The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

It is now 16 years since the first data release from the Sloan Digital Sky Survey (SDSS; York et al. 2000). This Early Data Release, or EDR, occurred in 2001 June (Stoughton et al. 2002). Since this time, annual data releases from SDSS have become part of the landscape of astronomy, populating databases used by thousands of astronomers worldwide (Raddick et al. 2014a, 2014b), and making the SDSS's 2.5 m Sloan Foundation Telescope (Gunn et al. 2006) one of the most productive observatories in the world (Madrid & Macchetto 2009). This paper describes the 14th public data release from SDSS, or DR14, released on 2017 July 31.

The SDSS has completed three phases and is currently in its fourth phase. SDSS-I and -II conducted a Legacy survey of galaxies and quasars (York et al. 2000), the SDSS-II Supernova Survey (Frieman et al. 2008; Sako et al. 2014), and conducted observations of stars for the Sloan Extension for Galactic Understanding and Exploration 1 (SEGUE-1; Yanny et al. 2009). These surveys made use of the SDSS imaging camera (Gunn et al. 1998) and 640 fiber optical spectrograph (Smee et al. 2013). SDSS-III continued observations of stars with SEGUE-2 and conducted two new surveys with new instrumentation (Eisenstein et al. 2011).

The Baryon Oscillation Spectroscopic Survey (BOSS; Dawson et al. 2013) upgraded the optical spectrograph to 1000 fibers (named the BOSS spectrograph; Smee et al. 2013) to conduct a large-volume cosmological redshift survey which built on the work of both SDSS-II (York et al. 2000) and 2dFGRS (Colless et al. 2003). At the same time, the Apache Point Observatory Galactic Evolution Experiment 1 (APOGEE-1; Majewski et al. 2017) employed a high-resolution near-infrared spectrograph to observe stars in the Milky Way. All of these observations were conducted at APO, and data were publicly released in DR12 (Alam et al. 2015).

This paper contains new data and data reductions produced by SDSS-IV (Blanton et al. 2017). SDSS-IV began observations in 2014 July and consists of three programs.

• 1.  
  The extended Baryon Oscillation Spectroscopic Survey (eBOSS; Dawson et al. 2016) is surveying galaxies and quasars at redshifts $z\sim 0.6\mbox{--}3.5$ for large-scale structure. eBOSS covers a wider class of galaxies than BOSS at higher effective redshifts. In particular, the size and depth of the quasar sample is a huge leap forward over previous surveys. eBOSS will also observe emission-line galaxies, extending the WiggleZ survey (Blake et al. 2011) in the southern sky to a larger sample of galaxies at higher redshifts. Following from eBOSS, the TAIPAN survey (da Cunha et al. 2017) will soon provide a low-redshift complement in the southern hemisphere. All of these surveys will be eclipsed by forthcoming experiments including DESI (Aghamousa et al. 2016a, 2016b), Euclid (Laureijs et al. 2011), and 4MOST (de Jong et al. 2014), which will use new instrumentation to obtain galaxy surveys an order of magnitude larger than ongoing surveys. Two major subprograms are being conducted concurrently with eBOSS:

  • (a)  
    The SPectroscopic IDentification of ERosita Sources (SPIDERS) investigates the nature of X-ray-emitting sources, including active galactic nuclei (AGNs) and galaxy clusters. This contains the largest systematic spectroscopic follow-up sample of X-ray-selected clusters (for details, see Section 4), reaching into a regime where meaningful dynamical estimates of cluster properties are possible for hundreds of massive systems. It contains a highly complete sample of the most luminous X-ray-selected AGNs, which will only be superseded by the spectroscopic follow-up programs of the eROSITA survey (mainly via SDSS-V and 4MOST)
  • (b)  
    The Time Domain Spectroscopic Survey (TDSS; Morganson et al. 2015) is exploring the physical nature of time-variable sources through spectroscopy. The main TDSS program of optical follow-up of variables from Pan-STARRS1 imaging is the first large—by order(s) of magnitude—program of optical spectroscopy of photometrically variable objects, selected without a priori restriction based on specific photometric colors or light-curve character. About 20% of TDSS targets involve repeat spectroscopy of select classes of known objects with earlier epochs of spectroscopy, e.g., searching for variability among known broad absorption line (BAL) quasars, and building and expanding on earlier such programs (e.g., Filiz Ak et al. 2014); a comprehensive description of the latter such repeat spectroscopy programs of the TDSS may be found in MacLeod et al. (2017).
• 2.  
  Mapping Nearby Galaxies at APO (MaNGA; Bundy et al. 2015) is using integral field spectroscopy (IFS) to study 10,000 nearby galaxies. MaNGA builds on a number of successful IFS surveys (e.g., ATLAS-3D, Cappellari et al. 2011; DiskMass, Bershady et al. 2010; and CALIFA, Sánchez et al. 2012), surveying a significantly larger and more diverse samples of galaxies over a broader spectral range at higher spectral resolution. It has finer spatial sampling and a final sample size three times that of the similar SAMI survey (Bryant et al. 2015), and in this release becomes the largest set of public IFS observations available.
• 3.  
  APOGEE/APOGEE-2 perform a large-scale and systematic investigation of the entire Milky Way Galaxy with near-infrared, high-resolution, and multiplexed instrumentation. For APOGEE-2, observations are being carried out at both northern and southern hemisphere locations: the 2.5 m Sloan Foundation Telescope of the Apache Point Observatory (APOGEE-2N; which started Q3 2014) and the 2.5 m du Pont Telescope of the Las Campanas Observatory (APOGEE-2S; from Q2 2017). APOGEE/APOGEE-2 is the only large-scale (>1,000,000 spectra for >450,000 objects) near-IR spectroscopic survey of stars, ensuring it has a unique view of all parts of our Galaxy, unhampered by interstellar obscuration in the Galactic plane. Most stellar surveys of equivalent scale—including those that have concluded (e.g., RAVE, SEGUE-1 and −2, and ARGOS; Steinmetz et al. 2006, Yanny et al. 2009, Rockosi et al. 2009, Freeman et al. 2013), are currently underway (e.g., LAMOST, Gaia-ESO, GALAH, and Gaia; Cui et al. 2012, Gilmore et al. 2012, Zucker et al. 2012, Perryman et al. 2001), or are anticipated in the future (e.g., WEAVE, 4MOST, and MOONS; Dalton et al. 2014, de Jong et al. 2014, Cirasuolo et al. 2014)—have been or will be performed in the optical and/or with largely medium spectral resolution (however, we note plans for high-resolution modes for some of these). All of these projects provide complementary data in the form of different wavelength or spatial regimes providing essential contributions to the ongoing census of the Milky Way's stars.

SDSS-IV has had one previous data release (DR13; Albareti & Allende Prieto et al. 2017; for a "behind the scenes" view of how this is done, see Weijmans et al. 2016), which contained the first year of MaNGA data, new calibrations of the SDSS imaging data set, and new processing of APOGEE-1 and BOSS data (along with a small amount of BOSS-related data taken during SDSS-IV).

DR14 contains new reductions and new data for all programs, roughly covering the first two years of SDSS-IV operations. This release contains the first public release of data from eBOSS and APOGEE-2, and almost doubles the number of data cubes publicly available from MaNGA.

The full scope of the data release is described in Section 2, and information on data distribution is given in Section 3. Each of the subsurveys is described in its own section, with eBOSS (including SPIDERS and TDSS) in Section 4, APOGEE-2 in Section 5, and MaNGA in Section 6. We discuss future plans for SDSS-IV and beyond in Section 7.

As has been the case for all public SDSS data releases, DR14 is cumulative, and includes re-releases of all previously released data processed through the most current data reduction pipelines (DRPs). In some cases, this pipeline has not changed for many DRs (see summary below). New data released in DR14 were taken by the Sloan Foundation 2.5 m telescope between 2014 August 23 (MJD = 56893)¹³⁸ and 2016 July 10 (MJD = 57580). The full scope of the release is summarized in Table 1.

We discuss the data released by each of the main surveys in detail below, but briefly, DR14 includes

• 1.  
  Data from 496 new eBOSS plates covering ∼2480 square degrees observed from 2014 September to 2016 May. We also include data from a transitional project between BOSS and eBOSS called the Sloan Extended Quasar, ELG, and Luminous Red Galaxy (LRG) Survey (SEQUELS), designed to test target-selection algorithms for eBOSS. The complete SEQUELS data set was previously released in DR13; however, DR14 is the first release for eBOSS. The eBOSS data contain mainly LRG and quasar spectra, as well as targets from TDSS and SPIDERS. Twenty-three new eBOSS Emission Line Galaxy (ELG) plates are included in DR14 to test final target-selection algorithms. The full ELG survey started collecting spectra in 2016 September and will be part of a future data release. We include in DR14 the first part of the ELG target catalog (see Table 2) described in Raichoor et al. (2017). Other eBOSS value added catalogs (VACs) are also released, namely (1) the redshift measurement and spectral classification catalog using Redmonster (Hutchinson et al. 2016), (2) the quasar catalog (Pâris et al. 2017b), and (3) a set of composite spectra of quasars binned on spectroscopic parameters (Jensen et al. 2016).
• 2.  
  APOGEE visit-combined spectra as well as pipeline-derived stellar atmospheric parameters and individual elemental abundances for more than 263,000 stars, sampling all major components of the Milky Way. This release includes all APOGEE-1 data from SDSS-III (2011 August–2014 July) as well as two years of APOGEE-2 data from SDSS-IV (2014 July–2016 July). APOGEE VACs include (1) an updated version of the APOGEE red-clump catalog (APOGEE-RC; Pinsonneault et al. 2018) (2) a cross-match between APOGEE and the Tycho-Gaia Astrometric Solution (APOGEE-TGAS; F. Anders et al. 2018, in preparation), and (3) a compilation of four different methods to estimate distances to APOGEE stars (Schultheis et al. 2014; Santiago et al. 2016; Wang et al. 2016; J. Holtzman et al. 2018, in preparation; Queiroz et al. 2018).
• 3.  
  Data from 166 MaNGA plates, which result in 2812 reconstructed 3D data cubes (for 2744 unique galaxies, primarily from the main MaNGA target sample, but these data also include ancillary targets and ∼50 repeat observations). Internally, this set of galaxies has been referred to as MaNGA Product Launch-5 (MPL-5); however, the reduction pipeline is a different version from that internal release. The new data relative to what was released in DR13 were taken between 2015 August 13 (MJD = 57248) and 2016 July 10. The MaNGA release also includes two VACs, which provide spatially resolved stellar population and ionized gas properties from Pipe3D (Sánchez et al. 2016a, 2016b; see Section 6.4.1) and FIREFLY (Goddard et al. 2017; see Section 6.4.2).
• 4.  
  The largest ever number of SDSS VACs produced by scientists in the collaboration—12 in total. See Table 2.
• 5.  
  A re-release of the most current reduction of all data from previous versions of SDSS. In some cases, the DRP has not changed for many DRs, and so has not been re-run. The most recent imaging was released in DR13 (Albareti & Allende Prieto et al. 2017); however, only the photometric calibrations changed in that release; the astrometry is the same as in DR9 (Ahn et al. 2012) and the area released and the other aspects of the photometric reduction remain the same as that in DR8 (Aihara et al. 2011). Legacy Spectra (those observed with the SDSS spectrograph) have also not changed since DR8. There have also been no changes to SEGUE-1 or SEGUE-2 since DR9, or MARVELS since DR12 (Alam et al. 2015). For DR14, we have re-reduced BOSS spectra using the eBOSS pipeline, where flux calibration has been improved by adding new atmospheric distortion corrections at the per-exposure level (Margala et al. 2016) and by employing an unbiased coaddition algorithm.

The DR14 data are distributed through the same mechanisms as DR13, with the addition of a Web application to interactively interface with optical and infrared spectra. We describe our three distribution mechanisms below. These methods are also documented on the SDSS Web site (http://www.sdss.org/dr14/data_access), and tutorial examples for accessing and working with SDSS data can be found at http://www.sdss.org/dr14/tutorials.

The raw and processed imaging and spectroscopic data, as well as the VACs, are available through the Science Archive Server (SAS, data.sdss.org/sas/dr14). Data can be downloaded from the SAS directly by browsing the directory structure, and also in bulk using rsync, wget, and Globus Online (see http://www.sdss.org/dr14/data_access/bulk for more details). The data files available on the SAS all have their own data model, which describes the content of each file in detail. These data models are available at https://data.sdss.org/datamodel.

The processed imaging and optical and infrared spectra on the SAS are also available through an interactive Web application (https://dr14.sdss.org). This Web application allows the user to search for spectra based on specific parameters, e.g., plate, redshift, coordinates, or observing program. Searches can be saved through permalinks, and options are provided to download the spectra directly from the SAS, either individually or in bulk. Previous data releases back to DR8 are available through the same interface. A link is also provided to the SkyServer explore page for each object.

Finally, the DR14 data can be found on the Catalog Archive Server (CAS; Thakar 2008; Thakar et al. 2008). The CAS stores catalogs of the photometric, spectroscopic, and derived quantities; these are available through the SkyServer Web application (http://skyserver.sdss.org) for browser-based queries in synchronous mode and through CasJobs (http://skyserver.sdss.org/casjobs), which offers more advanced and extensive query options in asynchronous or batch mode, with more time-consuming queries able to run in the background (Li & Thakar 2008). The CAS is part of the SciServer (http://www.sciserver.org) collaborative science framework, which provides users access to a collection of data-driven collaborative science services, including SkyServer and CasJobs. Other services include SciDrive, a "drag-and-drop" file hosting system that allows users to share files; SkyQuery, a database system for cross-matching astronomical multiwavelength catalogs; and SciServer Compute, a system that allows users to upload analysis scripts as Jupyter notebooks (supporting Python, MatLab, and R) and run these databases in Docker containers.

In addition to the data, the data processing software used by the APOGEE-2, eBOSS, and MaNGA teams to derive their data products from the raw frames is available at http://www.sdss.org/dr14/software/products.

eBOSS (Dawson et al. 2016) is surveying galaxies and quasars at redshifts $z\sim 0.6\mbox{--}3.5$ to map the large-scale structure of the universe, with the main goal to provide Baryonic Acoustic Oscillation (BAO) measurements in the uncharted redshift change spanning $0.6\lt z\lt 2.2$. eBOSS achieves this by observing a new set of targets: high-redshift LRGs, ELGs, and quasars. The three new tracers will provide BAO distance measurements with a precision of 1% at z = 0.7 (LRGs), 2% at z = 0.85 (ELGs), and 2% at z = 1.5 (quasars). The Lyα forest imprinted on approximately 120,000 new quasar spectra will give eBOSS an improved BAO measurement of 1.4× over that achieved by BOSS (Delubac et al. 2015; Bautista et al. 2017). Furthermore, the clustering from eBOSS tracers will allow new measurements of redshift-space distortions, non-Gaussianity in the primordial density field, and the summed mass of neutrino species. eBOSS will provide the first percent-level distance measurements with BAO in the redshift range $0.6\lt z\lt 3$, when cosmic expansion transitioned from deceleration to acceleration. The new redshift coverage of eBOSS obtained by targeting three classes of targets (LRGs, ELGs, and quasars) will have the statistical power to improve constraints relative to BOSS by up to a factor of 1.5 in ${{\rm{\Omega }}}_{M}$, a factor of three in the Dark Energy Task Force Figure of Merit (Albrecht et al. 2006), and a factor of 1.8 in the sum of the neutrino masses (Zhao et al. 2016).

We show in Figure 1 the N(z) in eBOSS DR14 QSO and LRG targets compared to the final BOSS release in DR12 (Alam et al. 2015), demonstrating how eBOSS is filling in the redshift desert between $z\sim 0.8\mbox{--}2.0$. DR14 does not contain any significant number of ELG targets, which will be released in future DRs.

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A significant number of fibers on the eBOSS plates are devoted to two additional dark-time programs. TDSS (TDSS; Morganson et al. 2015) seeks to understand the nature of celestial variables by targeting objects that vary in combined SDSS DR9 and Pan-STARRS1 data (PS1; Kaiser et al. 2002). A large number of the likely TDSS quasar targets are also targeted by the main eBOSS algorithms and therefore meet the goals of both surveys. TDSS-only targets fill ∼10 spectra per square degree. SPIDERS aims to characterize a subset of X-ray sources identified by eROSITA (extended Roentgen Survey with an Imaging Telescope Array; Predehl et al. 2014). However, until the first catalog of eROSITA sources is available, SPIDERS will target sources from the RASS (Roentgen All-Sky Survey; Voges et al. 1999) and XMM-Newton (X-ray Multi-mirror Mission; Jansen et al. 2001). SPIDERS will also obtain on average ∼10 spectra per square degree over the course of SDSS-IV, but the number of fibers per square degree on a plate is weighted toward the later years to take advantage of the new data from eROSITA.

A small fraction of eBOSS time is dedicated to an ancillary program to perform multi-object reverberation mapping for a single 7 deg² field. This program (SDSS-RM) aims to detect the lags between the broad-line flux and continuum flux in quasars over a broad range of redshift and luminosity with spectroscopic monitoring, which allows the measurement of the masses of these quasar black holes. Started as an ancillary program in SDSS-III, SDSS-RM continues in SDSS-IV with ∼12 epochs (each at nominal eBOSS depth) per year to extend the time baseline of the monitoring and to detect lags on multiyear timescales. The details of the SDSS-RM program can be found in Shen et al. (2015), and initial results on lag detections are reported in Shen et al. (2016) and Grier et al. (2017).

eBOSS started in 2014 September by taking spectra of LRGs and quasars, while further development on the definition of the ELG targets sample was conducted in parallel. In 2016 May, eBOSS completed its first major cosmological sample containing LRGs and quasars from the first two years of eBOSS data and from SEQUELS (already part of the DR13 release). These data have already been used to improve the classification of galaxy spectra (Hutchinson et al. 2016), introduce new techniques to the modeling of incompleteness in galaxy clustering, and to provide measurements of clustering on BAO scales at $1\lt z\lt 2$ for the first time (Ata et al. 2017).

4.1. Data Description

DR14 includes the data from 496 plates observed under the eBOSS program; it also includes the 126 SEQUELS plates (already released in DR13) from an ancillary program to take advantage of some of the dark time released when BOSS was completed early. The SEQUELS targets are similar to the eBOSS targets as it was a program to test the selection algorithms of eBOSS, in particular the LRG (Prakash et al. 2016) and quasar algorithms (Myers et al. 2015). The final ELG target recipe does not follow the one tested during SEQUELS. The new ELG recipe is documented in the DR14 release following the description given by Raichoor et al. (2017).

For the TDSS program, combined SDSS DR9 and Pan-STARRS1 data (PS1; Kaiser et al. 2002) are used to select variable object targets (Morganson et al. 2015; Ruan et al. 2016), while for SPIDERS, the objects are selected from a combination of X-ray and optical imaging for the SPIDERS cluster (Clerc et al. 2016) and AGN (Dwelly et al. 2017) programs.

The sky distribution of the DR14 data from eBOSS is shown in Figure 2. Table 3 summarizes the content and gives brief explanations of the targeting categories.

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Table 3.  eBOSS Spectroscopic Target Categories in DR14

Target Category	Target Flag	# DR14	Reference(s)
Main LRG sample	LRG1_WISE	105,764	Prakash et al. (2016)
Ancillary LRG sample	LRG1_IDROP	45	Prakash et al. (2016)
Main QSO selection	QSO1_EBOSS_CORE	154,349	Myers et al. (2015)
Variability-selected QSOs	QSO1_VAR_S82	10,477	Palanque-Delabrouille et al. (2016)
	QSO1_PTF	54,037	Myers et al. (2015)
Re-observed BOSS QSOs	QSO1_REOBS	16,333	Myers et al. (2015)
	QSO1_BAD_BOSS	584
QSOs from FIRST survey	QSO1_EBOSS_FIRST	1792	Myers et al. (2015)
All eBOSS QSOs also in BOSS	QSO_BOSS_TARGET	583	Myers et al. (2015)
All eBOSS QSOs also in SDSS	QSO_SDSS_TARGET	20	Myers et al. (2015)
All "known" QSOs	QSO_KNOWN	11	Myers et al. (2015)
Time-domain spectroscopic survey (TDSS)	TDSS_TARGET	39,748	Morganson et al. (2015), MacLeod et al. (2017)
X-ray sources from RASS & XMM-Newton	SPIDERS_TARGET	13,261	Clerc et al. (2016), Dwelly et al. (2017)
X-ray sources in Stripe 82	S82X_TILE1	2775	LaMassa et al. (2017)
	S82X_TILE2	2621
	S82X_TILE3	4
ELG Pilot Survey	ELG_TEST1	15,235	Delubac et al. (2017), Raichoor et al. (2016)
	ELG1_EBOSS	4741
	ELG1_EXTENDED	659
Standard stars	STD_FSTAR	8420	Dawson et al. (2016)
Standard white dwarfs	STD_WD	546	Dawson et al. (2016)

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4.2. Retrieving eBOSS Data

4.3. eBOSS/TDSS/SPIDERS VACs

4.4. FIREFLY Stellar Population Models of SDSS-I–SDSS-III and eBOSS Galaxy Spectra

DR14 is the fourth release from the Apache Point Observatory Galactic Evolution Experiment (APOGEE). DR14 presents, for the first time, the first two years of SDSS-IV APOGEE-2 data (2014 July–2016 July) as well as re-processed data from SDSS-III APOGEE-1 (2011 August–2014 July). Note that the general term APOGEE data, employed throughout this paper, refers to both APOGEE-1 and APOGEE-2 data. APOGEE-2 data are substantively the same as APOGEE-1 data; however, one of the three detectors in the instrument was replaced at the end of APOGEE-1 because it exhibited a substantial amount of persistence (i.e., light from previous exposures led to excess recorded charge in subsequent exposures). The new detector is substantially better in this regard.

APOGEE data in DR14 includes visit-combined spectra as well as pipeline-derived stellar atmospheric parameters and individual elemental abundances for 263,444 stars,¹⁴³ sampling all major components of the Milky Way. The DR14 coverage of APOGEE data is shown in Galactic coordinates in Figure 3. In addition to the Milky Way bulge, disk, and halo, DR14 includes, for the first time, data from stars in satellite galaxies, which are typically fainter targets than those from the main portion of the survey. DR14 incorporates a few modifications in the DRP as well as in the APOGEE Stellar Parameter and Chemical Abundance Pipeline (ASPCAP). It also includes a separate set of stellar parameters and abundances from The Cannon (Ness et al. 2015).¹⁴⁴

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Two separate papers will provide more in-depth discussion and analysis of APOGEE data released in DR13/DR14: J. Holtzman et al. (2018, in preparation) describes in detail the DR13/DR14 pipeline processing as well as the associated data products, and H. Jönsson et al. (2018, in preparation) compares stellar parameter and element abundances from DR13/DR14 with those from the literature.

5.1. Targeting

5.2. Reduction and Analysis Pipeline. Data Products

As with the previous data releases, all spectra are processed through the DRP, which includes dark current subtraction, cosmic-ray removal, flat-fielding, spectral extraction, telluric correction, wavelength calibration, and dither combination. Radial velocities (RVs) are determined for each individual visit and the individual visit spectra are resampled to rest wavelength and combined to generate a single spectrum for each object. Associated DRP data products are the visit-combined spectra and RV values. For DR14, modifications to the RV determination and associated star combination have occurred. The RV values are now determined both relative to the combined spectrum (in an iterative fashion) as well as to the best-matching model. The RVs from the method that yields the lower scatter are adopted (VHELIO_AVG), and estimates of the associated error and scatter are generated. Note that the new methodology has resulted in improved RV determinations for low S/N observations (and consequently, faint stars), but there can still be potentially significant issues with some of the faintest targets. The distribution of S/N values for spectra released in DR14 (compared to those released in DR13; Albareti & Allende Prieto et al. 2017) are shown in Figure 4.

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5.2.1. Persistence

As discussed in Nidever et al. (2015) and Holtzman et al. (2015), one of the three APOGEE-1 detectors (the "blue" detector) exhibited significant levels of persistence (i.e., charge that is held between exposures) over one-third of the detector area, and another (the "green" detector) exhibited persistence at a somewhat lower level over a smaller area. This persistence affected the derived stellar abundances (Holtzman et al. 2015). As mentioned above, the "blue" detector was replaced for APOGEE-2 in part to solve this problem. For the APOGEE-1 data, we attempt to subtract out persistence based on a model and also de-weight pixels affected by persistence during visit combination in such a way that for stars with a mix of persistence-affected and non-persistence-affected visits, the combined spectra are dominated by the non-affected visits. This results in a reduction of the systematic errors, but a slight increase of the random errors. This process significantly reduces the impact of persistence (J. Holtzman et al. 2018, in preparation); however, it can still have an effect, especially for fainter targets. Users of the APOGEE spectra should pay careful attention to the pixel-level data flags and the pixel uncertainties.

5.2.2. ASPCAP

After the DRP stage, the visit-combined stellar spectra are processed by ASPCAP, which derives the stellar atmospheric parameters (e.g., effective temperature $T\mathrm{eff}$, surface gravity $\mathrm{log}g$, metallicity [M/H]) as well as abundances for more than 20 species. The ASPCAP determination proceeds in three stages: an initial pass through ASPCAP gives coarse values for a few key atmospheric parameters to identify which spectral grids should be used on each object, a second pass yields the full set of parameters, and a final pass determines the abundances for each element with the stellar parameters fixed.

For DR14, ASPCAP modifications include a new normalization scheme for both observed and synthetic spectra. Rather than using an iteratively asymmetrically clipped fit, the continuum is determined by a polynomial fit to the spectra after masking of sky lines. This new scheme avoids clipping, since it leads to systematic differences in continuum normalization as a function of S/N. Another change is that the ASPCAP parameter determination was done by ${\chi }^{2}$ minimization over a seven-dimensional grid for giants which included a microturbulence dimension. This leads to a slightly lower abundance scatter in clusters as well as smaller trends of [M/H] with temperature.

One caveat of the DR14 ASPCAP analysis is that new grids were not constructed for APOGEE-2 line spread functions (LSFs): grids made with the APOGEE-1 LSFs were used. Since the only change was the detector replacement, large LSF changes were neither expected nor noticed, but subtle differences may be present.

5.2.3. Calibration and Data Product Usage

As with previous DRs, DR14 includes a post-ASPCAP calibration of the final stellar atmospheric parameter and element abundances. A variety of different stellar clusters and standards are employed in the calibration of the results. These calibrations include a metallicity-dependent temperature correction, a surface gravity calibration based on asteroseismic gravities, an internal and external calibration of metallicity ([M/H]), and a temperature-dependent and zero-point calibration for elemental abundances. Note that surface gravity calibration is not done for dwarfs because we do not have independent estimates of surface gravities from which to derive such calibrations. Calibrations are applied to abundances over temperature ranges that are determined by looking at the ranges over which data in star clusters produce the same abundance. Based on cluster results and inspection of the spectra, we do not provide calibrated abundances for Cu, Ge, Y, Rb, and Nd since these do not appear to be reliable.

Several different bitmasks (STARFLAG, PARAMFLAG, ASPCAPFLAG) that provide information on factors that affect data quality are included, and users are strongly encouraged to pay attention to these.

5.3. New DR14 Data Product: Results from The Cannon

5.4. APOGEE VACs

In the context of the MaNGA Survey, DR14 roughly doubles the sample size of the associated data products that were first made public in DR13. Spanning observations from the first two years of operations, the DR14 products include raw observations, intermediate reduction output, such as reduced fiber spectra, and final data cubes as constructed by the DRP (Law et al. 2016, hereafter L16). A summary drpall catalog provides target identification information, sky positions, and object properties like photometry and redshifts. The MaNGA observing strategy is described in Law et al. (2015), and the flux calibration scheme is presented in Yan et al. (2016b). An overview of the survey execution strategy and data quality is provided in Yan et al. (2016a). Weijmans & MaNGA Team (2016) provide a short summary to the entire survey, which is comprehensively described in Bundy et al. (2015).

DR14 includes observations from 166 MaNGA plates resulting in 2812 data cubes comprising targets in the main samples as well as ancillary programs, and around 50 repeat observations. The sky layout of the DR14-released MaNGA data is shown in Figure 5.

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6.1. MaNGA Target Classes

6.2. Working with MaNGA Data

6.3. Highlights of MaNGA Science with DR14 Data

6.4. MaNGA VACs

SDSS-IV is planning a six-year survey, with operations at both the 2.5 m Sloan Foundation Telescope at APO, New Mexico, USA, and the du Pont Telescope at Las Campanas, Chile, scheduled through 2020. Future data releases from SDSS-IV will include data observed with both telescopes; the final SDSS-IV data release is planned to be DR18, currently scheduled for 2020 December.

For APOGEE, future data releases will include, for the first time, southern hemisphere observations taken with the new APOGEE-S instrument at the Las Campanas Observatory with the du Pont 2.5 m telescope. These observations will extend APOGEE coverage to the full Galaxy, with significantly increased observations of the Galactic bulge and also include observations in the Magellanic Clouds, globular clusters, and dwarf spheroidal galaxies only accessible from the southern hemisphere. As usual, future data releases will also include re-reductions of all APOGEE-N data. Plans for improved stellar parameter/abundance analysis include using a new homogeneous grid of MARCS stellar atmospheres and the use of "minigrids" to analyze elements whose absorption features are too blended with those of other elements to be reliably extracted with the abundance techniques used to date.

For MaNGA, it is planned that the DR15 data release will include the ∼4000 MaNGA galaxies that have been observed up to the summer shutdown of 2017. In addition, we anticipate a number of new data products to be released in this and future DRs. These include reduced spectra from the MaStar stellar library (Yan et al. 2017), which is making use of commensal observations during APOGEE-2 time to obtain spectroscopic observations of stars which will be used to build a new stellar library through the MaNGA instrumentation, and output from the MaNGA DAP (K. Westfall et al. 2018, in preparation). The DAP produces maps of emission-line fluxes, gas and stellar kinematics, and stellar population properties. Some similar derived data products are already available as VACs (see Table 2 and Sections 6.4.1 and 6.4.2). Finally, we intend for DR15 to mark the first release of the "Marvin" ecosystem, which includes powerful Python tools for seamlessly downloading and querying the MaNGA data as well as a Web interface that provides advanced search functionality, a user interface for the MaNGA data cubes, and the ability to quickly choose and display maps of key quantities measured by the DAP.

For eBOSS, future data releases will include the ELG survey results as well as the continuation of the LRG-QSO surveys. They will also include further VACs: in particular, the continuation of the quasar catalog, a detailed ELG catalog, as well as large-scale structure clustering catalogs required for independent clustering analysis. Further improvement on the redshift measurement and spectral classification catalog is also likely.

For TDSS, a future SDSS data release will include very recent spectra from its Repeat Quasar Spectroscopy (RQS) program, which obtains multi-epoch spectra for thousands of known quasars, all of which have least one epoch of SDSS spectroscopy available (and often already archived). Quasar spectral variability on multiyear timescales is currently poorly characterized for large samples, although there are many exciting results from smaller select subsets (see Runnoe et al. 2016 and McGraw et al. 2017 for examples of studies based on repeat spectroscopy, ranging from discoveries of new changing-look quasars to BAL emergence and disappearance). The RQS program in TDSS will ultimately observe ∼10⁴ known (SDSS) quasars in the ELG survey region (Raichoor et al. 2017), adding at least one additional spectral epoch. This will allow for an extension of earlier work to a systematic investigation of quasar spectroscopic variability, both by making a larger sample and also by including large numbers of quasars as targets for repeat spectra that were selected without a priori knowledge of their specific quasar spectroscopic subclass or variability properties. A recent detailed technical description of target selection for all of the TDSS repeat spectroscopy programs (including RQS) may be found in MacLeod et al. (2017).

For SPIDERS, future data releases will focus on higher level data products, such as black hole masses and host galaxy properties of the X-ray AGN, as well as rich characterization of the X-ray-selected clusters (in particular, dynamical properties and calibrated cluster masses). The first spectra of counterparts of eROSITA sources, however, will only be obtained beginning in spring 2019, so they will be part of DR18 and subsequent releases only.

Planning has begun for the next generation of SDSS, to begin in 2020 (Kollmeier et al. 2017). SDSS-V will build on the SDSS infrastructure and expand the instrumentation (especially for optical IFU spectroscopy) in both hemispheres. This expansion of SDSS's legacy will enable an enormous sample comprising millions of spectra of quasars, galaxies, and stars, with scientific goals ranging from the growth of supermassive black holes to the chemical and dynamical structure of the Milky Way, the detailed architecture of planetary systems, and the astrophysics of star formation.

We would like to thank the University of St Andrews, Scotland, for their hospitality during DocuCeilidh 2017.

Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org.

SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration, including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.