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The AnIML data standard uses a highly generic XML-based architecture that is engineered to work in any scientific discipline. This standard can grow into new application domains with no need for new software tools.

Its generic architecture lets AnIML handle data from all well-known and frequently used techniques like spectroscopy, chromatography and imaging. But you can also use it for custom or one-off experiments, micro-fluidic chips or special sensors. AnIML makes these techniques equal to the better-known ones in your data system.

Over time, new analytical techniques and their corresponding Technique Definitions will develop. AnIML’s generic approach will let it accommodate these techniques with no need for software modifications or upgrades.

For a more complete technical overview of AnIML, please visit

The Anatomy of AnIML

AnIML uses two logical layers, the AnIML Core and AnIML Technique Definitions. Each is described by an XML Schema, the Core Schema and the Technique Schema.

AnIML Core

The AnIML Core provides a universal container for arbitrary analytical data. This container is very flexible: it accepts name–value pairs, hierarchies and multidimensional data sets to represent actual data. It also gives you mechanisms for organizing your data into samples and experiments. Every AnIML document is an XML file governed by the Core Schema.

AnIML Technique Definitions

To allow data interchangeability, usage of the Core must be constrained. That's where Technique Definitions come in.

A Technique Definition describes how to use the Core to record experiments in a particular scientific discipline. Like a digital blueprint, it defines how your data must be structured and labeled. This description is machine readable: Technique Definitions are simple XML documents, governed by the Technique Schema.

A Technique Definition lets your software discover how to create data files for a given technique. It also serves as a checklist of required data fields. These fields can be marked as either optional or required, allowing a validator tool to verify that all required information about your experiment has been properly captured. This opens up new possibilities for improving your data quality and integrity.


Sometimes, the fields defined in a Technique Definition aren’t sufficient to characterize certain experiments. Perhaps an instrument might be able to measure additional parameters, or users might need to store extra information about a sample. You can accommodate the necessary additional fields with a Technique Extension.  

A Technique Extension defines which fields should be added to a technique and how they should be structured. Because the Technique Extension is a machine-readable XML document, your software can discover these additional fields programmatically. This extends the standard without breaking AnIML’s compatibility with existing applications. 

The urgent Need for
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