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Information Systems for Crop and Genebank Data Management at CIP: Tools and Workflow Integration

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22 diapositives · 374 Views · Sep 14, 2014

This document outlines the activities and systems utilized at CIP for managing crop and genebank data. It highlights the integration of tools such as CIPSTATIONS, CIPSTAT, and DIVA-GIS, along with the development of workflows to streamline data capture and analytical processing. The focus is on standardized reporting, software development, and collaboration tools to enhance research informatics. It also discusses future harmonization with ICIS database schemes, project management insights, and performance indicators for effective data management and utilization in research.

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  1. CIP – RIU selected activities Information systems for crop and genebank data management Edwin Rojas, Reinhard Simon ICIS workshop 2006, CIMMYT

  2. The Research Informatics story Research Hypothesis Problematic situation Data capture Data/information management Analytical processing Standardized reports Research informatics Publication for diverse uses/uptake Presentation to CIP annual meeting 2004Reinhard Simon Adopted from: W. Busch:Max und Moritz, 1865

  3. Selected activities • Workflows • CIPSTATIONS • CIPPEX • CIPSTAT • LIMS for molecular marker lab and “quality” lab • CIPTCL • DIVA-GIS • Data warehouse for access and quality control • Software development and collaboration tools • Outlook – harmonization with ICIS database schemes and tools

  4. Workflows • Workflow motor: (Edwin teniamos un slide aqui de esto? Si no – use el siguinte como ejemplo.)

  5. Process: Distribution M S Lab. ADU Scientist ADU GADC SENASA Curator IVU Inv.ADU HQU Application Approve Reject Request Revise If Black Box Prepare Documents . MTA – (designated, no designated) . Permiso de importación . Condiciones fitosanitarias International Distribution Reserve True Seed National Distribution If TrueSeed A Sign MTA Revise Documentation Reserve Tuber If Tubers A Verify Availability B Request Reserve Reserve True Seed Hybrid If Hybrid True Seed If Available A B Request Propgation Supply Plantlets Check ELISA NASH Results If Tubers If no Available A If In-Vitro Plants B Propagated A Send Materials to ADU B If Hybrid True Seed A A Treat Seed Check ELISA NASH Results B Supply Plantlets If cuttings (Only for Ipomoea) Request Export A Request Phytosanitary Certificate B International Distribution A Prepare Documents And Package Receive Phytosanitary Certificate B Nacional Distribution B Send Documents And Package Notify Material Register in Distribution Database + Deliver Material

  6. CIPSTATIONS

  7. CIP databases:passport, charact, eval.data CIP-WorkflowEngine Resource scheduler:MRBS Project and experiment management:PHProject Breeding data:adaptations from ICIS Molecular data:adaptations from Germinate CIPPEX • Based on tool for project management (PHProjekt) • Phenotype data management inspired by ICIS • Genotype data management inspired by GERMINATE

  8. Diagram of the Experimental Design & Analysis Generator Module for the CIP-PEX System Input parameters Experimental Map Register Experiment Experimental Design Add Factors Field Book • RCBD • Plot Design • Lattice…. Add Variables Data Capture Central Database Analysis Modules Statistical GIS Dataware House Presentation to CIP annual meeting 2004Reinhard Simon

  9. CIP Mobile/Barcode Infrastructure Status 2005-12 Barcode Pockets LAN Wireless Potato Sweet potato ARTC Areas In vitro Chamber Cold Chamber for Seeds Pending Pending Pending Pending Pending Pending Pending Pending Cold Chamber for Tubers Pending Pending Pending LIMA Greenhouses Pending Pending Pending Pending Pending Pending Field Pending Pending Pending Pending Pending Pending Pending Pending Pending Laboratories (Molecular/Processing) Pending Pending Pending In vitro Chamber Pending Pending Pending Pending Pending Pending Pending Greenhouses Pending Pending Pending Pending Pending Pending Pending JUNIN Design completed (by ITU) Field Pending Pending Pending Pending Pending Pending Storage Room Pending Pending Pending Pending Pending Pending Laboratories Pending Pending Pending Pending Pending Pending Notes: The barcode includes the use of labels, thermal printers and reader guns. The symbol “ – ” means that the specific crop does not are the respective facility. Infrastructure Design for all In vitro & Greenhouse Infrastructure for all In vitro & Lima-Greenhouse Improve Infrastructure and Wireless Covertures (from 11MB to 54 MB) First Pilot in In vitro Potato Applications 2000 2003 January 2003 November 2004 2005

  10. Environment Experiment Data Capture with Mobile Device Central Database

  11. Performance Indicators

  12. CIPSTAT • Web interface for users (via web forms) and software (via WSDL web services) to statistical routines • Statistical routines packaged in a library ‘Agricolae’ written in R • Presently access to 29 routines covering frequently used at CIP for experimental planning and analysis

  13. CIPSTAT – screenshot

  14. CIPSTAT – screenshot Interface for tools via WSDL – e.g. Taverna

  15. CIPPEX – LIMS molecular data

  16. CIPTCL – LIMS for GR In vitro – quality check

  17. DIVA-GIS overview

  18. Data warehouse • MS based solution for genebank and GADC • OS based solution for breeding experiments (and others)

  19. Data warehouse –CIP intranet

  20. Data warehouse – examples from OS solution • Edwin: lista

  21. Software development practices • Use of RUP documents for planning and documentation • Languages: VB/.NET; Java, PHP, R, SAS, (JavaScript, Delphi, Perl, C, C++, Fortran, Python) • Standardized on Eclipse editors for Java, PHP, C, R • (use of Tortoise for CVS access for VB, etc) • Use of CVS and Subversion for all software development • JIRA (Issue management), Confluence (Wiki) • Evaluating: Tools for automating builds and software development quality control

  22. Outlook • Stronger collaboration with ICIS team for better harmonization of tools developed at CIP for potato and sweetpotato data management • Statistical quality control tools for process management • Integration of ontologies for data capture and quality control