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The lessons of SAP are relevant to research, where operational systems supporting business processes likely consume more than two thirds of an informatics portfolio. This poster from the Pistoia Alliance Conference in April 2011 postulates that open source solutions can provide SAP-like agility and cost effectiveness to life science organizations seeking to simplify their research informatics architecture.
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www.pistoiaalliance.org
Thoughts on a Research Platform ArchitectureSimplify your application portfolio so you can focus on innovation
When times get tough, your CIO demands simplification of the portfolio. One approach is application rationalization based on SAP. R&D is different. SAP doesn’t align well to research needs.
However, the lessons of SAP, especially its architecture, are very relevant to research. These learnings have been copied by companies like Oracle to simplify global development IT.
But no such architecture platform exists for research. Fortunately, open source provides a path to achieve the same simplifications in a manner that meet research’s needs for agility and cost effectiveness.
Operational systems supporting business processes likely consume more than two thirds of your informatics portfolio.
Platform Architecture for operational systems
“I’m familiar with open source and love the price.”
BioPharma
“An integrated platform allows me to focus on innovation instead of interoperability issues.”
Vendors Academia
“Horizontal capabilities are available to me. I can focus my energy on building scientific applications and not IT components.”
(delivers business value)
built
on
top
of
Scientific Applications
Vendor App
Vendor App
Vendor App
Business Components
Inventory Management Others…
Information Integration
Reporting
Master Data Management
Process Integration
Messaging ProcessManagement
Application Server
(simplifies business applications & simplifies integration)
BusinessApplications
Foundational Components
Application Server
Messaging
Generic Inventory
Process Management
Reporting
Authoritative Data Services
No need for heavy-weight commercial EJB containers. Open-source application servers are more than sufficient for research. Even Microsoft IIS is good enough.
Apache HTTP Server Apache TomcatRabbitMQ
Our IT systems need to support the increasing externalization of research and enable the plug-and-play of entire systems and processes.
Systems and processes need to be loosely integrated, which is exactly what a messaging component gives you. Messaging also creates a foundation for standardization efforts relating to data interchange.
The open source options are arguably better than the COTS options. Many ESB options also available in open source.
Eclipse BIRT
Lab heads want insight into lab operations including real-time dashboards and historical metrics on throughput and cycle time.
Vendor App Report
Reporting Layer
generate
embeddedreport
query
The primary output of research is data. Research needs authoritative data services to simplify data integration tasks. Pistoia could define lightweight and generic approaches for achieving consistency in approach across all data services.
Does Walmart have an inventory system for books and another inventory system for electronics? Absolutely not!
Global Material Inventory
… into this!
Convert this…
MouseInventory
ReagentInventory
Cell linesinventory
Cell culturesinventory
BiologicsInventory #1
BiologicsInventory #2
CompoundInventory
Other inventories
Animalinventory
Business Rules - Research labs have many business rules that often need to be configurable without requiring IT involvement. Systems can then use the centralized rules to control application behavior.
Workflow - Many research processes can be modeled and executed with a workflow tool that makes process changes easy enough for lab scientists to do it themselves.
Events - Activity monitoring can capture data about process events on the fly and surface it through dashboards in the reporting layer.
Scheduling – Generic scheduling components can help with everything from efficiently computing static schedules to dynamically optimizing the allocation of work to lab resources based on priority
Summary