Tools for Applying the Analytical Information Markup Language (AnIML)
Tuesday, March 4, 2008
1:30 p.m., Room 236

Organizer:

Gary W Kramer, National Institute of Standards and Technology

Speakers:

1:35     Fundamentals of the Analytical Information Markup Language (AnIML)  BURKHARD A SCHAEFER, BSSN Software

2:00     How to Export Legacy Chromatography Data to AnIML  DALE O'NEILL, Agilent Technologies

2:25     Validating AnIML Data Files  GARY W KRAMER, National Institute of Standards and Technology

2:50     Recess

3:05     Using AnIML as a Data Archiving Format in Academia  STUART J CHALK, University of North Florida

3:30     Using AnIML in Regulated Environments  MAREN FIEGE, Waters GmbH

3:55     Open Source Software for AnIML  JAMIE MCQUAY, Scimatic Software

4:20     Native AnIML LCMS Processing and Viewing  MARK F BEAN, GSK

Overview:

ASTM Subcommittee E13.15 on Analytical Data in collaboration with IUPAC Subcommittee on Electronic Data Standards is developing
the Analytical Information Markup Language (AnIML) to provide mechanisms for representing, organizing, and storing analytical result data and metadata from any analytical technique.  Raw, processed, annotated, simulated, and, in some cases, legacy data can be interchanged and archived in AnIML format. Applying software tools to AnIML datasets demonstrates additional power and utility of the AnIML approach.  Because it is based on XML (Extensible Markup Language), AnIML data can be readily manipulated, converted to other formats, and examined using standard XML tools.  Since metadata are included with result data, generic applications can be created that can visualize the data in any AnIML file.  Validating parsers along with digital signature, verification, and data tracking tools can ensure the data and document integrity necessary for the use of AnIML in regulated industries.  Format conversion tools can transform legacy data, such as, Andi and JCAMP-DX datasets, into AnIML format.

This Workshop will examine how relatively simple software tools can enhance the utility of AnIML-formatted data beyond data interchange and archiving while improving the usefulness and availability of analytical result data. Additional information may be found on the AnIML website:
animl.sourceforge.net.