The Future of the Journal And Applications in an Open Scientific Ecosystem
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The Future of the Journal And Applications in an Open Scientific Ecosystem

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Vishal Gupta + Anita de Waard at AI Mashup session at ESWC2010

Vishal Gupta + Anita de Waard at AI Mashup session at ESWC2010

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    The Future of the Journal And Applications in an Open Scientific Ecosystem The Future of the Journal And Applications in an Open Scientific Ecosystem Presentation Transcript

    • Elsevier- Open to Accelerate Science The Future of the Journal, and Applications in an Open Scientific Ecosystem Anita de Waard , a.dewaard@elsevier.com Disruptive Technologies Director, Elsevier Labs Vishal Gupta, v.gupta@elsevier.com Head of Developer Programs, Elsevier 7th Extended Semantic Web Conference May 31, 2010
    • Science is made of information... 2
    • Science is made of information... ...that gets created... 2
    • Science is made of information... ...that gets created... ... and destroyed. 2
    • What is the problem? 3
    • What is the problem? 1. Researchers can’t keep track of their data. 3
    • What is the problem? 1. Researchers can’t keep track of their data. 2. Data is not stored in a way that is easy for authors. 3
    • What is the problem? 1. Researchers can’t keep track of their data. 2. Data is not stored in a way that is easy for authors. 3. For readers, article text is not linked to the underlying data. 3
    • Workflow tools to the rescue! 4
    • Workflow tools to the rescue! http://MyExperiment.org 4
    • Workflow tools to the rescue! http://VisTrails.org http://MyExperiment.org 4
    • Workflow tools to the rescue! http://VisTrails.org http://MyExperiment.org http://wings.isi.edu/ 4
    • The Vision Work done with Ed Hovy, Phil Bourne, Gully Burns and Cartic Ramakrishnan 5
    • The Vision Work done with Ed Hovy, Phil Bourne, Gully Burns and Cartic Ramakrishnan All data items created in the lab are added to the workflow system. 5
    • The Vision Work done with Ed Hovy, Phil Bourne, Gully Burns and Cartic Ramakrishnan All data items created in the lab are added to the workflow system. Each item in the system has metadata (including provenance) and relations to other data items added to it. 5
    • The Vision Work done with Ed Hovy, Phil Bourne, Gully Burns and Cartic Ramakrishnan All data items created in the lab are added to the workflow system. Each item in the system has metadata (including provenance) and relations to other data items added to it. When a paper is published, a slice of this information is exposed to the world. It remains connected to its related data item, and its heritage can be traced. Rats were subjected to two grueling tests... see figure 2 for more details (click on figure to see data) 5
    • The Vision Work done with Ed Hovy, Phil Bourne, Gully Burns and Cartic Ramakrishnan All data items created in the lab are added to the workflow system. Each item in the system has metadata (including provenance) and relations to other data items added to it. When a paper is published, a slice of this information is exposed to the world. It remains connected to its related data item, and its heritage can be traced. Rats were subjected to two grueling tests... Applications run on this ‘exposed data’ Rats were subjected to two grueling tests... Rats were subjected to two grueling tests... see figure 2 for more details (click on universe. see figure data) more details (click on 2 for figure to figure 2 for more details (click on see see figure to see data) figure to see data) Some other publisher 5
    • The vision (same thing, now in words): 6
    • The vision (same thing, now in words): 1. All data items created in the lab (including all measurements, graphs, emails, talks: everything!) gets included in a workflow system. 6
    • The vision (same thing, now in words): 1. All data items created in the lab (including all measurements, graphs, emails, talks: everything!) gets included in a workflow system. 2. Each item in the system has a proper set of tags - including identification of provenance and authorship - and relations to other data items. 6
    • The vision (same thing, now in words): 1. All data items created in the lab (including all measurements, graphs, emails, talks: everything!) gets included in a workflow system. 2. Each item in the system has a proper set of tags - including identification of provenance and authorship - and relations to other data items. 3. When a paper is published, a slice of this information is exposed to the world. It remains connected to its related data item, and its heritage can be traced. 6
    • The vision (same thing, now in words): 1. All data items created in the lab (including all measurements, graphs, emails, talks: everything!) gets included in a workflow system. 2. Each item in the system has a proper set of tags - including identification of provenance and authorship - and relations to other data items. 3. When a paper is published, a slice of this information is exposed to the world. It remains connected to its related data item, and its heritage can be traced. 4. Applications run on this ‘exposed data’ universe. 6
    • The vision (same thing, now in words): 1. All data items created in the lab (including all measurements, graphs, emails, talks: everything!) gets included in a workflow system. 2. Each item in the system has a proper set of tags - including identification of provenance and authorship - and relations to other data items. 3. When a paper is published, a slice of this information is exposed to the world. It remains connected to its related data item, and its heritage can be traced. 4. Applications run on this ‘exposed data’ universe. 5. Everything lives in the cloud. 6
    • What is needed to get there? 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights C. Social change: Scientists need to realize they should annotate their work 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights C. Social change: Scientists need to realize they should annotate their work D. Semantic/Linked Data space at the publisher end. 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights C. Social change: Scientists need to realize they should annotate their work D. Semantic/Linked Data space at the publisher end. 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights C. Social change: Scientists need to realize they should annotate their work D. Semantic/Linked Data space at the publisher end. E. Publishing systems that run as application servers. 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly tool builders B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights standards bodies C. Social change: Scientists need to realize they should annotate their work institutes, funding bodies, individuals D. Semantic/Linked Data space at the publisher end. E. Publishing systems that run as application servers. 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly tool builders B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights standards bodies C. Social change: Scientists need to realize they should annotate their work institutes, funding bodies, individuals D. Semantic/Linked Data space at the publisher end. publishers E. Publishing systems that run as application servers. 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly tool builders B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights standards bodies C. Social change: Scientists need to realize they should annotate their work institutes, funding bodies, individuals D. Semantic/Linked Data space at the publisher end. publishers E. Publishing systems that run as application servers. publishers 7
    • What is needed to get there? A. Tools: Workflow tools that work for all science, are scalable, safe, and user-friendly tool builders B. Metadata standards: Standards that allow interoperable exchange of information on any knowledge item created in a lab, including provenance and privacy/IPR rights standards bodies C. Social change: Scientists need to realize they should annotate their work institutes, funding bodies, individuals D. Semantic/Linked Data space at the publisher end. publishers E. Publishing systems that run as application servers. publishers 7
    • Linked Data for Elsevier 10 8
    • Linked Data for Elsevier <ce:section id=#123> 10 8
    • Linked Data for Elsevier this says <ce:section id=#123> mice like cheese 10 8
    • Linked Data for Elsevier said @anita on May 31 2010 this says <ce:section id=#123> mice like cheese 10 8
    • Linked Data for Elsevier but we all know she was jetlagged then said @anita on May 31 2010 this says <ce:section id=#123> mice like cheese 10 8
    • Linked Data for Elsevier immutable, $$, proprietary but we all know she was jetlagged then said @anita on May 31 2010 this says <ce:section id=#123> mice like cheese 10 8
    • Linked Data for Elsevier immutable, $$, proprietary dynamic, personal, task-driven, - open? but we all know she was jetlagged then said @anita on May 31 2010 this says <ce:section id=#123> mice like cheese 10 8
    • Semantic annotation grid 11 9
    • Semantic annotation grid 11 9
    • Granularity Semantic annotation grid collection document claim triple entity 11 9
    • Granularity Semantic annotation grid collection document claim triple entity Moment measure author/editor typesetter/production reader/data minin 11 9
    • Granularity Semantic annotation grid collection document claim triple entity Moment measure author/editor typesetter/production reader/data minin Meansmanual semi-automated automated11 9
    • Granularity Semantic annotation grid collection document claim triple Automated Copy Editing entity Moment measure author/editor typesetter/production reader/data minin Meansmanual semi-automated automated11 9
    • Granularity Semantic annotation grid collection document claim triple Automated Copy Editing entity Moment measure author/editor typesetter/production reader/data minin Reflect Meansmanual semi-automated automated11 9
    • .XMP RDF in all our PDFs: DC + PRISM 12 10
    • Scientific Applications, Open APIs and a New Publishing Ecosystem
    • “ If I were to guess what Web 3.0 is, I would tell you that it’s a different way of building applications… My prediction would be that Web 3.0 will ultimately be seen as applications which are pieced together. There are a number of characteristics: the applications are relatively small, the data is in the cloud, the applications can run on any device, PC or mobile phone, the applications are very fast and they’re very customizable. Furthermore, the applications are distributed virally: literally by social networks, by email. You won’t go to the store and purchase them… That’s a very different application model than we’ve ever seen in computing. ” - Eric Schmidt CEO Google
    • We conducted 3,000 interviews with researchers, librarians and developers
    • Librarian feedback “This is just amazing. What faculty is really after is for something that ties this all together, so it’s all in one place. This makes it really easy for them.”
    • Researcher feedback “Apps (interacting) with results are very important to help save time... apps integrated into article such as the pop-up example is also very interesting…”
    • Developer feedback “Holy ****…you are clearly aware of what the web really looks like, I’m very impressed with that. I haven’t seen anything so far that comes anywhere close to what you have done …I would love to help out in any capacity…” 19
    • Open APIs for applications
    • Developers can gain recognition and revenues
    • Institutions can become focal point for applications
    • Researchers can save time, improve their information discovery process and innovate
    • An ecosystem open to accelerate science
    • App Integration in Science Direct
    • Thank You Anita de Waard