Canada)

MiBIO: Mining Biodiversity

1. Automatic error correction of OCR text errors.

2. Crowdsource annotation of legacy texts with semantic metadata.

3. Adapt text mining techniques to extract terminology, entities and significant events automatically and to track terminology evolution over time.

4. Use Interactive visualization techniques to help users manage search results through next generation browsing capabilities, assisted by a semantic similarity network of important terms and entities.

5. Design of a social media layer, serving as an environment for diverse users to interact and collaborate on science, public education, awareness and outreach.

MiBIO: Mining Biodiversity

•

Crowdsource Markup

Display text Species Profile Model category

General/summary TaxonBiology

Geographic range Distribution

Habitat Habitat

Food sources and feeding behavior TrophicStrategy

Physical description (general) Description

Physical description (detailed morphology) DiagnosticDescription

Visit to NaCTeM, Feb. 17, 2014

NaCTeM’s Biodiversity- relevant tools

ANNNOTATION PLATFORM

Remote Processing Workflows processed on remote machines. No attendance needed

Workflows GUI for creating single-flow and multi-branch workflows

Workflow Designer

User Interaction Annotation Editor allows for making changes while processing

Annotator/Curator W

eb S

erv

ice

Third-party applications

Processing Components Data (de)serialisation, search engines, NLP, NER, etc.

Developers

Workflows view

Processes View

Documents view

Workflow editor

Workflow as a Web service

Workflow as a Web service

http://argo.nactem.ac.uk/test/services/webservice/314

INPUT

OUTPUT

NAMED ENTITY RECOGNISERS AND NORMALISERS

✔

✔ ✔

✔

✔

Automatically recognised named entities

Linking to external dictionaries

Species and habitat recognition

EVENT EXTRACTORS

Events: associations between entities

SEMANTIC SEARCH

TERM EXTRACTION

Dalhousie SocialLab’s Netlytic.org

http://miningbiodiversity.com/ http://miningbiodiversity.org/

Thank you William Ulate BHL Technical Director

Missouri Botanical Garden

william.ulate@mobot.org

Skype: william_ulate_r