![[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Science Paradigms](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Similar to Riding the wave - Paradigm shifts in information access
Similar to Riding the wave - Paradigm shifts in information access (20)
More from datacite
More from datacite (20)
Recently uploaded
Recently uploaded (20)
Riding the wave - Paradigm shifts in information access
- 1. Riding the Wave - Paradigm shifts in Information Access Jan Brase, DataCite eResearch Australiasia Conference November 9th Melbourne
- 4. We do not have it BUT We know where you can find And here is the link to it!
- 6. Including non-textual content Simulation Scientific Films 3D Objects Text Research Data Software
- 10. Indexing and search content based indexing visual search
- 12. Table with reaction scheme Reaction scheme Extracting the information from the text 2a-i: Derivates from the reaction Chemical structure Chemical Names Linked entities from the table
- 13. Chemical search
- 17. Problem with data: The research trajectory analysed synthesised interpreted are become Information is published becomes Knowledge Publication ā¦ is accessible ā¦ is traceable ā¦ is lost! Data
- 24. DataCite structure Carries International DOI Foundation DataCite ā¦ Works with Managing Agent (TIB) Member Associate Stakeholder Member Institution Data Centre Data Centre Data Centre Member Institution Data Centre Data Centre Data Centre
- 33. The wave Growth of Information ā Diversity of media types and formats User requirements ā e. g. : Science 2.0, collaborative networks, social media
Editor's Notes
- Ein Paper aus der Chemie enthƤlt chemische Informationen in unterschiedlichsten Facetten und Formen. So finden sich im Text chemischen Namen, Namen von Reaktionen, Verweise auf Strukturformel in Bilder. Es gibt Tabellen mit Text und chemischer Strukturinformation und graphische Darstellungen von chemischen Strukturen oder Reaktionsschemata. FĆ¼r eine inhaltliche ErschlieĆung mĆ¼ssen daher sowohl Text als auch nicht-textuelle Elemente ausgewertet werden damit chemische Suchportale sowohl Text- als auch Struktursuchen anbieten kƶnnen. Dies ist ein arbeits- und kostenintensiver ProzeĆ, der Ć¼berwiegend von kommerziellen Datenbankanbieter durchgefĆ¼hrt wird. Die Kommerzialisierung der Suchportale konterkariert allerdings die Idee von Open Access Was nĆ¼tzen Open Access Zeitschriften, wenn sie Ć¼ber kostenpflichtige Suchportal recherchiert werden mĆ¼ssen?
- Gerade ForschungsdatensƤtze von Spektren aller Art stellen eine potentielle Quelle von Referenzdaten dar. Aber wie kann man spƤter solche ForschungsdatensƤtze wiederfinden? Aktuelle Spektrendatenbanken wie die frei verfĆ¼gbare Spectral Database for Organic Compounds erlauben die Suche nach ausgewƤhlten Metadaten oder eine inhaltsbasierte Suche durch Angaben von numerischen Peaks Aber was wƤre, wenn man die relevanten Teile eines Spektrums, das man suchen mƶchte, einfach zeichnen kann? Man mĆ¼Ćte nicht mĆ¼hselig irgendwelche Zahlenbereiche von Peaks o.Ƥ. angeben.
- In our current research project āVisual access to research dataā the TIB, the Interactive Graphics Group at the Technical University of Darmstadt and the Fraunhofer IGD we are working on a concept for visual retrieval process. To start a query you just need to sketch line or curve or you can upload similiar datasets. I have mentioned these two query input types as Query-by-Example and Query-by-Sketch before. The search algorithm will then search a special index, based on the original research data. As a result of your visual search you will retrieve a so called Visual Catalog shown here on the slide, where you can study similar curve progressions found in the database. Colormaps indicate the similiarity between your query and the found curve progression. If you find some interesting curve in the visual catalog you just click on the cell to access the underlying datasets.
- Knowledge, as published through scientific literature, is the last step in a process originating from primary scientific data. (Click) These data are analysed, synthesised, interpreted (Click) and we gain information. (Click) The outcome of this process is published (Click) as a scientific article, which is the classical shape of knowledge.(Click) We can access the article in an easy way (Click) We can trace the information in the article (Click) But in todayās practice data are primarily stored in private files, not in secure institutional repositories, and effectively are lost.
- The approach that DataCite is taking ā using DOIs - has some important social benefits. Researchers, authors, publishers are comfortable, understand, and know how to use them. They put datasets on a level playing field with articles.
- Started in 2004 with a DFG funded project lead by TIB and including three World Data Centres (STD-DOI Scientific Technical Data with DOIs)
- Schauen wir von auĆen nach innen. ZunƤchst die ƤuĆeren Rahmenbedingungen: Informationszuwachs (Beispiel chemische Strukturen CAS - 2000: 20 mio Substanzen 2008: 40 mio Substanzen 2009: 50 mio Substanzen, 2010: 56.2 mio. Substanzen Diversifizierung digitaler Wissensobjekte, vernetztes und interdisziplinƤres Arbeiten. All dies fĆ¼hrt zu Informationsflut und zum Information Overload beim Benutzer, d. h. er kann aus den zur VerfĆ¼gung gestellten Informationen nicht mehr den optimalen Nutzen ziehen.