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Table of Contents
External Collaborators
Information on how to become an external collaborator, and a list of active external collaborators with their projects, including start dates and status.
Introduction
This page is the External Collaborators Wiki as referenced in the Apertif Participation and Data Usage Policy document. The External Collaborators Wiki is the system by which details pertaining to ongoing projects based on proprietary Apertif data and by which the project, the scientific or data product contribution of external collaborators is tracked and shared with the Apertif science team.
External Collaborators are described in Section 2.2.3 of the Apertif Participation and Data Usage policy. They agree to abide by the Apertif Publication Policy, the Code of Conduct outlined in Section 8 of the Apertif Participation and Data Usage policy, and the Netherlands Code of Conduct for Research Integrity.
Instructions
Apertif Participants or Builders who wish to support the proposal for an External Collaborator(s) (EC) should first make the EC aware of the Apertif policy documentation.
External collaborators are approved through a written proposal submission to the Apertif Survey Executive (ASE; chair Betsey Adams adams@astron.nl). Submissions should concisely describe the project that will be undertaken, why access to proprietary Apertif data is necessary, what Apertif data products will be used, and what contribution the EC brings to Apertif that is not already available within the Apertif team.
After approval by the ASE, the EC or their Participant/Builder representative
Adding an External Collaborator
External Collaborations are listed in the table below. When adding an external collaboration please follow these instructions:
- Newly approved EC projects must be added to the top of the table (i.e., reverse chronological order).
- An existing row in the table may not be removed. All changes must be captured within the row. If a project has been scrapped,
Strike-through Textmust be used in the relevant row(s). - The following list provides instructions and/or notes for each of the columns of the External Collaborators table:
- Date Added: format yyyy-mm
- External Collaborator(s): This is the person(people) approved by the ASE with the rights as outlined in the Apertif Participation and Data Usage Policy. Include their home institute.
- Title of project: any updates to the proposed title should be listed alongside the original title.
- Short Description: text longer than 50 words should be uploaded as a simple text file. Include link to the EC proposal (either PDF or Overleaf).
- Survey code: indicate on which survey the collaboration is primarily based (SNS/MDS/ARTS).
- Required data products: indicate what proprietary data products are required to undertake this project.
- EC sponsored students/postdocs: External collaborators may have associated students/postdocs: one student or postdoc per defined science project or paper.
- PhD Thesis: Y/N this column indicates whether the project will make up part of a PhD Thesis.
- Apertif Participant/Builder: This is the sponsoring member of the Apertif Science team.
- Status of project: this column must list one of the following indicators of the status of the project.
- “active”: work is ongoing.
- “closed”: work is complete.
- Publications: Use this column to indicate links to publications as a result of the EC. This should be updated upon the acceptance of a publication at the same time as the Apertif Publication Wiki.
- Notes: any other notes.
Apertif External Collaborators Table
General instructions on editing and syntax can be found here. Text files (.txt) files should be gzipped (due to wiki limitations) and uploaded in the wiki:abstracts namespace area (and coded as {{wiki:abstracts:myfilename.txt.gz}}.
| Date Added | External Collaborator | Title | Description | Survey | Required Data | Contribution | Students/ Postdocs | PhD Thesis | Apertif Sponsor(s) | Status | Publications | Notes |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-08 | H. Roberts, J. Darling (CU Boulder) | Finding Imposters in HI Surveys | Use machine learning to identify OH megamasers in HI catalogs. Proposal | SNS/ MDS | HI source catalog | OHM catalog; IR cross-matching to HI sources | n/a | Y | K.M. Hess | ongoing | First paper draft submitted to Apertif builders |
