The Exoplanet Orbit Database
The Exoplanet Orbit Database
Author(s): J. T. Wright, O. Fakhouri, G. W. Marcy, E. Han, Y. Feng, John Asher Johnson, A.
W. Howard, D. A. Fischer, J. A. Valenti, J. Anderson, N. Piskunov
Source: Publications of the Astronomical Society of the Pacific, Vol. 123, No. 902 (April 2011),
pp. 412-422
Published by: The University of Chicago Press on behalf of the Astronomical Society of the Pacific
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Accessed: 01/06/2011 11:47
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The Exoplanet Orbit Database
Received 2010 December 20; accepted 2011 February 7; published 2011 April 13
ABSTRACT. We present a database of well-determined orbital parameters of exoplanets, and their host stars’
properties. This database comprises spectroscopic orbital elements measured for 427 planets orbiting 363 stars from
radial velocity and transit measurements as reported in the literature. We have also compiled fundamental transit
parameters, stellar parameters, and the method used for the planets discovery. This Exoplanet Orbit Database includes all planets with robust, well measured orbital parameters reported in peer-reviewed articles. The database is
available in a searchable, filterable, and sortable form online through the Exoplanets Data Explorer table, and the
data can be plotted and explored through the Exoplanet Data Explorer plotter. We use the Data Explorer to generate
publication-ready plots, giving three examples of the signatures of exoplanet migration and dynamical evolution:
We illustrate the character of the apparent correlation between mass and period in exoplanet orbits, the different
selection biases between radial velocity and transit surveys, and that the multiplanet systems show a distinct
semimajor-axis distribution from apparently singleton systems.
Online material: online table
paedia11 and, more recently, the NASA/NExScI/IPAC Stellar
and Exoplanet Database (NStED).12
The first peer-reviewed list of exoplanets with robust orbits
appearing in the peer-reviewed literature was in Butler et al.
(2002). Fischer & Valenti (2005) compiled a comprehensive list
of uniformly calculated orbital parameters and stellar properties for planets orbiting stars monitored by the California &
Carnegie and Anglo-Australian Planet Searches.
Butler et al. (2006) presented orbital and stellar parameters
for the 172 exoplanets with well-determined orbits around normal stars known within 200 pc. At that time, only a handful of
planets had been discovered through the transit method, and the
distance threshold served to distinguish planets orbiting the
brightest and most easily studied stars from more distant planets
around faint stars with ill-determined orbits, such as the planets
discovered by microlensing.
We have maintained and updated the catalog and have expanded it to include additional information, including transit
parameters and asymmetric uncertainties. We have made this
Exoplanet Orbit Database (EOD) available online and developed the Exoplanet Data Explorer to allow users to easily explore and display its contents. This article serves to document
the methodology of the EOD and subject it to peer review. We
anticipate many future upgrades to the EOD, including the addition of fields not currently supported and more thorough documentation of references.
Since the first discovery of exoplanets orbiting normal stars
(Latham et al. 1989; Mayor & Queloz 1995) the number of
known exoplanets has grown rapidly, predominantly through
the precise radial velocity (RV) method. Recently, exoplanet
discoveries via transit have begun to keep pace, and the Kepler
mission to detect transiting planets promises to surpass RV
methods and other methods such as microlensing and direct
imaging have made promising progress. Careful tracking of
the many dozens of discoveries per year has been carried out
by a few groups: most notably, the Extrasolar Planets Encyclo-
Center for Exoplanets and Habitable Worlds, 525 Davey Lab, The Pennsylvania State University, University Park, PA 16803.
Department of Astronomy and Astrophysics, 525 Davey Lab, The Pennsylvania State University, University Park, PA 16803.
Pivotal Labs, 731 Market Street, Third Floor, San Francisco, CA 94103.
Department of Astronomy, University of California, Berkeley, CA 947203411.
Center for Integrative and Planetary Science, University of California,
Berkeley, CA 94720.
Department of Astrophysics, California Institute of Technology, MC 249-17,
Pasadena, CA 91125.
Space Sciences Laboratory, University of California, Berkeley, CA 947207450.
Department of Astronomy, Yale University, New Haven, CT 06511.
Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD
Department of Astronomy and Space Physics, Uppsala University, Box 515,
751 20 Uppsala, Sweden.
Maintained by J. Schneider; see
For the Exoplanet Orbit Database, we have dropped the
200 pc limit from the old catalog and now include all robustly
detected planets appearing in the peer-reviewed literature with
well-determined orbital parameters. We have retained the generous upper mass limit of 24 Jupiter masses in our definition of a
“planet,” for the same reasons as in the catalog: at the moment,
any mass limit is arbitrary and will serve little practical function,
both because of the sin i ambiguity in radial velocity masses and
because of the lack of physical motivation.13 We therefore err on
the side of inclusiveness by admitting the long high-mass tail of
the exoplanet population at the risk of having a few bona fide
brown dwarfs in the sample.
The scope of this Exoplanet Orbit Database is to provide the
highest-quality orbital parameters for exoplanets orbiting normal stars. We are not attempting to provide an encyclopedic presentation of every claimed detection of an exoplanet.14 At
present, we include giant and subgiant stars, because exoplanet
detection methods and measurement uncertainties for these stars
are similar to main-sequence stars. In the future, we may include
other evolutionary states such as hot subdwarfs, white dwarfs,
post-CE binaries, or pulsars. We plan to include astrometrically
discovered planets when they appear in the literature with robust
orbital elements.
Our definition of “robust” is not strictly quantitative. We require that the period be certain to at least 15% (usually corresponding to seeing at least one or two complete orbits);
otherwise, we have applied our judgment regarding whether
both the detection and the orbit are sufficiently secure to warrant
inclusion in the database. We attempt to be conservative in these
evaluations. Our standards for the quality of a radial velocity
curve might be relaxed, for instance, if a given planet transits
or might be tightened if phase coverage is especially poor. In
any case, we strive to avoid including dubious orbits or detections that we may need to revise at a later date. We stress that
this judgment is not necessarily a judgment on the quality of
other groups’ work in general or on the existence of a particular
planet—indeed, we have not included some very real planets
published in our own articles, because their orbital parameters
are not sufficiently well determined to meet the database’s
The 13 Jupiter-mass limit by the IAU Working Group is physically unmotivated for planets with rocky cores and observationally unenforceable, due to
the sin i ambiguity. A useful theoretical and rhetorical distinction is to segregate
brown dwarfs from planets by their formation mechanism, but such a distinction
is of little utility observationally.
This service is admirably provided by the Extrasolar Planets Encyclopaedia.
Since this task becomes more complex as new planet detection methods explore
new dimensionalities of exoplanet observation, we restrict ourselves to orbital
parameters determined spectroscopically or (in the cases of unambiguously
planetary transits) photometrically.
2011 PASP, 123:412–422
We also collect basic information regarding the quality of the
orbital fit, including the number of velocity measurements
made, the rms scatter about the fit, and the resulting χ2 . Finally,
we collect substantial auxiliary information regarding the host
star, including its best measured parallax, mass, and activity levels. We provide references for nearly all quantities, and our
World Wide Web site provides easy links to these refereed
Thus, the EOD provides added value to other compendia of
exoplanet properties in that:
1. It provides a quality cut containing only robust orbital
parameters for clearly detected planets appearing in the peerreviewed literature.
2. It distinguishes derived quantities, such as m sin i from
measured quantities such as period, eccentricity, and RV semiamplitude (the last of which, for instance, is not stored in other
compendia). This allows derived quantities to be recalculated,
for instance, when better stellar masses become available.
3. It provides a suite of stellar and orbital fit parameters, such
as the number of radial velocity observations in the fit, the quality of the published fit, and the mass, projected rotational velocity, and chromospheric activity level of the host star.
4. It links to the underlying radial velocity and photometric
data that generated the orbital fit.
5. It is available on a Web site that provides a powerful and
visually elegant data exploration and visualization tool.
We stress that the heterogenous detection thresholds within
and among the many exoplanet search programs responsible for
the detection and characterization of the known exoplanets
make a sensitive analysis of the global properties of the known
exoplanet treacherous. An obvious example is the very different
properties of the host stars and orbits of planets discovered by
transit versus those discovered by RVs. While this particular
factor can be crudely addressed through use of the DISCMETH
field in the EOD, other factors are less obvious and more difficult to control. A more subtle example is that the cadence and
radial velocity precision achieved on particular targets by the
many telescopes, groups, and techniques varies as a function
of stellar spectral type, as a function of magnitude, and in less
predictable ways. Thus, careful consideration of the many and
often ill-defined selection effects in planet search programs is
crucial when interpreting these data statistically to find astrophysically meaningful correlations or effects.
Our methodology largely follows that of Butler et al. (2006).
We summarize the important points and differences from that
work next.
The EOD and the Exoplanet Data Explorer Table and Plotter are available on
the World Wide Web at
Data type
NAME . . . . . . . . . . . . . . .
STAR . . . . . . . . . . . . . . . .
COMP . . . . . . . . . . . . . . .
OTHERNAME . . . . . .
HD . . . . . . . . . . . . . . . . . . .
HR . . . . . . . . . . . . . . . . . . .
HIPP . . . . . . . . . . . . . . . . .
SAO . . . . . . . . . . . . . . . . .
GL . . . . . . . . . . . . . . . . . . .
RA . . . . . . . . . . . . . . . . . . .
DEC . . . . . . . . . . . . . . . . .
RA_STRING . . . . . . . .
DEC_STRING . . . . . .
V ....................
BMV . . . . . . . . . . . . . . . .
J .....................
H ....................
KS . . . . . . . . . . . . . . . . . . .
PAR . . . . . . . . . . . . . . . . .
UPAR . . . . . . . . . . . . . . . .
PER . . . . . . . . . . . . . . . . . .
UPER . . . . . . . . . . . . . . . .
T0 ...................
UT0 . . . . . . . . . . . . . . . . . .
K .....................
UK . . . . . . . . . . . . . . . . . . .
ECC . . . . . . . . . . . . . . . . .
UECC . . . . . . . . . . . . . . .
UECCD . . . . . . . . . . . . .
FREEZE_ECC . . . . . .
OM . . . . . . . . . . . . . . . . . .
UOM . . . . . . . . . . . . . . . .
TREND . . . . . . . . . . . . . .
DVDT . . . . . . . . . . . . . . .
UDVDT . . . . . . . . . . . . .
MSINI . . . . . . . . . . . . . . .
UMSINI . . . . . . . . . . . . .
A .....................
UA . . . . . . . . . . . . . . . . . . .
TRANSIT . . . . . . . . . . .
DEPTH . . . . . . . . . . . . . .
UDEPTH . . . . . . . . . . . .
UDEPTHD . . . . . . . . . .
T14 . . . . . . . . . . . . . . . . . .
UT14 . . . . . . . . . . . . . . . .
TT . . . . . . . . . . . . . . . . . . .
UTT . . . . . . . . . . . . . . . . .
I ......................
UI . . . . . . . . . . . . . . . . . . . .
UID . . . . . . . . . . . . . . . . . .
R .....................
UR . . . . . . . . . . . . . . . . . . .
AR . . . . . . . . . . . . . . . . . . .
UAR . . . . . . . . . . . . . . . . .
UARD . . . . . . . . . . . . . . .
B .....................
UB . . . . . . . . . . . . . . . . . . .
UBD . . . . . . . . . . . . . . . . .
DENSITY . . . . . . . . . . .
Long Integer
Long Integer
Long Integer
Name of planet
Name of host star
Component name of planet (b, c, etc.)
Other commonly used star name
Henry Draper number of star
Bright Star Catalog number of star
Hipparcos catalog number of star
SAO catalog number of star
GJ or Gliese catalog number of star
J2000 right ascension in decimal hours, Epoch 2000
J2000 declination in decimal degrees, Epoch 2000
J2000 right ascension as a sexagesimal string, Epoch 2000
J2000 declination as a sexagesimal string, Epoch 2000
V magnitude
B V color
J magnitude
H magnitude
K S magnitude
Parallax in mas
Orbital period in days
Epoch of periastron in HJDa−2,440,000
Semiamplitude of stellar reflex motion in m s1
Orbital eccentricity
Eccentricity frozen in fit?
Argument of periastron in degrees
Linear trend in fit?
Magnitude of linear trend in m s1 day1
Minimum mass (as calculated from the mass function) in M Jup
Orbital semimajor axis in AU
Is the planet known to transit?
ðRp =R Þ2
Time of transit from first to fourth contact in days
Epoch of transit center in HJDa −2,440,000
Orbital inclination in degrees (for transiting systems only)
Radius of the planet in Jupiter radii
ða=R Þ
Impact parameter of transit
Density of planet in g cc1
2011 PASP, 123:412–422
TABLE 1 (Continued)
Data type
UDENSITY . . . . . . . . .
GRAVITY . . . . . . . . . . .
UGRAVITY . . . . . . . . .
LAMBDA . . . . . . . . . . .
ULAMBDA . . . . . . . . .
RMS . . . . . . . . . . . . . . . . .
CHI2 . . . . . . . . . . . . . . . . .
NOBS . . . . . . . . . . . . . . .
NCOMP . . . . . . . . . . . . .
MULT . . . . . . . . . . . . . . .
DISCMETH . . . . . . . . .
DATE . . . . . . . . . . . . . . . .
MSTAR . . . . . . . . . . . . . .
UMSTAR . . . . . . . . . . . .
UMSTARD . . . . . . . . . .
SPTYPE . . . . . . . . . . . . .
BINARY . . . . . . . . . . . . .
FE . . . . . . . . . . . . . . . . . . .
UFE . . . . . . . . . . . . . . . . .
LOGG . . . . . . . . . . . . . . .
ULOGG . . . . . . . . . . . . .
TEFF . . . . . . . . . . . . . . . .
UTEFF . . . . . . . . . . . . . .
VSINI . . . . . . . . . . . . . . .
UVSINI . . . . . . . . . . . . .
S .....................
RHK . . . . . . . . . . . . . . . . .
JSNAME . . . . . . . . . . . .
ETDNAME . . . . . . . . . .
SIMBADNAME . . . . .
NSTEDID . . . . . . . . . . .
FIRSTREF . . . . . . . . . .
FIRSTURL . . . . . . . . . .
ORBREF . . . . . . . . . . . .
ORBURL . . . . . . . . . . . .
MASSREF . . . . . . . . . .
MASSURL . . . . . . . . . .
DISTREF . . . . . . . . . . . .
DISTURL . . . . . . . . . . .
TRANSITREF . . . . . .
TRANSITURL . . . . . .
BINARYREF . . . . . . . .
BINARYURL . . . . . . .
Long Integer
log g (surface gravity) of the planet calculated from transit parameters
Projected spin-orbit misalignment
Root-mean-square residuals to orbital RV fit
χ2ν to orbital RV fit
Number of observations used in fit
Number of planetary companions known
Multiple planets in system?
Method of discovery. Has value RV or Transit
Year of publication of FIRSTREF
Mass of host star
Spectral type of host star, not a fully vetted field
Star known to be binary?
Iron abundance (or metallicity) of star
Spectroscopic log g (surface gravity) of host star
Effective temperature of host star
Projected equatorial rotational velocity of star
Mount Wilson Ca II S-value
Chromospheric activity of star as R0HK
Name of host star used in the Extrasolar Planets Encyclopaedia
Name of host star used in the Exoplanet Transit Database
Valid SIMBAD name of host star
ID of host star in NStED
First peer-reviewed publication of planetary orbit
Peer-reviewed origin or orbital parameters
Peer-reviewed origin of stellar mass
Peer-reviewed origin of stellar distance
Peer-reviewed origin of transit parameters
Example of peer-reviewed article mentioning stellar binarity
NOTE.—Fields beginning with U represent uncertainties in the parameter listed before them. Fields beginning with
U and ending with D represent the asymmetric component of these uncertainties, as described in the text. Fields
ending with “URL” contain the World Wide Web’s Uniform Resource Locator to the reference in the corresponding
field ending in “REF.”
The bases for the epoch of transit and periastron passage (JD, HJD, BJD, or others) used in the literature are varied
and occasionally misreported, especially for nontransiting systems. We have recorded the times given in the original
articles, whatever their basis, and plan to report all times consistently in the future. At present, applications requiring
precision to better than several minutes should refer to the TRANSITREF or ORBREF citations.
3.1. Data
The data in the EOD are stored in flat text files, one per planet. Next, we describe each of the fields and how we determine its
value. The names of the fields as used in the database are specified in all CAPS in the text and are summarized in Table 1.
2011 PASP, 123:412–422
We record the published fundamental observables of SB1’s
period (P , stored as PER), semiamplitude (K), eccentricity (e,
stored as ECC), and the time and argument of periastron (T 0 , ω,
stored as T 0 and OM), and their uncertainties. In a few cases of
multiplanet systems for which orbital parameters are not
constant over the span of the observations, we report the osculating elements at the epoch given in the source. We also record
the presence of a linear trend (TREND) and its magnitude
(DVDT), where relevant, and whether the eccentricity was frozen in the orbital fit (FREEZE_ECC). In the case of circular
orbits for which ω is not listed in the literature, we
choose ω ¼ 90°.
We have opted to use these classical SB1 orbital parameters,
rather than using mean longitude at epoch, because they are
more frequently reported in the literature and the latter is
trivially computed from the former. In those cases (especially
for multiplanet systems or transiting systems) where the phase
of a planet is reported as the mean anomaly at epoch, or epoch
of transit center, or in some similar way, we have converted the
quantities to ω and T 0 for consistency. We recognize that for
circular orbits the uncertainty in mean longitude is better behaved than those in T 0 and ω, and we note that the uncertainty
in mean longitude can be estimated from the period uncertainty
and the span of the observations. We plan to incorporate mean
longitude at epoch, transit time predictions, and robust uncertainties for these quantities in the future, but in the meantime,
any application requiring more precision should calculate the
quantity explicitly from the radial velocities or from the source
We have attempted to make the stellar mass measurements as
uniform as possible, with many masses coming from Takeda
et al. (2007) instead of the planet discovery articles. From
the five orbital parameters and these masses, we calculate the
minimum mass m sin i (MSINI) and the orbital semimajor axis
a (A) for every planet, following the methodology of Wright &
Howard (2009) and Butler et al. (2006). Note that because we
often use stellar masses that differ from the discovery article
values, the minimum masses and a values may differ from their
discovery values. In articles where the minimum masses of
planets are given, but not K (for instance, in multiplanet systems where only a dynamical fit is given), we have computed
K from the M , P , e, and M sin i values in the database, for
We report stellar parallaxes (PAR) and coordinates using the
rereduction of the Hipparcos data set by van Leeuwen (2009),
where available, and from discovery articles otherwise.16 Coordinates are stored in the RA and DEC fields as decimal quantities and in RA_STRING and DEC_STRING as sexagesimal
strings. The V and BMV fields contain the V magnitude and
B V color, usually from the Hipparcos catalog (Perryman &
ESA 1997), and JHK S photometry is from the Two Micron All
Sky Survey (2MASS; Skrutskie et al. 2006) (contained in the
fields J, H, and K S , with the latter being distinguished from
the semiamplitude K). For stars not appearing in those catalogs,
the values come from the discovery articles. Chromospheric
In a few cases, we have had to estimate distances directly from stellar parameters; in these cases, we have attempted to be conservative in our error estimates.
activity measurements are from the discovery articles or from
the values listed in Butler et al. (2006) and are stored as Mount
Wilson S values (SHK) and log R0HK (RHK).
Where the literature is not consistent, we use proper names,
Bayer designations, or Flamsteed numbers to identify a star in
the STAR field, where available, because we find those to be
more mnemonic than catalog numbers. We then give priority
to Gliese-Jahreiss (GJ) numbers before HD numbers, and
HD numbers before Hipparcos designations. In cases where
the literature violates this scheme or is inconsistent, we give
an alternative name in the OTHERNAME field. We include
fields in the database for HD numbers, HR numbers, Gliese
numbers (GL), Hippacos number (HIPP), and SAO number.
For Bayer designations we spell out the Greek letter component,
and in all cases we use three-letter constellation abbreviations.
We provide a component name (COMP, i.e., b, c, d, etc.) and
combine the STAR and COMP fields to generate the NAME of
the planet.
As in the case for stellar masses, we attempt to record as
consistent a set of metallicities (FE), effective temperatures
(TEFF), gravities (LOGG), and projected rotational speeds
(VSINI) as possible, relying heavily on the Spectroscopic Properties of Cool Stars catalogs (e.g., Valenti & Fischer 2005) and
studies by the Geneva group (e.g., Santos et al. 2003). In most
other cases these values come from the discovery articles, and
for the host stars of transiting planets, we prefer the log g value
determined with the transit light curve to a value determined
from spectroscopy alone. We have collected spectral types from
discovery articles and SIMBAD17 and store the values in
SPTYPE, although this field is difficult to maintain or check
in a consistent way.
Stars identified as binaries in the literature have the BINARY
flag set to 1. For multiplanet systems we set the MULT flag to 1
and record the number of planets in the NCOMP field.
For planets that transit (for which the TRANSIT field is set to
1), we incorporate data on the period, epoch of transit center
(T t , stored as T T ), impact parameter (b, as B), the square of
the planet-star radius ratio ðRp =R Þ2 (as DEPTH), the time
of transit from first to fourth contact (T 14 as T14), inclination
(i, as I), orbital distance to stellar radius ratio a=R (as AR), and
planetary radius (r, as R). Unlike the SB1 orbital parameters, this set is overdetermined, and we do not calculate any
of these transit parameters from the others (except in cases
where a parameter is not reported, and in no case do we attempt
to calculate values directly from light curves). We also record
the bulk density of the planet (ρ, as DENSITY). Where these
quantities are not published for a transiting planet, we have calculated them from the other parameters for completeness. Since
m sin i is derived including the stellar mass, which may come
from a source other than the reference providing the transit
See http://simbad.u‑
2011 PASP, 123:412–422
parameters, this may cause minor inconsistencies between
the EOD and rigorously calculated values from the discovery
data. We also record the projected spin-orbit misalignment
λ (as LAMBDA, sometimes reported in the literature in terms
of β ¼ λ), as measured by the Rossiter-McLaughlin
effect. We calculate planetary surface gravity (log g as GRAVITY) from the recorded transit parameters and A (using the
formalism of Southworth et al. 2007), and we calculate
UGRAVITY through a formal propagation of errors assuming
no covariances.
In a small number of cases, it is obvious based on the data
presented in planet discovery articles that the orbital parameters
are misreported. In cases where it appears to be a simple typographical error, we have simply corrected the value; in most
cases the problem is a misreported offset to the Julian Date
of the time of periastron passage.
We also record the method of discovery of a planetary system, DISCMETH. At present, this field can take two values: RV
or Transit. So, for instance, HD209458b (which was discovered
in the course of RV surveys and later found to transit) has
TRANSIT ¼ 1, but DISCMETH ¼ `RV0 , while HAT-P-13c
(which is not known to transit and was discovered in the course
of radial velocity follow-up for the transiting planet HAT-P-13b)
has TRANSIT ¼ 0 and DISCMETH ¼ `Transit0 . This allows for some crude corrections to the very different selection
effects of RV and transit surveys in analyses of global exoplanet
properties (e.g., Gaudi et al. 2005; Gaudi 2005).
3.2. Uncertainties
Where possible, we have recorded the uncertainties from the
literature, where they are computed in a nonuniform way.
Where available or trivially computed, we record the quality
of the orbital fit, including the χ2ν (CHI2) and root-mean-square
residuals of the fit (RMS), and the number of RV observations
used in the fit (NOBS).
All uncertainties are stored in fields beginning with a U and
followed by the field name. Thus, the period uncertainty is specified in the field UPER. For those fields where asymmetric uncertainties are commonly found in the literature, we record the
uncertainty field as half of the span between the upper and lower
limits of the uncertainty interval, and we store the asymmetry
in an additional field, which ends in D, as the value of the
upper uncertainty. For instance, the quantity e ¼ 0:5þ0:1
0:2 would
be stored as three fields: ECC ¼ 0:5, UECC ¼ 0:15, and
UECCD ¼ 0:1. For symmetric uncertainties in the eccentricity,
UECCD is undefined (or, equivalently, equal to UECC).
In many cases we have computed quantities from other literature values (e.g., m sin i, GRAVITY, or T 0 for planets where
only T t is given), and we have had to make estimates of the
uncertainties in these quantities. In all cases we attempt to be
conservative in our estimates to avoid the false precision that
can come from a lack of knowledge of the covariance between
quantities when propagating errors. For instance, we have con2011 PASP, 123:412–422
servatively assumed a minimum uncertainty of 5% on all stellar
masses, regardless of the formal uncertainties in the literature, to
account for likely systematic effects (but this may be too conservative, see Torres et al. 2010). In particular, the actual uncertainties in the surface gravities or semimajor axes of transiting
planets may be lower than we report.
3.3. References
We provide references (REFs) for most numbers in the
database. We do this as a simple text sting of the form “First_
Author Year” referring to the article from which we collected
the quantity. For instance, a reference to this article would be
rendered as the string “Wright 2011.” We also provide a
URL to the Astrophysics Data System (ADS) Web page of that
article. In the case of recently announced planets for which an
ADS page is not available, we provide a link to the relevant
peer-reviewed preprint at the arXiv.18 We provide references and URLs for the spectroscopic orbital elements in the
fields ORBREF and ORBURL, respectively. MASSREF and
MASSURL contain the reference for the stellar mass, and
DISTREF and DISTURL refer to the distance to the star.
SPECREF and SPECURL provide a reference for the stellar
parameters such as ½Fe=H and T eff , and TRANSITREF and
TRANSITURL refer to the article from which we have collected
transit parameters. BINARYREF and BINARYURL contain an
example of a reference to the multiplicity of a star for all stars
with BINARY ¼ 1. In cases where we have combined data from
multiple sources, we separate the references and URLS with
semicolons. In the future we will provide references to all of
the quantities in the database, including magnitudes and
We also provide a reference to the first peer-reviewed appearance of each planet in the literature (FIRSTREF and FIRSTURL) for historical use, along with the year of that
reference’s publication (DATE). Care should be taken with this
field, since many planets were first announced as tentative detections in the literature, in conference proceedings, or, in a few
cases, by press release. As a result, this field should not be used
to determine credit or priority for a planet’s discovery, since the
first peer-reviewed article on a planet was not written by its discoverers in a few cases and, in any event, many planets effectively have co-discoverers.19
We provide the names used by the Extrasolar Planets
(SIMBADNAME), and the Exoplanet Transit Database20
(ETDNAME) for cross-referencing purposes.
A thorough, though somewhat out-of-date, compendium of planet discovery
claims is available online at
4.1. The Exoplanet Orbit Database Online
A snapshot of the complete database is available in the electronic version of this article and online21 as a comma-separated
value file. The Web site will be regularly maintained to include
new planets as they are published in the literature. Reports of
errors and omissions are welcome by e-mail at the addresses
listed on the Web site. We anticipate that the incorporation
of new planets may have a modest delay from the date of publication to allow for confirmation that a planet is peer-reviewed,
careful consideration of the robustness of the orbit, and, in some
cases, follow-up or confirming observations.
When using the database or its products in publication, it is
appropriate to cite this article and to include an acknowledgment similar to “This research has made use of the Exoplanet
Orbit Database and the Exoplanet Data Explorer at http://,” as appropriate.
4.2. The Data Explorer
The EOD can be explored and displayed using the Exoplanet
Data Explorer table and plotter.
The Table Explorer allows for the user to dynamically create
a sorted table of planets and selected properties, including a
choice of units and parameter uncertainties. Once a table has
been generated, it may be exported as a custom text file. References are linked to their corresponding URLs; we provide columns for links to SIMBAD, NStED, and Exoplanet Transit
Database; and planets are linked to “one-up” planet pages that
contain all fields and values for a given set of planets. Both
pages as illustrated in Figure 1.
These one-up pages include a link to the publicly available
velocities of each star, stored at NStED, and a plot showing
these published velocities as a function of time or phase (as appropriate), along with a velocity curve generated from the listed
orbital solution. Note that we have not attempted to fit the
velocities and generate our own solution; we solve only for
the velocity offset γ and simply overplot the solution and data.
This serves as a check on the accuracy of our transcription of
orbital elements.
The Plotter Explorer allows for the quantitative fields to be
plotted as scatter plots or histograms, including asymmetric error bars, logarithmic axes, annotated axes, custom axis ranges,
plot symbol sizes and styles, and line widths. It also allows for
additional quantities to be displayed as color-coding of plotted
symbols or symbol sizes and for multiple charts to appear overplotted in different colors (especially useful for histograms).
Plot axes and error bars can be specified with arbitrarily complex formulae using any field in the EOD (see § 5 for a simple
These tables and plots can be performed on any subset of the
database through the use of filters. These filters can be arbitrarily
complex, including restrictions on arithmetically combined
parameters (for instance, one could search for all RV-discovered
planets whose periods are known to better than 5% through the
filter UPER=PER < 0:05 and DISCMETH ¼ `RV0 ) and with
a variety of units (units are accessed with square brackets:
MSINI[mjupiter] or MSINI[g] for grams). Filters and plot
settings can be saved for future use, as described subsequently, so
that plots can be regenerated at a later time with the latest version
of the EOD without rebuilding the plot manually.
Plots can be exported in several formats, including PNG,
SVD, and PDF, and in an arbitrary aspect ratio. We also provide
suggested output settings for presentation-quality plots (e.g., for
PowerPoint) and for publication. Users can then further annotate plots using their own presentation software or download the
data used to generated the plot (through the filter and export
features of the Exoplanet Data Explorer table) and use their favorite plotting software to make a custom plot.
4.3. Implementation of the Data Explorer
The Exoplanet Data Explorer is a Web application that aims
to make data analysis in the Web browser possible, practical,
and accessible. This is accomplished by transferring as much
of the data processing load as possible from the server onto
the user’s browser and by leveraging the latest browser standards (commonly referred to as the HTML 5 standards) to give
users a rich low-latency environment to manipulate the EOD.
The server code is implemented using the Python programming language and exists solely to provide the front-end client
(the browser) access to the underlying data stored on the server
in a SQLite database. The client code is a mix of HTML for
document layout, CSS for document styling, and JavaScript
for program logic. JavaScript, not to be confused with Java,
is a programming language introduced by the Netscape Communications Corporation in 1995 to facilitate the production of
dynamic Web pages; despite many misconceptions, JavaScript
is a full-fledged, mature, object-oriented language capable of
building complex applications.
JavaScript is used to construct the Data Explorer’s rich interactive user interface. Table columns are draggable and sortable,
units and errors can be toggled via drop-down menus, and the
set of available planet properties can be quickly searched to pinpoint the desired property in real time—all of this functionality
is provided by JavaScript. In fact, the interface components
themselves are implemented using a custom JavaScript-driven
graphical user interface framework to allow for a consistent,
customizable, look and feel across browsers. We use a small
number of external libraries; of these, the most important is
the open-source jQuery library,22 which provides a thoughtful
2011 PASP, 123:412–422
FIG. 1.—An example of the table interface (left) and a one-up page (right).
and consistent cross-browser application programming interface
for manipulating HTML elements.
We also use JavaScript to write a custom language parser
based on Crockford’s (2007) implementation of a top-down
operator-precedence parsing algorithm, first described by Pratt
(1973). This parser allows the user to construct and apply arbitrarily complex cuts on the EOD data set using a simple, but
powerful, query language. Since these filters are parsed in
the browser, they can be modified in real time without the delay
commonly associated with queries that must make the round
trip between the browser and server. These filters include support for inline unit conversion and arbitrary arithmetic, and they
expose the underlying JavaScript math functions—which include, for example, the standard trigonometry functions, logarithms, exponentials, rounding functions, etc. In the table, these
custom filters can be used to constrain the set of exoplanets
shown and to construct new custom planet properties that
can in turn be added as table columns and used in subsequent
filters. In the plotter these custom filters can be used to rapidly
construct plots featuring various data cuts.
The plotter uses the relatively modern HTML canvas tag to
implement a fluid, interactive, in-browser plotting environment.
We use multiple canvas buffers to make panning and zooming
the plot as smooth as possible, even when several complex plots
are overlaid on the same figure. The plotter supports customizable scatter plots and histograms—scatter plots, in particular,
can display up to four variables simultaneously: the x and y
coordinates can each be bound to different quantities, as can
the marker colors and scales. Of course, the language parser
used to construct arbitrary cuts can also be used to specify arbitrary quantities to plot and changes to the plot appear in real
time as they are made. All of this plotting functionality is implemented in JavaScript.
2011 PASP, 123:412–422
The HTML canvas tag allows us to export the resulting
plot directly into the common PNG raster format. To support
publication-quality output we also allow for vector export in
the PDF and SVG formats. To make this possible, we implement a secondary SVG, plotting the back end on the client using
the open-source Raphaël JavaScript library.23 When the user
chooses to export to a vector format, the plotter generates a vector copy of the plot off-screen—tweaked to look identical to the
raster canvas version visible on-screen—that is then exported to
the server, where it can be converted to a PDF and sent back to
the browser.
Finally, users can save their plots and tables for later reuse;
these saved plots will automatically update to reflect the latest
version of the EOD when the user returns to the Web site. This is
accomplished without storing any information on the server by,
instead, storing the plots/tables in cookies on the user’s browser.
The benefit here is that we do not need to provide our users with
accounts to store any data on our server. The downside is that
stored plots and tables will only be available in the same browser that the user created them on and will be lost if the user clears
his or her cookies.
One of the most useful added values of the EOD is its distinction between planets discovered through radial velocity and
those discovered through transit. This allows for the worst
inherent selection effects in both methods to be separated.
We illustrate some of the plotting capabilities of the Exoplanet
Data Explorer next, with examples of interesting features in the
FIG. 2.—Semimajor-axis distribution of all planets in the EOD (red) and all
RV-discovered planets (blue). The latter gives a better sense of the true significance of the 3-day pileup compared with longer orbital periods (i.e.,
0:1 < a < 0:5 AU), because the a dependence of the sensitivity of the RV methpffiffiffi
od is weak (∼ a), while the dependence of the transit method sensitivity is
much stronger.
FIG. 4.—Log semimajor-axis distribution of RV-discovered super-Jupiters
(red) and sub-Jupiters (0:1 < M sin i < 1 M Jup ) (blue). The “3-day pileup”
near 0.05 AU does not appear in the super-Jupiter sample. Note that the sensitivity to sub-Jupiters beyond 0.5 AU falls quickly (see Fig. 3), so the apparent
lack of a 1 AU jump in among the sub-Jupiters may be due to lack of sensitivity.
semimajor-axis distribution among the RV-discovered planets.
Many of these features have been explored in the literature,
especially in Wright et al. (2009) and Wright (2009).
Figure 2 shows that the 3-day pileup of close-in planets is
significant in the radial velocity sample and appears over-
whelming in the overall sample, because of the insensitivity
of most transit searches to planets with significantly longerperiod orbits (e.g., Gaudi et al. 2005; Gaudi 2005).
Focus on only the RV-discovered planets allows us to explore
the nature of the mass-period correlation (Fig. 3). Comparison
FIG. 3.—M sin i vs. log semimajor axis for all RV-discovered planets. The
lower envelope illustrates the sensitivity of the highest-precision and longestrunning surveys.
FIG. 5.—Distribution of semimajor axis for all apparently singleton RVdiscovered planets (red) and planets in multiplanet systems (blue). These populations follow very different semimajor-axis distributions.
2011 PASP, 123:412–422
Orbit Database and the Exoplanet Data Explorer. The latter is a
powerful tool for creating figures and plots for professional and
public talks, telescope and funding proposals, educational
purposes in laboratory exercises using authentic data, and the
general exploration of planet and host-star properties. We
will continue to update the database with new planets as they
are discovered and to update the explorer with new
FIG. 6.—Radius vs. mass for the known transiting exoplanets. To illustrate the
versatility of the Exoplanet Data Explorer, in this plot the quantity of mass has
been calculated by the Web browser as m sin i= sin i from the MSINI and I fields
of pthe
EOD, and the uncertainties
have been propagated as σm ¼
m ðσm sin i =m sin iÞ2 þ ðσi = tan iÞ2 using the UMISNI and UI fields. In the
browser, each point is clickable and links to that planet’s one-up page.
of the semimajor axes of super-Jupiters and sub-Jupiters (Fig. 4)
shows that the 3-day pileup is predominantly due to the population of sub-Jupiters and that super-Jupiters are rarely found in
close-in orbits. The lack of an obvious 1-AU “jump” among the
sub-Jupiters could easily be due to the difficulty of detecting
such planets at such large orbital distances.
Figure 5 shows that among the multiplanet systems, the
semimajor-axis distribution is quite distinct: multiplanet
systems are much less likely to include a close-in planet, and
there also does not appear to be a 1-AU jump among the multiplanet systems.
Finally, we illustrate the new transit parameter and uncertainty calculators. Figure 6 shows the radius-mass relation
for the known transiting systems. Here, we have calculated the
true mass of planets by using the I field of the EOD, and the
quantity of mass is then calculated as MSINI[mjupiter]/
sin (I[rad]). We have then chosen to simply propagate the errors in I and MSINI through the error-bar calculator as sqrt((UMSINI[mjupiter]^2+(UI[rad]*
MSINI[mjupiter]/tan (I[rad]))^2))/sin (I
[rad]). More sophisticated formulae would allow for asymmetric errors based on upper and lower limits for I.
We have made our compilation of robust orbital parameters
for all known exoplanets available online through the Exoplanet
2011 PASP, 123:412–422
We would like to thank and acknowledge the tireless work of
Jean Schneider, whose Extrasolar Planets Encyclopedia is an
indispensable reference for all things exoplanetary. While we
have complied every datum in the Exoplanet Orbit Database
(EOD) ourselves from original sources, the Extrasolar Planets
Encyclopedia has been a useful check on our numbers and an
invaluable clearinghouse of every new planet announcement.
We thank the anonymous referee for a quick and constructive
referee’s report that improved this article and the database. Special thanks go to R. Paul Butler, who generated the first peerreviewed catalog of exoplanets, from which the EOD is
descended. We thank Scott Gaudi for helpful suggestions that
improved this article. We also thank the many users of the EOD
and Data Explorers who sent in edits and suggestions. We cannot provide a comprehensive list, but such a list would include
Michael Perryman, Jean Schneider, Ian Crossfield, Subo Dong,
Wes Traub, and Marshall Perrin. We thank Jason Eastman for a
particularly thorough cross-checking of our numbers. We have
made extensive use of the NASA/IPAC/NExScI Star and Exoplanet Database, which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with
the National Aeronautics and Space Administration, and
NASA’s Astrophysics Data System Bibliographic Services.
We thank the NStED administrators (in particular, Stephen
Kane and David Ciardi) for their assistance and support with
the EOD and the Exoplanet Data Explorer for their help checking database numbers, agreeing to cross-link the Web sites, and
especially for checking, archiving, and providing all published
radial velocity data for every exoplanet. This research has made
use of the SIMBAD database, operated at CDS, Strasbourg,
France. This publication makes use of data products from the
2MASS, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California
Institute of Technology, funded by the National Aeronautics and
Space Administration and the National Science Foundation.
This work was partially supported by funding from the Center
for Exoplanets and Habitable Worlds. The Center for Exoplanets and Habitable Worlds is supported by the Pennsylvania
State University, the Eberly College of Science, and the Pennsylvania Space Grant Consortium.
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