Identifying Candidate Papers
We start with a selection of journals from which we will pull any papers that include data from or discussion about one of our missions. Our software scans the full text of all articles from these journals that have recently been added to ADS. If the article contains any of these keywords, our software flags the article for human review:
ACS COS FGS FOC FOS GHRS HSP NICMOS STIS WFPC WFPC2 WFC3 HST ‘Hubble Space’ GOODS HDF HLA HUDF HLA ‘Hubble Legacy Archive’ HFF ‘Hubble Frontier Field’ ‘Hubble Source Catalog’ HSC MAST 10.17909 ‘James Webb’ JWST NIRCam NIRSpec MIRI NIRISS WFIRST ‘Wide Field Infrared Survey Telescope’ ‘Wide-Field Infrared Survey Telescope’ ‘Roman Space’ RST NGRST
Once an article has been flagged, we download a PDF copy and use a full-text search to find any mention of our missions and any relevant data that have been used or referenced. Although the ADS system provides a convenient interface for keyword searches, the full-text search on the downloaded papers ensures that publications are correctly identified even if the ADS full text preview does not contain all of the sufficient information (see Grothkopf & Treumann 2003).
Categorizing the Included Papers
Every paper that includes a legitimate reference to the HST, JWST, or RST missions and/or relevant datasets is then categorized based on the substance of the paper. A paper can fall into any of these categorizations (mutually exclusive):
- Science: Presents original analysis of observations or data/data products to reach a scientific conclusion
- Data-Influenced (new categorization effective 2019—combined with Mention for reporting): Indirectly relies on data or products, but no new analysis of data or use of a data product
- Mention: Mentions mission(s) by name but no new analysis of or reliance on data or data products
- Engineering: Describes the design of the telescope array itself, instrumentation as a whole, or operational software and other ground support systems
- Instrument: Describes the design, calibration, or capabilities of a specific instrument
Some papers only use images from a mission as a visual reference in the form of an overlay image. If the details of the image are not discussed and it does not contribute to the scientific results of the paper, we will include this paper as a Mention, not Science.
Frequently, one or more datasets are re-reduced and re-published. Regardless of whether or not a dataset has been published previously, a paper is considered Science if it demonstrates a new analysis of this data. If a paper cites previously published data, but these data have little impact on the conclusions of the paper, this will be considered a Mention.
Many papers present ground-based follow-up observations of targets previously identified through HST observations. Unless these papers include original analysis of actual HST data, they will be categorized as Data-Influenced. Papers that speak about simulations, future observations, and/or capabilities may also be considered Data-Influenced for active missions.
Assigning Programs, Program Types and Instruments to Publications
Once a paper has been classified as a Science publication, we then determine or verify:
- The specific proposals and datasets/data products that were utilized
- The instrument(s) used in the program
- The authors of the paper and their associated country affiliations
- The investigators on the original proposals
For each paper for which data is not clearly cited, our library and archive teams query the MAST database to attempt to identify the program(s) and dataset(s) that have been used. This step allows an unambiguous identification of the data—valuable information for linking our data products to publications and for evaluating the performance of observing programs. Once the program and dataset identifiers have been established, the original proposals are cross-referenced in order to further categorize the paper as follows:
- GO: At least one author was investigator on the GO proposal that obtained the data.
- AR: There is no overlap between the paper authors and the GO proposal investigators.
- Part: Combination of GO data sets with AR data sets.
Please email the library with any questions or comments about our publications database.