Informatics
of research samples and models are continuously invented. It becomes very difficult to track the entire experiment from hypothesis and methods through to the raw data, to the processed and analysed data to the results to the conclusions to the reports and then to the management decision processes to find and use the information. As data become distributed into cloud reposito- ries it becomes increasingly important to use semantic methods to annotate and be able to relate these data to other scientific information. This is essential for many reasons. If scientists can- not easily find information to use or to share, there is little value to collecting it in the first place. Readily searchable repositories support collabora- tion and minimise unintentional duplication of effort. Links also allow researchers to communi- cate about data without having to send copies of it around by email – and multiple users can create annotations that point back to a common data object even if stored in a cloud repository. “The use of ontologies and hierarchically organised controlled vocabularies is fundamental to help the subject matter experts to find the right informa- tion,” said Jeff Spitzner, President of Rescentris Inc.
http://rescentris.com http://rescentris/cerf/ “Cloud computing and semantic web tech- nologies are now becoming mainstream in leading research organisations and we have been applying these over the past decade to turn data into shared and actionable knowledge.”
Semantic technologies are gaining momentum. Controlled vocabularies, controlled protocols and ontologies will enable scientists, students and other experts to perform scientific knowledge modelling, and logic-based hypothesis checking with signifi- cantly better results. Even simple terms like ‘gene’ and ‘cancer’ mean different things for different kinds of research activities and data types. Use of namespaces helps distinguish between universal properties like pH or temperature, properties that mean different things in different spaces, such as ‘sequence’, which could be DNA bases or the order of treatments, and properties that are specific to one context like ‘activity’, which could refer to the results measured in a specific assay. When cloud- based data is semantically annotated it can be linked back to any other scientific lab data system and provenance (the evidence trail) can be tracked. The impact of semantic web technology in the cloud is significant. Semantic web technology will considerably decrease the need for central ware- houses of information. There will be no need to transfer large amounts of data across networks. This truly enhances collaboration as semantic agents created by scientists would constantly lurk
Drug Discovery World Fall 2011
the internal and external web for information related to a molecule or experiment. Users would be instantly alerted to new data sources and have it automatically categorised, prioritised and sorted based on the rules set by the scientists. “Service is as important as the product itself,” said Megean Schoenberg, Director of Enterprise Software at PerkinElmer. “Scientific research will be accelerated when there is a close contact between scientists, user community and software solution providers.” PerkinElmer recently acquired CambridgeSoft, ArtusLabs and Labtronics.
Building bridges
New initiatives between industry, solution providers and government are developing which show com- mitment to implement the cloud to support cross- functional collaborations. IDBS, a global provider of data management, analytics and modelling solutions, announced this summer that it is leading a stratified medicine consortium to build a UK-wide Cancer Research and Collaboration Platform. This highly secured data solution brings together patient, ‘omic and up-to-date research data to enable cohort selection, scientifically-based data mining and the secure sharing of cohort outcomes. “The Cloud pro- vides that extensible, accessible computing capability which, with strong application security, can provide the necessary Infrastructure-as-a-Service and Platform-as-a-Service systems which will be a feature of tomorrow’s software landscape,” said Chris Molloy, VP Corporate Development, IDBS. It helps clinical-researchers better identify patients by their clinical and genetic profiles and examine the effects of genetics on disease and on disease outcomes – fun- damentally a collaborative effort between clinicians. Hybrid clouds take advantage of the scalability and cost-effectiveness of a public cloud without exposing mission-critical applications and data to third-party vulnerabilities. These cloud offerings will allow individuals to link computing resources across their organisations into a single, high-per- formance, private cloud while providing system administrators the flexibility to set priorities based on business or technical needs. IBM recently announced a High Performance Cloud (HPC) offering that enables clients to manage and priori- tise HPC assets on a global basis while maintaining operations and data securely behind its firewall.
Eureka moments
The cloud stimulates agile collaboration. Instead of disappearing into a black-hole for 18 months and not showing up with any results until the first proj- ect milestone, the remote teams are fully real-time
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