{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:51:40Z","timestamp":1740099100078,"version":"3.37.3"},"publisher-location":"Cham","reference-count":50,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319965529"},{"type":"electronic","value":"9783319965536"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-96553-6_5","type":"book-chapter","created":{"date-parts":[[2018,7,12]],"date-time":"2018-07-12T01:00:38Z","timestamp":1531357238000},"page":"61-72","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9506-5680","authenticated-orcid":false,"given":"Massimo","family":"Brescia","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3787-4196","authenticated-orcid":false,"given":"Stefano","family":"Cavuoti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1953-5104","authenticated-orcid":false,"given":"Valeria","family":"Amaro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7020-1172","authenticated-orcid":false,"given":"Giuseppe","family":"Riccio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0316-6562","authenticated-orcid":false,"given":"Giuseppe","family":"Angora","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8141-5552","authenticated-orcid":false,"given":"Civita","family":"Vellucci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9182-8414","authenticated-orcid":false,"given":"Giuseppe","family":"Longo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,7,13]]},"reference":[{"key":"5_CR1","unstructured":"Ivezic, Z., et al.: LSST: from science drivers to reference design and anticipated data products. arXiv:0805.2366v4 (2008)"},{"issue":"11\u201312","key":"5_CR2","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1016\/j.newar.2004.09.045","volume":"48","author":"CA Blake","year":"2004","unstructured":"Blake, C.A., Abdalla, F.B., Bridle, S.L., Rawlings, S.: Cosmology with the SKA. New Astron. Rev. 48(11\u201312), 1063\u20131077 (2004)","journal-title":"New Astron. Rev."},{"key":"5_CR3","unstructured":"Allen, M.G., Fernique, P., Boch, T., et al.: An Hierarchical Approach to Big Data. arXiv:1611.01312 (2016)"},{"key":"5_CR4","unstructured":"Longo, G., Brescia, M., Cavuoti, S.: The astronomical data deluge: the template case of photometric redshifts. In: CEUR Workshop Proceedings, vol. 2022, pp. 27\u201329 (2017)"},{"key":"5_CR5","unstructured":"Dunham, M.: Data Mining Introductory and Advanced Topics. Prentice-Hall, Upper Saddle River (2002)"},{"issue":"923","key":"5_CR6","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1086\/669333","volume":"125","author":"M Annunziatella","year":"2013","unstructured":"Annunziatella, M., et al.: Inside catalogs: a comparison of source extraction software. PASP 125(923), 68\u201382 (2013)","journal-title":"PASP"},{"key":"5_CR7","unstructured":"Odenwald, S.: Cosmology in More Than 4 Dimensions. Astrophysics Workshop, N.R.L. (1987)"},{"key":"5_CR8","unstructured":"Paliouras, G.: Scalability of Machine Learning Algorithms. M.Sc. thesis, University of Manchester (1993)"},{"key":"5_CR9","unstructured":"Goldberg, D.E., Holland, J.H.: Genetic algorithms and machine learning. Mach. Learn. 3, 95\u201399 (1988)"},{"issue":"942","key":"5_CR10","first-page":"783","volume":"126","author":"M Brescia","year":"2014","unstructured":"Brescia, M., Cavuoti, S., Longo, G., et al.: DAMEWARE: a web cyberinfrastructure for astrophysical data mining. PASP 126(942), 783\u2013797 (2014)","journal-title":"PASP"},{"key":"5_CR11","unstructured":"Hey, T., Tansley, S., Tolle, K.: The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, Redmond (2009)"},{"key":"5_CR12","unstructured":"Brescia, M.: New trends in E-science: machine learning and knowledge discovery in databases. In: Horizons in Computer Science Research, vol. 7, pp. 1\u201373. Nova Science Publishers (2012)"},{"key":"5_CR13","unstructured":"Baum, W.A.: Photometric magnitudes and redshifts. In: McVittie, G.C. (ed.) IAU Symposium, vol. 15, Problems of Extra-Galactic Research, p. 390 (1962)"},{"key":"5_CR14","doi-asserted-by":"publisher","first-page":"2655","DOI":"10.1086\/117720","volume":"110","author":"A. J. Connolly","year":"1995","unstructured":"Connolly, A.J., Csabai, I., Szalay, A.S., et al.: Slicing through multicolour space: galaxy redshifts from broadband photometry. AJ 110, 2655 (1995)","journal-title":"The Astronomical Journal"},{"key":"5_CR15","first-page":"476","volume":"363","author":"M Bolzonella","year":"2000","unstructured":"Bolzonella, M., Miralles, J.M., Pello, R.: Photometric redshifts based on standard SED fitting procedures. A&A 363, 476\u2013492 (2000)","journal-title":"A&A"},{"key":"5_CR16","doi-asserted-by":"publisher","first-page":"540","DOI":"10.1046\/j.1365-8711.1999.02978.x","volume":"310","author":"S Arnouts","year":"1999","unstructured":"Arnouts, S., Cristiani, S., Moscardini, L., et al.: Measuring and modelling the redshift evolution of clustering: the Hubble Deep Field North. MNRAS 310, 540 (1999)","journal-title":"MNRAS"},{"key":"5_CR17","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1051\/0004-6361:20065138","volume":"457","author":"O Ilbert","year":"2006","unstructured":"Ilbert, O., Arnouts, S., McCracken, H.J., et al.: Accurate photometric redshifts for the CFHT Legacy Survey calibrated using the VIMOS VLT Deep Survey. A&A 457, 841 (2006)","journal-title":"A&A"},{"issue":"1","key":"5_CR18","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1088\/0004-637X\/801\/1\/20","volume":"801","author":"Masayuki Tanaka","year":"2015","unstructured":"Tanaka, M.: Photometric redshift with Bayesian priors on physical properties of galaxies. AJ 801, 1, 20 (2015)","journal-title":"The Astrophysical Journal"},{"key":"5_CR19","doi-asserted-by":"crossref","unstructured":"Tagliaferri, R., Longo, G., Andreon, S., et al.: Neural Networks and Photometric Redshifts, ArXiv e-prints:0203445 (2002)","DOI":"10.1007\/978-3-540-45216-4_26"},{"issue":"3","key":"5_CR20","doi-asserted-by":"publisher","first-page":"3100","DOI":"10.1093\/mnras\/stv1496","volume":"452","author":"S Cavuoti","year":"2015","unstructured":"Cavuoti, S., Brescia, M., Tortora, C., et al.: Machine-Learning-based photometric redshifts for the KiDS ESO DR2 galaxies. MNRAS 452(3), 3100\u20133105 (2015)","journal-title":"MNRAS"},{"issue":"1","key":"5_CR21","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/s10686-015-9443-4","volume":"39","author":"S Cavuoti","year":"2015","unstructured":"Cavuoti, S., Brescia, M., De Stefano, V., Longo, G.: Photometric redshift estimation based on data mining with PhotoRApToR. Exp. Astron. 39(1), 45\u201371 (2015)","journal-title":"Exp. Astron."},{"key":"5_CR22","doi-asserted-by":"publisher","first-page":"A126","DOI":"10.1051\/0004-6361\/201424383","volume":"568","author":"M Brescia","year":"2014","unstructured":"Brescia, M., Cavuoti, S., Longo, G., De Stefano, V.: A catalogue of photometric redshifts for the SDSS-DR9 galaxies (Research Note). Astron. Astrophys. 568, A126 (2014)","journal-title":"Astron. Astrophys."},{"key":"5_CR23","unstructured":"Carrasco, K., Brunner, R.J.: Implementing Probabilistic Photometric Redshifts, Astronomical Data Analysis Software and Systems XXII. San Francisco: Astronomical Society of the Pacific, p. 69 (2013)"},{"key":"5_CR24","doi-asserted-by":"publisher","first-page":"1891","DOI":"10.1111\/j.1365-2966.2011.19375.x","volume":"417","author":"Abdalla","year":"2011","unstructured":"Abdalla, et al.: A comparison of six photometric redshift methods applied to 1.5 million luminous red galaxies. MNRAS 417, 1891 (2011)","journal-title":"MNRAS"},{"key":"5_CR25","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1086\/383254","volume":"116","author":"AA Collister","year":"2004","unstructured":"Collister, A.A., Lahav, O.: ANNz: estimating photometric redshifts using artificial neural networks. PASP 116, 345 (2004)","journal-title":"PASP"},{"issue":"2","key":"5_CR26","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1088\/0004-637X\/715\/2\/823","volume":"715","author":"David W. Gerdes","year":"2010","unstructured":"Gerdes, et al.: ArborZ: photometric redshifts using boosted decision trees. AJ 715, 823 (2010)","journal-title":"The Astrophysical Journal"},{"issue":"4","key":"5_CR27","doi-asserted-by":"publisher","first-page":"3409","DOI":"10.1093\/mnras\/stt2456","volume":"438","author":"K Carrasco","year":"2014","unstructured":"Carrasco, K., Brunner, R.J.: Sparse representation of photometric redshift PDFs: preparing for petascale astronomy. MNRAS 438(4), 3409\u20133421 (2014)","journal-title":"MNRAS"},{"issue":"4","key":"5_CR28","doi-asserted-by":"publisher","first-page":"3380","DOI":"10.1093\/mnras\/stu1098","volume":"442","author":"K Carrasco","year":"2014","unstructured":"Carrasco, K., Brunner, R.J.: Exhausting the information: novel bayesian combination of photometric redshift PDFs. MNRAS 442(4), 3380\u20133399 (2014)","journal-title":"MNRAS"},{"key":"5_CR29","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1051\/0004-6361\/201219755","volume":"546","author":"S Cavuoti","year":"2012","unstructured":"Cavuoti, S., Brescia, M., Longo, G., Mercurio, A.: Photometric redshifts with the quasi Newton algorithm (MLPQNA) results in the PHAT1 contest. A&A 546, 13 (2012)","journal-title":"A&A"},{"key":"5_CR30","first-page":"29","volume":"19","author":"S Cavuoti","year":"2013","unstructured":"Cavuoti, S., et al.: Genetic algorithm modeling with GPU parallel computing technology smart innovation. Syst. Technol. 19, 29\u201339 (2013)","journal-title":"Syst. Technol."},{"key":"5_CR31","first-page":"12","volume":"26","author":"S Cavuoti","year":"2014","unstructured":"Cavuoti, S., et al.: Astrophysical data mining with GPU. A case study: genetic classification of globular clusters, New Astron. 26, 12\u201322 (2014)","journal-title":"A case study: genetic classification of globular clusters, New Astron."},{"key":"5_CR32","doi-asserted-by":"publisher","first-page":"A31","DOI":"10.1051\/0004-6361\/201014885","volume":"523","author":"H Hildebrandt","year":"2010","unstructured":"Hildebrandt, H., et al.: PHAT: PHoto- z Accuracy Testing. A&A 523, A31 (2010)","journal-title":"A&A"},{"key":"5_CR33","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1093\/mnras\/stv599","volume":"450","author":"B Hoyle","year":"2015","unstructured":"Hoyle, B., Rau, M.M., Bonnett, C., Seitz, S., Weller, J.: Anomaly detection for machine learning redshifts applied to SDSS galaxies. MNRAS 450, 305\u2013316 (2015)","journal-title":"MNRAS"},{"issue":"2","key":"5_CR34","doi-asserted-by":"publisher","first-page":"2039","DOI":"10.1093\/mnras\/stw3208","volume":"466","author":"S Cavuoti","year":"2017","unstructured":"Cavuoti, S., et al.: A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data. MNRAS 466(2), 2039\u20132053 (2017)","journal-title":"MNRAS"},{"key":"5_CR35","doi-asserted-by":"crossref","unstructured":"Duncan, K.J., Jarvis, M.J., Brown, M.J.I., et al.: Photometric redshifts for the next generation of deep radio continuum surveys - II. Gaussian processes and hybrid estimates, arXiv:1712.04476 (2017)","DOI":"10.1093\/mnras\/sty940"},{"key":"5_CR36","doi-asserted-by":"publisher","first-page":"2165","DOI":"10.1111\/j.1365-2966.2011.19416.x","volume":"418","author":"O Laurino","year":"2011","unstructured":"Laurino, O., DAbrusco, R., Longo, G., Riccio, G.: Astroinformatics of galaxies and quasars: a new general method for photometric redshifts estimation. MNRAS 418, 2165 (2011)","journal-title":"MNRAS"},{"key":"5_CR37","unstructured":"Polsterer, K.L., Gieseke, F., Igel, C., Goto, T.: Improving the performance of photometric regression models via massive parallel feature selection. In: Manset, N., Forshay, P. (ed.) Data Analysis Software and Systems. ASP Conference Series, vol. 485, p. 425 (2014)"},{"issue":"1","key":"5_CR38","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1088\/0004-637X\/813\/1\/53","volume":"813","author":"Daniel Masters","year":"2015","unstructured":"Masters, D., Capak, P., Stern, D., et al.: Mapping the galaxy color\u2013redshift relation: optimal photometric redshift calibration strategies for cosmology surveys. ApJ 813(1), 53 (2015)","journal-title":"The Astrophysical Journal"},{"issue":"2","key":"5_CR39","doi-asserted-by":"publisher","first-page":"24","DOI":"10.3847\/0067-0049\/224\/2\/24","volume":"224","author":"C. Laigle","year":"2016","unstructured":"Laigle, C., et al.: The COSMOS2015 Catalog: Exploring the 1\u2009<\u2009z\u2009<\u20096 Universe with Half a Million Galaxies, ApJ Supp. Ser. 224(2), 23 (2016). Article id. 24","journal-title":"The Astrophysical Journal Supplement Series"},{"issue":"S325","key":"5_CR40","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1017\/S1743921317001521","volume":"12","author":"P Dubath","year":"2016","unstructured":"Dubath, P., Apostolakos, N., Bonchi, A., et al.: The euclid data processing challenges. Proc. IAU 12(S325), 73\u201382 (2016)","journal-title":"Proc. IAU"},{"key":"5_CR41","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1088\/0067-0049\/203\/2\/21","volume":"203","author":"CP Ahn","year":"2012","unstructured":"Ahn, C.P., Alexandroff, R., Allende Prieto, C., et al.: The ninth data release of the sloan digital sky survey: first spectroscopic data from the SDSS-III baryon oscillation spectroscopic survey. ApJS 203, 21 (2012)","journal-title":"ApJS"},{"key":"5_CR42","doi-asserted-by":"crossref","unstructured":"D\u2019Isanto, A., Cavuoti, S., Gieseke, F., Polsterer, K.L.: Return of the features - Efficient feature selection and interpretation for photometric redshifts. Submitted to A&A (2018)","DOI":"10.1051\/0004-6361\/201833103"},{"key":"5_CR43","doi-asserted-by":"publisher","first-page":"104502","DOI":"10.1088\/1538-3873\/128\/968\/104502","volume":"128","author":"I Sadeh","year":"2016","unstructured":"Sadeh, I., Abdalla, F.B., Lahav, O.: ANNz2: photometric redshift and probability distribution function estimation using machine learning. PASP 128, 104502 (2016)","journal-title":"PASP"},{"issue":"2","key":"5_CR44","doi-asserted-by":"publisher","first-page":"1959","DOI":"10.1093\/mnras\/stw2930","volume":"465","author":"S Cavuoti","year":"2017","unstructured":"Cavuoti, S., Amaro, V., Brescia, M., et al.: METAPHOR: a machine-learning-based method for the probability density estimation of photometric redshifts. MNRAS 465(2), 1959\u20131973 (2017)","journal-title":"MNRAS"},{"key":"5_CR45","doi-asserted-by":"publisher","first-page":"A134","DOI":"10.1051\/0004-6361\/201730747","volume":"604","author":"JTA Jong de","year":"2017","unstructured":"de Jong, J.T.A., Verdoes Kleijn, G.A., Erben, T., Hildebrandt, H., et al.: The third data release of the Kilo-Degree Survey and associated data products. Astron. Astrophys. 604, A134 (2017)","journal-title":"Astron. Astrophys."},{"issue":"2","key":"5_CR46","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1088\/0004-637X\/772\/2\/140","volume":"772","author":"M Brescia","year":"2013","unstructured":"Brescia, M., Cavuoti, S., D\u2019Abrusco, R., Mercurio, A., Longo, G.: Photometric redshifts for quasars in multi-band surveys. ApJ 772(2), 140 (2013)","journal-title":"ApJ"},{"key":"5_CR47","doi-asserted-by":"crossref","unstructured":"Amaro, V., Cavuoti, S., Brescia M., Vellucci C., Longo, G., et al.: Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies. MNRAS submitted (2018)","DOI":"10.1093\/mnras\/sty2922"},{"issue":"2","key":"5_CR48","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1086\/308947","volume":"536","author":"N Benitez","year":"2000","unstructured":"Benitez, N.: Bayesian Photometric Redshift Estimation. ApJ 536(2), 571\u2013583 (2000)","journal-title":"ApJ"},{"issue":"5","key":"5_CR49","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1175\/MWR2904.1","volume":"133","author":"T Gneiting","year":"2005","unstructured":"Gneiting, T., Raftery, A.E., Westveld, A.H., Goldman, T.: Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Mon. Weather Rev. 133(5), 1098 (2005)","journal-title":"Mon. Weather Rev."},{"key":"5_CR50","doi-asserted-by":"publisher","first-page":"4005","DOI":"10.1093\/mnras\/stw261","volume":"457","author":"D Wittman","year":"2016","unstructured":"Wittman, D., Bhaskar, R., Tobin, R.: Overconfidence in photometric redshift estimation. MNRAS 457, 4005 (2016)","journal-title":"MNRAS"}],"container-title":["Communications in Computer and Information Science","Data Analytics and Management in Data Intensive Domains"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-96553-6_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,20]],"date-time":"2019-10-20T13:38:32Z","timestamp":1571578712000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-96553-6_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319965529","9783319965536"],"references-count":50,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-96553-6_5","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2018]]}}}