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What's New?

To download, go to the link and click the Raw button.
The March 23, 2016 recording includes the most recent discussion (primarily) focused on term definitions.
March 28, 2016 recording, term definitions and possible ontology alignment.


Problem Statement and Use Case

For a given dataset, it is difficult to find the tools that can be used to work with the dataset. In many cases, the information that Tool A works with Dataset B is somewhere on the Web, but not in a readily identifiable or discoverable form. In other cases, particularly more generalized tools, the information does not exist at all, until somebody tries to use the tool on a given dataset.

Thus, the simplest, most prevalent use case is for a user to search for the tools that can be used with a given dataset. A further refinement would be to specify what the tool can do with the dataset, e.g., read, visualize, map, analyze, reformat.

  • Note that the Energy Cluster is actually looking for this kind of tool. (See Rahul.)

Proposed Solution

Often, whether a tool is likely to work with a dataset can be inferred through simple rules. For example, knowing that a data is available in netcdf/CF1 and is on a lat/long grid is typically sufficient to infer the data can be viewed through Panoply. Secondly, the problem lends itself to crowdsourcing: once one user has found a given tool to be usable with a given dataset, this holds true for all users, and so the information should be promulgated.

We propose the construction of RDF triples that record the fact that a tool works with a particular dataset. It would be based on a simple ontology, with minimal information about the dataset (enough to uniquely identify it and present it as an option in a user interface). There would be slightly more information captured for the tool. A simple user interface would allow a user to select a dataset or paste in a unique dataset identifier.


  • Tools can be either downloadable tools or online services
  • Datasets should be identifiable either through GCMD DIF ID or DOI.
  • Reformatted data and reformatting services (WCS, OPeNDAP) should be considered in compatibility.
  • A simple User interface should provide the ability to search for tools compatible with a certain dataset
  • Users should be able to see a brief description of the tool.
  • Users should be presented with a website for the tool in the search results.
  • A simple mechanism should be provided for authoring the RDF links. (This does not mean they will author RDF directly in, say, TTL or XML. They might do so through simple hashtags).
  • The "system" should be able to do some simple inferencing.


Random Notes

Relationship to Servicecasting

This could be an underlying infrastructure for generating service casts...


There are three kinds of inferences that can greatly cut down the cost of authoring the RDF.

  1. For tools based on netcdf-java, the likelihood of usability can often be inferred from availability in netCDF or OPeNDAP and presence of CF-1 coordinates. Note that this is not an ironclad guarantee however.
  2. Many data collections have "homeomorphic" siblings: datasets with the same or similar variables and data format. For example, AIRH2RET, AIRS2RET and AIRX2RET are AIRS Level 2 datasets that all have the same variables (roughly) and data structure and format. Usability for one in a given tool strongly implies usability for a sibling dataset.
  3. Some tools by their nature are NOT suited to an entire class of datasets, such as GrADS for mapping Level 2 data.

Tool Scripts

  1. Some tools are actually scripts written to work within other tools. An example of this is the opengrads cookbook, which contains scripts for reading and working with certain data collections in the GrADS tool.

Implementation Plan


  • TBD

Per ESIP Winter 2013 Meeting:

  1. Continue identifying tools that could be included and describing pertinent characteristics
  2. Identify collections that could be used as test cases
  3. Adjust SADL and CMAP representations of ToolMatch models as they evolve
  4. Coordinate with ESIP Energy Cluster as they are working on similar efforts
  5. Identify next steps in joint telecons with the Energy Cluster & other interested parties
  6. Create a plan for realistic implementation to be demonstrated at ESIP Summer mtg 2014



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