Riding the wave - Paradigm shifts in information access
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Riding the Wave - Paradigm shifts in Information Access
Jan Brase, DataCiteeResearch Australiasia ConferenceNovember 9thMelbourne
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Thousand years ago: science was empirical
describing natural phenomena
Last few hundred years: theoretical branch
using models, generalizations
Last few decades: a computational branch
simulating complex phenomena
Today: data exploration (eScience)
unify theory, experiment, and simulation
Jim Gray, eScience Group, Microsoft Research
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Science Paradigms
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Scientific Information is more than a published article or a book
Libraries should open their cataolgues to this non-textual information
The catalogue of the future is NOT ONLY a window to the library‘s holding, but
A portal in a net of trusted providers of scientific content
Consequences for Libraries
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We do not have it
BUT
We know where you can find
And here is the link to it!
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German National Library of Science and Technology• Architecture• Chemistry• Computer Science• Mathematics• Physics• Engineering technology
Global Supplier for scientific and technical documents
Financed by Federal Government and all Federal States• € 18 mio. annual acquisition budget• 18,500 journal subscriptions• 7,0 mio. items
TIB
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Simulation
Simulation
Scientific FilmsScientific Films
3D Objects 3D Objects
Text Text
Research Data Research Data
Software Software
Including non-textual content
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https://getinfo.de/app
Query for „SAFOD“
„Potter peninsula“
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Make more scientific and technical content searchable
Develop tools to address each type of scientific and technical Information
Present systems are designed to handle text formats
Move beyond text - Tools
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Example from architecture
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content based indexing
visual search
Indexing and search
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classification of floor types machine learning
> content based indexing > visual search
segmentation with form-primitives
extraction of room connectivity graphs
3D sketchattributed graph
result visualization
How it works
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Table with reaction scheme
2a-i: Derivates from the reaction
Chemical structure
Reaction scheme
Chemical Names
Linked entities from the table
Extracting the information from the text
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Chemical search
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Content based search
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Visual Search in Time series• Query-by-Example, Query-by-Sketch
• Visual Catalog as result list
• Colormaps for the indication of similarity
Visual search approch
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Data
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Problem with data: The research trajectory
analysed
synthesised
interpreted
are
become Information
is
published
becomes Knowledge
Publication
… is accessible
… is traceable
… is lost!Data
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Digital Object Identifiers (DOI names) offer a solution
Mostly widely used identifier for scientific articles
Researchers, authors, publishers know how to use them
Put datasets on the same playing field as articles
DatasetYancheva et al (2007). Analyses on sediment of Lake Maar. PANGAEA.doi:10.1594/PANGAEA.587840
URLs are not persistent
(e.g. Wren JD: URL decay in MEDLINE- a 4-year follow-up study. Bioinformatics. 2008, Jun 1;24(11):1381-5).
DOI names for data
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High visability of the data
Easy re-use and verification of the data sets.
Scientific reputation for the collection and documentation of data (Citation Index)
Encouraging the Brussels declaration on STM publishing
Avoiding duplications
Motivation for new research
What if data would be citable?
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How to achive this?
Science is global• it needs global standards• Global workflows• Cooperation of global players
Science is carried out locally• By local scientist• Beeing part of local infrastrucures• Having local funders
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Global consortium carried by local institutions
focused on improving the scholarly infrastructure around datasets and other non-textual information
focused on working with data centres and organisations that hold data
Providing standards, workflows and best-practice
Initially, but not exclusivly based on the DOI system
Founded December 1st 2009 in London
DataCite
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• TIB begins to issue DOI names for datasets
• Paris Memo-randum
• DataCite Asso-ciation founded in London
• 7 members
• 12 members• All members
assigned DOIs• Over 800,000
items registered• Pilot projects with
Data Centres
06.1105 03.
0906.10
12.09
• 15 members
• Over 1,2 million DOI names
• Metadata store
03
• DFG funded project with German WDCs
History
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Technische Informationsbibliothek (TIB)Canada Institute for Scientific and Technical Information (CISTI), California Digital Library, USAPurdue University, USAOffice of Scientific and Technical
Information (OSTI), USALibrary of TU Delft,
The NetherlandsTechnical Information
Center of DenmarkThe British LibraryZB Med, GermanyZBW, GermanyGesis, GermanyLibrary of ETH ZürichL’Institut de l’Information Scientifique
et Technique (INIST), FranceSwedish National Data Service (SND)Australian National Data Service (ANDS)
Affiliated members:Digital Curation Center (UK)Microsoft ResearchInteruniversity Consortium for Political and Social Research (ICPSR) Korea Institute of Science and Technology Information (KISTI)
DataCite members
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Carries
International DOI Foundation
DataCite
MemberInstitution
Data CentreData CentreData Centre
MemberInstitution
Data CentreData CentreData Centre
… Works with
Managing Agent(TIB)
Member
AssociateStakeholder
DataCite structure
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Act as DOI registration agency
Actively involved in developing standards and workflows CODATA-TG, STM, ICSTI, Data citation index
Central portal allowing access to the metadata from all registered objects. (OAI)
ISI, Scopus, Microsoft Academic search
Community for exchange of all relevant stakeholders in the area access to and linking of data (data centers, publishers, libraries, research organisation, science unions, funders)
DataCite‘s main goals
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Over 1,300,000 DOI names registered so far
DataCite Metadata schema published (in cooperation with all members) http://schema.datacite.org
DataCite MetadataStore
http://search.datacite.org
DataCite in 2011
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DataCite Content Service
Service for displaying DataCite metadata
Different formats (BibTeX, RIS, RDF, etc.)
Content Negotation (through MIME-Typ)
• Access through DOI proxy (http://dx.doi.org)
• First implemented by CNRI and CrossRef:
Alpha available:
http://data.datacite.org
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Examples
curl -L -H "Accept: application/x-datacite+text" "http://dx.doi.org/10.5524/100005"
Li, j; Zhang, G; Lambert, D; Wang, J (2011): Genomic data from Emperor penguin. GigaScience. http://dx.doi.org/10.5524/100005
curl -L -H "Accept: application/rdf+xml" http://dx.doi.org/10.5524/100005
RDF-file
curl -L -H "Accept: application/raw" http://dx.doi.org/10.5524/100005
=> ?
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IRD
( gr av/ 10 cm 3)
Sand
( %)
CaCO3
( %)
TOC
( %)
Radio
( %/ sand)
Smect
( %/ clay)
IRD
( gr av/ 10 cm 3)
Sand
( %)
CaCO3
( %)
TOC
( %)
Radio
( %/ sand)
Smect
( %/ clay)
IRD
( gr av/ 10 cm 3)
Sand
( %)
CaCO3
( %)
TOC
( %)
Radio
( %/ sand)
Smect
( %/ clay)
IRD
( gr av/ 10 cm 3)
Sand
( %)
CaCO3
( %)
TOC
( %)
Radio
( %/ sand)
Smect
( %/ clay)
IRD
( gr av/ 10 cm 3)
Sand
( %)
CaCO3
( %)
TOC
( %)
Radio
( %/ sand)
Smect
( %/ clay)
PS1389-3 PS1390-3 PS1431-1 PS1640-1 PS1648-1
Age (kyr) max. : 233.55 kyr PS1389-3ff
0.0
100.0
200.0
0 20 0 100 0 15 0 0. 5 0 50 0 100 0 20 0 100 0 15 0 0. 5 0 50 0 100 0 20 0 100 0 15 0 0. 5 0 50 0 100 0 20 0 100 0 15 0 0. 5 0 50 0 100 0 20 0 100 0 15 0 0. 5 0 50 0 100
54° 0' 54° 0'
54°30' 54°30'
55° 0' 55° 0'
55°30' 55°30'
11°
11°
12°
12°
13°
13°
14°
14°
15°
15°
World vector shore lineGrain size class KOLP AGrain size class KOEHN2Grain size class KOEHNGeochemistryGrain size class KOLP BGrain size class KOLP DIN20 m
Scale: 1:2695194 at Latitude 0°
Source: Baltic Sea Research Institute, Warnemünde.
Earth quake events => doi:10.1594/GFZ.GEOFON.gfz2009kciu
Climate models => doi:10.1594/WDCC/dphase_mpeps
Sea bed photos => doi:10.1594/PANGAEA.757741
Distributes samples => doi:10.1594/PANGAEA.51749
Medical case studies => doi:10.1594/eaacinet2007/CR/5-270407
Computational model => doi:10.4225/02/4E9F69C011BC8
Audio record => doi:10.1594/PANGAEA.339110
Videos => doi:10.3207/2959859860
What type of data are we talking about?
Anything that is the foundation of further reserach
is research data
Data is evidence
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Citation
The dataset:Storz, D et al. (2009): Planktic foraminiferal flux and faunal composition of sediment trap
L1_K276 in the northeastern Atlantic. http://dx.doi.org/10.1594/PANGAEA.724325
Is supplement to the article:Storz, David; Schulz, Hartmut; Waniek, Joanna J; Schulz-Bull, Detlef;
Kucera, Michal (2009): Seasonal and interannual variability of the planktic foraminiferal flux in the vicinity of the Azores Current.
Deep-Sea Research Part I-Oceanographic Research Papers, 56(1), 107-124,
http://dx.doi.org/10.1016/j.dsr.2008.08.009
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We don’t use the Web.
Berners-Lee created the Web as a scholarly communication tool.
Today the Web has changed everything but scholarly communication.
Online journals are essentially paper journals, delivered by faster horses.
But journals and citation are technology of the 18th century
Beyond citation
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Future
Try to measure various kinds of use:• Resolution• Downloads• Mentions• Citations• Other types of linking
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The wave
Growth of Information –
Diversity of media types and formats
User requirements – e. g. :Science 2.0, collaborativenetworks, social media
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A threat?
Information overload is only a problem for manual curation.
Google is not complaining about data deluge—they’re constantly trying to get more data.
The more data you throw, the better the filter gets.
Don’t turn off the taps, build boats.
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It is not only a challenge …
… it is an opportunity
Let us ride the wave together…