1. XMC CAT Among the Stars Yiming Sun Beth Plale Scott Jensen SC11

2. One Degree Imager (ODI) 3.5m Observatory on Kitt Peak, AZ Operated by WIYN Consortium New Detector Technology: Orthogonal Transfer Arrays Extremely Wide Angle Superb resolution: >1 billion pixels Photo credit: NOAO/AURA/NSF. Copyright WIYN Consortium Inc., all rights reserved.

3. ODI Data Challenges ODI Data Subsystem ODI Workflow Subsystem Traditionally ODI Photo credit: NOAO/AURA/NSF. Copyright WIYN Consortium Inc., all rights reserved Archive Astronomer Data Capacitor & HPSS Data too large to be processed on desktop computers XMC Cat Data Engine metadata iRODS

4. ODI Data Requirements Photo credit: NOAO/AURA/NSF. Copyright WIYN Consortium Inc., all rights reserved ODI Workflow Subsystem ODI Data Capacitor & HPSS Produces 1 raw image every 6-20 seconds 2GB per raw image, consists of 64 FITS files ~ 500GB of raw images per night Expected 100~300 images per night +250GB of processed data products Data becomes public after 18 months ODI Data Subsystem XMC Cat Data Engine metadata iRODS

5. Data Subsystem Role in ODI Automation of data and metadata management – Data ingest and archival – Metadata extraction and cataloging – Manages data ownership Data search and discovery – Fast query on metadata attributes – Selection of best suitable master calibration files Assisting workflow orchestration and execution – Invokes calibration planner prior to workflow execution Eliminates callouts and idling CPUs – Stores workflow execution status as provenance – Allows data product review process Future development – Metadata support for Tier2 data products – Support for Faceted Search Local computation resource Data Subsystem Calibration Planner Workflow Subsystem Metadata Workflow plan Raw data + workflow recipe Workflow

6. ODI Metadata Requirements Metadata sources – Headers embedded in FITS and PNG files – Execution logs – Workflow notifications – Guide star configuration files – User comments and quality assessments Metadata for higher-level aggregates – How to minimize repetition? Metadata Type Description PhotometryMetadata regarding light and exposure AstrometryMetadata regarding celestial bodies TelemetryMetadata regarding remote communication and data transmission AssociationRelationship between master calibration data and image data Quality assessment Evaluation of raw image quality using quick look User comments Additional notes Workflow execution recipes Workflow execution details for re- executing the workflow using tweaked parameters