Moving forward our shared data agenda: a view from the publishing industry ICSTI, March 2012.
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Transcript of Moving forward our shared data agenda: a view from the publishing industry ICSTI, March 2012.
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Moving forward our shared data agenda: a view from the publishing industry
ICSTI, March 2012
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Data and the Scientific Article
Researchers perceive data sets as “important, but hard to access”
Publishing Research Consortium, 2010Researchers, N = 3824
Important, but hard to access
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Overview: Data & the Scientific Article
• Current approaches• Thoughts for the future
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Supplementary Material
• Authors can upload Supplementary Material with their paper
Pro’s• Coupling of data and article• Peer review• Citation mechanism• Preservation (byte-wise)
Con’s• Limited data type support• Compatibility (format support)• Limited capacity• Data not centrally stored
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Connecting with Data Repositories, 1
Link to CCDC database(indicates that information for thisarticle is available)
Screenshot of journal article on ScienceDirect (http://dx.doi.org/10.1016/j.jfluchem.2009.07.015)
Article Linking example: CCDC
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Connecting with Data Repositories, 2
... clicking on the CCDC logo takes the reader to a page at the CCDC repository with data related to the article
Screenshot of information page at CCDC (Cambridge Crystallographic Data Centre)
Article Linking example: CCDC
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Connecting with Data Repositories, 3
Tagged Genbank entry(genetic sequence)
Screenshot of journal article on ScienceDirect (http://dx.doi.org/10.1016/j.biortech.2010.03.063 )
Entity Linking example: Genbank Accession Number
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Connecting with Data Repositories, 4
... clicking on the linked Genbank accession code takes the reader to an information page on the NCBI data repository about that specific genetic sequence
Screenshot of information page at NCBI (National Center for Biotechnology Information)
Entity Linking example: Genbank Accession Number
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Connecting with Data Repositories, 5
Database Subject Type of Linking
CCDC Crystallography Article-level
PANGAEA Earth Sciences Article-level*
EMBL Molecular Interactions Chemistry Entity, tagging
Molecular INTeraction DB Chemistry Entity, tagging
Genbank Nucleotides Entity, tagging
UniProt Proteins Entity, tagging
Protein Data Bank Proteins Entity, tagging
ClinicalTrials Medicine Entity, tagging
TAIR (Arabidopsis) Model organism Entity, tagging
Mendelian Inheritance in Men Genetics, inheritance Entity, tagging
*: with Application
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The Article of the Future
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Discovery and Use via SciVerse Applications
Use information from SciVerse and the web
Support for rich user interfaces
Integrated directly into the online article
Simple to build using Content and Framework APIs
Open standards (Apache Shindig, Open Social)
Features & Benefits
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Discovery and Use via SciVerse Applications
•Give me your data, my way…
Openness and Interoperability
•Know who I am and what I want…
Personalization
•The right contacts, at the right time…
Collaboration and trusted views
Libraries can become focal point for applicationsResearchers can save time and improve their information discovery process
“Apps interacting with results are very important to help save time…”
Specific information can be targeted by applications to facilitate content mining and speed up the search time, utilising more time for analysis.
“what faculty is really after is something that ties this altogether, so its all in one place…”
Applications assist researchers to extract all information – content, data, figures etc. to a single analysis source which can be on a local database at the customer’s institute.
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Applications example: NCBI Genome Viewer Scans the article and builds list of sequences based on NCBI accession numbers tagged in the article View/analyze sequence data from genes in the article using NCBI Sequence Viewer See specific information about each strand; zoom in/out; export data
Screenshots of journal article on ScienceDirect (http://dx.doi.org/10.1016/j.ygeno.2007.07.010)
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Applications example: PANGAEA Document identifier sent to PANGAEA data repository for earth sciences PANGAEA returns map plotted with locations where cited data was collected Push-pins open with details of dataset and direct link to data on PANGAEA.de
Screenshots of journal article on ScienceDirect (http://dx.doi.org/10.1016/S0377-8398(01)00044-5)
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Elsevier Enables Content Mining
CONTENT
Customers may:
Run extensive searches and use locally loaded content for text mining purposes for their own research.
Perform extensive mining operations on subscribed content . Structuring input text Deriving patterns within the structured
text Evaluation and interpretation of the
output.
Extract semantic entities from Elsevier content for the purpose of recognition and classification of the relations between them
Integrate results on a server used for the customer’s own mining system for access and use by its researchers through the customer’s internal secure network.
Enabling developers who wish to design and implement applications to analyse our content, or test applications as part of their research within Elsevier content
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Our Content Mining Solution Suite
CONTENT DELIVERYSEARCH &
WORKFLOWSOLUTIONS
ANALYSIS
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Current initiative overview
◦ Supplementary Material◦ Linking to Data Repositories◦ Presentation via Article of the Future◦ Discovery and Use via SciVerse Applications◦ Empower scientists to mine content and use locally
***************************◦ Data store (600 terrabytes as present)◦ Executable papers◦ Workflow tools◦ Etc.
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Conclusions: some thoughts for the future
RESEARCHERS
FUNDERSPUBLISHERS
INSTITUTIONS
Need for aligned strategies and policies, sustainable business models, and concerted collaboration