1 / 18

Monash Data Capture Team

Monash Data Capture Team. Monash eResearch Data Capture Program. Agenda. MeRC Data Capture Program – helicopter view MeRC Data Capture Projects (overview) DC6D: Ecosystem Measurements DC6: Climate and Weather DC6C: History of Adoption DC6E: Multimedia Collections and ARROW (Kashgar)

charis
Télécharger la présentation

Monash Data Capture Team

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Monash Data Capture Team Monash eResearch Data Capture Program

  2. Agenda MeRC Data Capture Program – helicopter view MeRC Data Capture Projects (overview) DC6D: Ecosystem Measurements DC6: Climate and Weather DC6C: History of Adoption DC6E: Multimedia Collections and ARROW (Kashgar) DC6A: Biomedical Data Platform (Molecular Biology) EIF019: Metadata Store Infrastructure with LaRDS EIF036: Microscopy Research Datasets DC6F: Data Publication to Interferome Challenges Ahead

  3. MeRC Data Capture Program

  4. researcher driven solutions What do these projects have in common? Collaborate with other institutions work in with research discipline’s existing environment • Data/Metadata Capture • injestion of experimental raw data, derived data or processed data • capturing additional information (metadata) about the experiments • Data Management • recommend solution • modify existing solution to facilitate data editing, searching, sharing • Data Re-Use • integration to Research Master database to provide party and activity information • provide RIF-CS feeds to • ARDC

  5. DC6D: Ecosystem Measurements Key Features • Upload files • Create Collection • Add descriptive metadata • Sharing with colleagues • Publish to ANDS

  6. DC6D: Ecosystem Measurements

  7. DC6: Climate and Weather Key Features • Same as Ecosystem solution except: • Ability to import files deposited on LaRDS.

  8. DC6C: History of Adoption Key Features • Integration of various applications • Automatic creation of Mediaflux collections. • Automatic creation of Confluence Pages. • Automatic publication of data to ARROW

  9. DC6C: History of Adoption

  10. DC6E: Multimedia Collections & ARROW Key Features • Image Management • Audio Management • Image Conversion • Metadata Extraction • Publication of data to ARROW

  11. DC6E: Multimedia Collections & ARROW

  12. DC6A: Biomedical Data Platform

  13. EIF019: Metadata Store Infrastructure with a Large Research Data - Squirrel Key Features • Upload files • Search by Metadata • Create Experiment / Dataset • Add descriptive metadata • Sharing with colleagues • Publish to ANDS

  14. Data/Metadata Capture • Auto-captures images from the Synchrotron’s MX1 and MX2 beam lines, and metadata output from Metaman for storage in LaRDS • Auto-captures crystallography processed data from grid computing with relevant metadata • Configurable/customisation for the capturing of various scientific experimental data and metadata for storage in LaRDS and extensible to integrate into 3rd party systems such as ARROW. • Data Management • Specialised for protein crystallography • Execution of Molecular Replacement processing on grid computing with the input data on LaRDs • Versatile web interfaces for data management • Define custom metadata schema depending on discipline • Improved audit capability • Data Re-Use • Publication of RIF-CS with relevant crystallography information • Publication of metadata to the Protein Data Bank and TARDIS. • Platform specific for protein crystallography data • Ability to turn on/off data feed publication to ANDS • Flexible platform to cater for multi-discipline data Key differences between Metadata Store vs Biomedical project • Biomedical (DC6A) • Metadata Store (EIF019)

  15. EIF036: Optical Microscopy Research Datasets Key Features • Central store for images & metadata • Create Collections • Share data with other researchers • Publish to ANDS

  16. DC6F: Data Publication to Interferome Key Features • Implementation of BASE • Integration of various applications and external data providers. • Enhancement to Interferome query capability. • Sharing of data with other researchers. • Publication to ANDS

  17. Challenges Ahead • Data licencing model to support the publication/distribution of research data and reuse; and protecting the rights of the data owner and the institution • Adoption of solution by researchers, scientists and its community • Reaching the overall target number of data collections publication to ANDS • (currently 30 of 100 data collections) • Operational support for these solution when the program funding ends

  18. Getting researchers to adopt solution • Metadata Store(Squirrel) • Biomedical Platform (TARDIS) • Ecosystem • Measurem’t • Climate & • Weather • Microscopy • Datasets • History of Adoption • Multimedia Collections • Interferome • Considering / Interested Word of mouth has been effective in the promotion of the solutions implemented… • Trialling Solution • Implementing / Implemented

More Related