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Panels PDF Print E-mail

"How to gain venture capital investments - What you always wanted to ask a VC but never dared to do"

December 2 | 17:00 - 18:00 | Flaming Red

Participants: Hannes Schwetz | Austrian Economic Service (AT), John Brimacombe| Spventures (UK), Mark Greaves | Vulcan (US), Klaus Matzka | gamma capital partners (AT), Aleš Špetič, Zemanta | Suresh Patel, Verdexus

Moderator: William Stevens, Europe Unlimited

VCs discuss the actual market and finance situation for startups and will give practical insides: how to approach VCs! what do they expect from the startups! how are they evaluating proposals! whats the expected relationship VC/startup! how do you select the companies you invest in? if you can choose only one selection criteria for your investments, would it be team, business model or technology?how important are the exit channels? Is semantic web an attractive investment target technology and why - what does it mean for entrepreneurs? Can European investors build attractive semantic web technology companies or must European entrepreneurs go to the US?


"Next steps in intelligent information management in the Pharmaceutical and eHealth domains: Facts and trends."

Panel supported by NeOn

December 3 | 10:00 - 10:45 | Flaming Red

 

Participants: Susie Stephens |Johnson & Johnson, Rudi Studer | AIFB - University of Karlsruhe, Bo Andersson | AstraZeneca, Francisco José Farfán | Hospital de Fuenlabrada, Todor Primov | Ontotext AD

Moderator: Jose Manuel Gomez-Perez | iSOCO

The pharmaceutical industry is one of the business sectors where the data explosion experienced by the global economy in the last years has had a bigger impact. Motivated by the need of safer and more effective medical treatments, means for the analysis of existing literature and its reuse in order to form new concepts and hypotheses have become essential for research on drug discovery.
Along with the size, number, and complexity of drug databases and repositories, investments have considerably increased in these years in order to produce means that harness all such data into knowledge that can be capitalized by the pharmaceutical companies. Key issues to be addressed include dealing with disconnected datasets, addressing heteogeneous nomenclature, which hamper information search and retrieval both for drugs and diseases, and keeping track of the data produced throughout experimental processess for later interpretation of the results and tracing the provenance of the data.
Furthermore, most of these issues are reccurrent also at the opposite end of the drug chain, with direct consequences on patients. Through a combination of technology and standars, healthcare institutions are struggling to address the interoperability problem existing between the different nomenclature used in eHealth systems. However, this is a hard problem and, as a consequence, patient safety is compromised by medication errors occurring both at the prescription and administration stages.
Semantic technologies are having a fundamental role in addressing these problems. This panel brings together experts from the fields of drug discovery, healthcare, and semantic technologies with the twofold goal of analyzing the impact of such technologies in these sectors and assessing ongoing and new challenges to be addressed in the short and mid-term.


"Linked Data in the Enterprise: is it just another hype or does it have real added value for information management"

December 3 | 12:00 - 13:00 | Flaming Red


Participants: Tom Tague | Thomson Reuters,  Leigh Dodds | Talis, Hans-Peter Schnurr | Ontoprise, Richard Cyganiak | DERI Galway, Antanas Kiryakov | Ontotext AD

Moderator: Paul Miller | The Cloud of Data

The concept of Linked Data has grown in significance over the past year or so, and is being actively discussed in research groups and in relation to Government drives for transparency. Enterprise adoption is proving less rapid, and this panel session will address some of the reasons for this before looking at examples of successful adoption from which others might learn.

 

 
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