1. How to represent coverage: temporal, spectral, positional Clive Page AstroGrid Project University of Leicester 2003 March 19.

2. Registry properties Registry does not contain definitive information on coverage of any dataset. False positives are not of great concern: at worst they waste some search time. False negatives, however, may fail to locate data needed by the user. Registry never answers “yes” or “no”, only “maybe” or “no”.

3. Typical query Find all datasets which may contain information about objects: –Located in –observed in –between and –... All three of these imply range searches.

4. (1) Coarse-grained Registry One entry per resource or data collection, –E.g. one for whole HST-WFPC2 data archive. –Perhaps only 100 to 1000 entries in total. Should answer questions like: –Is there any HST-WFPC2 field covering –If answer is “maybe” then have to scan the HST archive for more information

5. (2) Fine-grained Registry One entry per observation per instrument. –Perhaps 10^5 to 10^6 entries in whole registry Should answer questions like: –Which HST-WFPC2 fields (if any) cover –May store spatial, spectral, and temporal metadata about each observation. –Can directly retrieve required dataset Much more selective, useful scientifically.

6. Time Simplest representation: for each data resource store the start and end dates of observation (e.g. from FITS DATE- OBS, DATE-END keywords). User’s query may contain range of dates of interest: Registry can easily find all resources for which the ranges overlap. A more complex representation might be needed if: –Single resource has sparse coverage of time axis, e.g. many single observations over a long period of time –User has a long list of dates of interest, e.g. wants to find observations of some periodic phenomenon.

7. Wavelength range Could represent by an enumerated list of attributes, e.g. –Radio, optical, x-ray, etc. But –Bands not very well defined, e.g. where does soft X-ray turn into XUV? –Probably need to subdivide: e.g. near UV, far UV, but where do you stop? –Even with many terms, it does not provide much selectivity for queries.

8. Wavelength representation Proposed solution as for time: for each resource store and wavelengths/frequencies observed, specify values for queries. High selectivity: can even find e.g. neutral hydrogen surveys by specifying suitable ranges. Units need to be agreed: Hertz, metres, electron volts? Inter-conversion is easy.

9. Wavebands – use bitmap? Patricio Ortiz has suggested using a bitmap for wavelength. Observable spectrum covers ~15 decades. –2 bits/decade: 30 bit word bit-mask - 20 bits/decade: 300 bits or 38 bytes. To find matching resources do bit-wise AND of the user’s bitmask with that of each resource.

10. Sky Coverage We should try to handle instrumental archives, with individual pointings, and find which ones match the user’s query. Examples: –HST ~20,000 pointings, each covering 10 sq.arcmin. –XMM-Newton: ~1000 pointings, each 0.2 sq degs. Two-dimensional problem, not as simple.

11. Sky coverage representations Store (RAmin, RAmax, DECmin, DECmax): –Suitable for finding which HST field covered this position. –Not suitable for answering a question as to whether any HST field ever covered this position. Bitmap: –1º resolution  >41,253 pixels, a bitmap of 5k bytes. –OK to represent coverage of all observed fields of a given instrument, inefficient if used for individual fields. List of pixels: –using HTM or HEALPix to convert (RA,DEC)  integer. –OK for single fields, inefficient for a whole collection of data.