Supporting MIAPA

From Evolutionary Informatics Working Group
Revision as of 11:51, 30 May 2008 by Arlin.stoltzfus@nist.gov (talk) (Knowledge Capture Exercise)
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Overview

Domain scientists with an interest in the archiving and re-use of phylogenetic data have called for a reporting standard designated "Minimal Information for a Phylogenetic Analysis", or MIAPA (Leebens-Mack, et al. 2006). Ideally the research community would develop, and adhere to, a standard that imposes a minimal reporting burden yet ensures that the reported data can be interpreted and re-used. Such a standard might be adopted by

  • pipeline projects that generate phylogenetic data sets for downloading and re-use (e.g., TreeFam, Pandit, Hovergen,PhylomeDB)
  • repositories and databases designed to archive published data (e.g., TreeBase, Dryad)
  • journals that publish supplementary material for phylogenetic studies (e.g., MBE, Systematic Biology)
  • granting organizations that support phylogenetic studies (e.g., NSF)
  • organizations that develop taxonomic nomenclature based on phylogenetic results

Currently MIAPA is hypothetical and aspirational, i.e., no standard has been adopted nor even developed. As a starting point, Leebens-Mack, et al. suggest that a study should report objectives, sequences, taxa, alignment method, alignment, phylogeny inference method, and phylogeny.

The MIAPA concept clearly aligns with the interoperability mandate of the NESCent evolutionary informatics working group, e.g., data re-use (the primary goal of MIAPA) is a desideratum of interoperability. Development of a MIAPA standard could synergize with ongoing projects and long-term goals of the working group. To achieve re-use through compliance with reporting standards, we need to develop technology that makes it easy to comply with the standard, e.g., a nice GUI that makes it easy for users to construct a MIAPA-compliant submission. To support re-use through data-mining or reasoning (on MIAPA-compliant reports), we need a controlled vocabulary, ideally an ontology. Developing such an ontology not only would jump-start the MIAPA project, it also would contribute to our efforts to develop a language to describe Transition Models, and it would represent a step in the direction of our long-term goal of developing a domain-specific language for phylogenetic analysis.

Some thoughts on developing MIAPA

Leebens-Mack, et al. called for further work, attempting to attract attention to this idea in order to stimulate effort. However, there has been no further effort to develop MIAPA. The NESCent evolutionary informatics working group invited Dr. Leebens-Mack to speak at our recent meeting, and there was general agreement with the value of developing a MIAPA standard, and with the importance of ensuring that the interoperability artefacts developed by the group -- nexml and CDAO -- provide a means of MIAPA compliance.

After the working group meeting officially ended, a few members (Arlin, Brandon, Hilmar) began to discuss what the further development of MIAPA would entail (below), and how we could jump-start the project with a knowledge capture exercise (next section).

  1. What it might mean to have an effective MIAPA standard:
    • an explicit (possibly formal) description of the standard, specifying types of data and metadata
    • an explicit conformance policy
    • adoption of a separate data (as opposed to meta-data) representation standard such as nexml or CDAO
    • a controlled vocabulary for data and metadata
    • a file format for MIAPA documents
    • a repository to store MIAPA-compliant entries
  2. What software support might entail
    • interactive software to facilitate creation of MIAPA-compliant documents
    • a relational mapping of the MIAPA standard to be used in repositories
    • a formal taxonomy or ontology of metadata terms
  3. What logistics might be involved in developing and promulgating the standard
    • a working group with external funding
    • a consortium with representatives from data resources, publishers, researchers, and programmers
    • user testing at scientific conferences
    • collaboration with ontology experts at NCBO
    • multiple rounds of revision
    • workshops (to train users) and hackathons (to develop implementations)
  4. What would ease the burden on scientists (i.e., this is the goal behind the "minimal" in MIAPA)?
    • fewer categories of metadata
    • fewer arbitrary restrictions on format
    • familiarity of metadata concepts
    • flexibility in representation
    • software support for annotation
  5. What makes data reusable?
    • standard formats
    • capacity for validation
    • provenance, ideally, provenance that can be traced automatically via external references
    • description of methods sufficient to reproduce results from data

Knowledge Capture Exercise

We imagine a Knowledge-capture-and-user-testing exercise along the following lines of the following experiment described in the abstract of "Fast, Cheap and Out of Control: A Zero Curation Model for Ontology Development" (Good, et al. 2006: File:Good.pdf):

During two days at a conference focused on circulatory and respiratory health, 68 volunteers
untrained in knowledge engineering participated in an experimental knowledge capture exercise.
These volunteers created a shared vocabulary of 661 terms, linking these terms to each other
and to a pre-existing upper ontology by adding 245 hyponym relationships and 340 synonym
relationships. While ontology-building has proved to be an expensive and labor-intensive process
using most existing methodologies, the rudimentary ontology constructed in this study was
composed in only two days at a cost of only 3 t-shirts, 4 coffee mugs, and one chocolate moose.
The protocol used to create and evaluate this ontology involved a targeted, web-based interface.
The design and implementation of this protocol is discussed along with quantitative and qualitative
assessments of the constructed ontology.

Note that it only takes a few t-shirts and coffee mugs to stimulate potential users to log in to a web site and fill out some forms.

Our plan would be to use a conference (ideally, the upcoming 2008 Evolution meeting, though its a bit soon) to gather data and to begin developing infrastructure for a MIAPA standard:

  1. Task 1. develop an initial controlled vocabulary
  2. Task 2. develop and test a web client for interactively constructing MIAPA annotations
    1. Develop the client-side capabilities
      • use an existing cutomizable framework such as Phenote
      • load vocabulary terms from ontologies identified in step 1
      • provide term-completion based on the loaded vocabularies as in Phenote
      • provide slots for specific types of MIAPA annotations
      • provide support for term requests (i.e., user requests a needed term that is not in the controlled vocabulary)
    2. Implement a system to add term requests as provisional classes
    3. carry out a preliminary round of in-house testing and revision to make sure the system works
  3. Task 3. Arrange logistics to deploy the system at the Evolution meeting
    • advertise the exercise
      • send an email to evoldir, to registered participants of the conference, and of the pre-conference Ontology workshop
      • advertise the exercise in person at the Ontology workshop (Todd? Brandon?)
    • assemble a team of problem-solvers to be on call to fix problems during the conference weekend
      • set up a chat for discussions of emerging problems
      • make sure we have a sys admin contact in case of server problems
    • procure rewards (t-shirts, mugs, etc) and make a plan to distribute them at the conference
    • engage online participants in testing and knowledge capture
      • request users to generate MIAPA-compliant annotations for actual or hypothetical data sets
      • provide incentives for the most annotations, or the most new terms
      • provide users with the means to request new terms
      • provide users the means to categorize terms and specify relations

Alternatively, if we can't do this in time for the conference, we could just identify a target group of potential users and go ahead with the same kind of experiment on a longer time-scale. The targeted users might be

  • those that have published a paper with the term "phylogeny"
  • those attending a scientific meeting on phylogenetics
  • those that use a particular archive or piece of software

Follow-up: MIAPA alpha version

  1. Follow up the knowledge capture experiment
    • expert review of the results
    • revisions and additions to ontology
    • proposal of initial version of MIAPA (alpha version)
    • proposal of initial version of file format
    • proposal of initial version of DB schema
    • manuscript describing exercise and result

Further development and promulgation of MIAPA

Supposing that the above experiment is successful and gets some attention, we could move ahead with opening up the development process and involving the research community. The medium-range goal (1 to 2 years) would be to engage the community in developing a beta version of the standard that would support compliant annotation of a majority of phylogenetic analyses. The longer-range goal would be to take the necessary steps to promulgate MIAPA so that it becomes an accepted standard.

MIAPA beta version

  1. Form a consortium
    • Recruit consortium members from diverse constituencies:
      • end-users (the ones who will submit individual reports to repositories)
      • journal editorial boards
      • repository managers
      • pipeline managers
      • software developers
    • Secure funding for consortium operations
    • Implement the infrastructure needed
      • to maintain artefacts (e.g., sourceforge project)
      • for intra-group communication and coordination (email lists, web server, conference calls)
      • for publicity (web server)
  2. Develop beta version of standard
  3. Develop plans for a second round of testing
    • Set a specific milestone for the level of support (e.g., support 75 % of annotations with existing vocabulary)
    • Include testing in several different contexts:
      • mapping the standard to a relational schema in a repository
      • automatically constructing MIAPA-compliant annotations in a pipeline context
      • interactive end-user generation of MIAPA-compliant annotations
  4. Carry out testing
  5. Publish the revised standard

Promulgating MIAPA

  1. develop long-term maintenance plan for standard (decisions, versioning, obsolescence)
  2. develop infrastructure to support long-term maintenance plan
  3. recruit partners to commit to standard