Strategies for Adding EML Support to the GCE Data Toolbox for Matlab Wade Sheldon Georgia Coastal Ecosystems LTER (WWW: gce-lter.marsci.uga.edu/lter)

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Strategies for Adding EML Support to the GCE Data Toolbox for Matlab Wade Sheldon Georgia Coastal Ecosystems LTER (WWW: gce-lter.marsci.uga.edu/lter)

Background  Needed universal solution for processing tabular data sets (majority of IM work)  Goals:  Import from various data sources  Standardize units, date formats, attribute names  Assign metadata descriptors  Validate/QAQC  Generate statistical summaries, plots, maps  Export to various data/metadata formats  Support sub-setting & queries, super-setting (unions/joins)  Support automation of all steps  Automatically capture metadata throughout interactive processing

Background  Developed Matlab data structure specification for storing data table tightly coupled with metadata  Developed ‘Toolbox’ (function library) for working with data structures  Many roles in GCE IS:  Primary tool for acquisition, QAQC of data from monitoring network, PI submissions  Data/metadata packaging (linked to RDMS)  Data distribution (flexible formats)  New Role: Automated harvesting/processing/QC/web posting of remote data stores (USGS, NOAA) and post-processing of CSI arrays downloaded via modem  Began public distribution of toolbox in 2002 (primarily for end-user analysis of GCE data)

Toolbox Metadata Standard  Full implementation of FLED (+ user- extensible content)  Attribute-level metadata managed with data  General documentation descriptors stored in simple array format (Category, Field, Value) – designed for pre-formatted metadata, but parseable/updateable  Simple user-editable style definition tables used to produce formatted ASCII metadata

EML Differences  Higher granularity  Hierarchical structure (vs flatter 3-tier)  Different delineation of semantic/numerical attribute descriptors (much overlap, but different philosophy)  New unit dictionary requirements for validation contrary to units/unit conversion conventions (at odds with non-IM end-user focus of toolbox)  XML-based (requires extra steps for presentation)

Strategy  Short term: develop XSLT to convert EML (primarily dataset, entity, attribute) to ASCII headers for importing metadata along with data  Medium term: switch to EML-oriented metadata schema (e.g. use similar arrays, but support direct eml schema mapping by using xpath syntax for category/field info)  Long term: add support for direct caching of EML docs, include native xml routines for syncing metadata during processing (requires more users adopt latest Matlab version - R13)

Significance  Allow IM community take full advantage of these tools/capabilities for their own site’s data with minimal re- mastering (EML + ASCII/Matlab table)  Allow LTER IM community to showcase research- oriented, metadata-driven tools to bolster support for EML efforts immediately  If full EML support achieved, could become a useful mechanism for automatically producing EML- documented/validated data sets (datalogging -> harvest -> process -> QC -> dataset+EML -> validation)