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Tracking Chandra Science Productivity Publication Metrics special thanks to John Bright, Arnold Rots, and Sherry Winkelman (Archive Group) and Mihoko Yukita.

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Presentation on theme: "Tracking Chandra Science Productivity Publication Metrics special thanks to John Bright, Arnold Rots, and Sherry Winkelman (Archive Group) and Mihoko Yukita."— Presentation transcript:

1 Tracking Chandra Science Productivity Publication Metrics special thanks to John Bright, Arnold Rots, and Sherry Winkelman (Archive Group) and Mihoko Yukita (CDO) Paul J. Green (CDO)

2 Which Metrics? PhD dissertations papers citations pages subgroups all publications refereed papers highly cited papers certain journals

3 Chandra Bibliography Database Queries the ADS weekly: Queries the ADS weekly: (Title or Abstract) contains (AXAF OR Chandra OR X-ray) (Title or Abstract) contains (AXAF OR Chandra OR X-ray) Requires additional human scanning, culling, and categorization. Requires additional human scanning, culling, and categorization. Database now current and backfilled. Database now current and backfilled. Allows public searches that link data ←→ literature Allows public searches that link data ←→ literature CXC internal also links to PropDB, allows many statistics to be derived CXC internal also links to PropDB, allows many statistics to be derived Archive Group – A. Rots, S. Winkelman, J. Bright

4 Tabulated Bibliographic Categories Tabulated Bibliographic Categories 1. Presents specific Chandra observations 2. Refers to published Chandra results 3. Predicts Chandra results (could be either astrophysical theory or data extrapolation) 4. Describes instrumentation, software or operations 5. Cannot be classified and any of these FLAGS may accompany the above categories A) Complementary observations A) Complementary observations B) Simulations or Follow-up Analysis B) Simulations or Follow-up Analysis C) Astrophysical theory that explains Chandra results C) Astrophysical theory that explains Chandra results D) Instrument flags (ACIS, HRC, HETG, LETG, HRMA, PCAD, EPHIN) D) Instrument flags (ACIS, HRC, HETG, LETG, HRMA, PCAD, EPHIN) E) Operations E) Operations F) Software F) Software

5 Definition of "Chandra Paper" Presents specific Chandra observations explaining theory, or followup Category 1 + (all, any, none) Category 1 + (all, any, none) Category 2 + (flag A, B, or C required) Category 2 + (flag A, B, or C required) in other words 1 + (2A, 2B, or 2C) in other words 1 + (2A, 2B, or 2C)

6 Currently Available Categories and Variables Science Category Science Category Proposal Category Proposal Category (VLP, LP, GTO, GO, TOO, DDT, CAL) † Exposure Time Exposure Time N papers N papers N citations N citations † These are mutually exclusive definitions in the Chandra databases, e.g., a TOO from a General Observer is not also counted as a GO.

7 SCIENCE CATEGORIES 1. Solar System 1. Solar System 2. Stars and WD 2. Stars and WD 3. WD Binaries and CVs + 3. WD Binaries and CVs + BH and NS Binaries BH and NS Binaries 4. SN, SNR and Isolated NS 4. SN, SNR and Isolated NS 5. Normal Galaxies: Diffuse Emission + 5. Normal Galaxies: Diffuse Emission + Normal Galaxies: X-ray Populations 6. Active Galaxies and Quasars 6. Active Galaxies and Quasars 7. Clusters of Galaxies 7. Clusters of Galaxies 8. Extragalactic Diffuse Emission and Surveys + Galactic Diffuse Emission and Surveys 8. Extragalactic Diffuse Emission and Surveys + Galactic Diffuse Emission and Surveys

8 Proposal Categories Mutually exclusive in the Chandra databases † Mutually exclusive in the Chandra databases † GO GO GTO GTO TOO TOO DDT DDT LP (first defined for Cycle2) LP (first defined for Cycle2) VLP (first defined for Cycle5) VLP (first defined for Cycle5) N.B. V/LP status is optional even over the nominal 300/1000ksec limits. For complete stats, best to tally by exposure time. † e.g., a TOO from a General Observer is not also counted as a GO.

9 Totals by Proposal Cycle PAPERSCITATIONS

10 Totals by Proposal Cycle Includes  Refereed Chandra papers only  Statistics through May 26 2004  Includes all proposal types GO, GTO, TOO, DDT (no CAL) Statistics best for Cycle1 Strong ramp-down, reflected strongly in ksec -1 plots as well

11 Citations per ksec by Cycle How would you know that statistics are best for Cycle1? check linked plot data check totals plots

12 Example of Linked Plot Data # Values for Citations_by-cycle.txt # CycleCitations N_Proposals Cycle1 10401 312 Cycle2 3985 278 Cycle3 474 304 Cycle4 9 258 Cycle5 0 90 Statistics best for Cycle1

13 Totals by Exposure Time Σ(Papers referring to any Chandra Target in an Approved Program) in bins by Total Program Approved Exposure Time Σ(Citations to Papers referring to any Chandra Target in an Approved Program) in bins by Total Program Approved Exposure Time

14 Citations/ksec by Exposure Time with Cycles Appears as if short observations have greatest impact/ksec. Σ N i=1 {(Citations to Targets in each Program)/(Total ksec in Program)}/N

15 Large Projects Have Longer Citation Lag

16 Conclusions Short exposures appear to provide a larger science return per ksec. Short exposures appear to provide a larger science return per ksec. Relative productivity (papers) and impact (citations) of larger projects appears to have a longer latency. Relative productivity (papers) and impact (citations) of larger projects appears to have a longer latency. Some results have large impact but do not produce large N papers or N citations Some results have large impact but do not produce large N papers or N citations


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