{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T17:58:07Z","timestamp":1761674287539,"version":"3.41.0"},"reference-count":118,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2019,6,18]],"date-time":"2019-06-18T00:00:00Z","timestamp":1560816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Australian Research Council projects","award":["DP170100136 and LP140100816"],"award-info":[{"award-number":["DP170100136 and LP140100816"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2020,5,31]]},"abstract":"<jats:p>Integration of embedded multimedia devices with powerful computing platforms, e.g., machine learning platforms, helps to build smart cities and transforms the concept of Internet of Things into Internet of Multimedia Things (IoMT). To provide different services to the residents of smart cities, the IoMT technology generates big multimedia data. The management of big multimedia data is a challenging task for IoMT technology. Without proper management, it is hard to maintain consistency, reusability, and reconcilability of generated big multimedia data in smart cities. Various machine learning techniques can be used for automatic classification of raw multimedia data and to allow machines to learn features and perform specific tasks. In this survey, we focus on various machine learning platforms that can be used to process and manage big multimedia data generated by different applications in smart cities. We also highlight various limitations and research challenges that need to be considered when processing big multimedia data in real-time.<\/jats:p>","DOI":"10.1145\/3323334","type":"journal-article","created":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T12:05:38Z","timestamp":1560945938000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":37,"title":["A Survey on Big Multimedia Data Processing and Management in Smart Cities"],"prefix":"10.1145","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2165-4575","authenticated-orcid":false,"given":"Muhammad","family":"Usman","sequence":"first","affiliation":[{"name":"Swinburne University of Technology, Melbourne, Victoria, Australia"}]},{"given":"Mian Ahmad","family":"Jan","sequence":"additional","affiliation":[{"name":"Abdul Wali Khan University Mardan, Mardan, Khyber Pakhtunkhwa, Pakistan"}]},{"given":"Xiangjian","family":"He","sequence":"additional","affiliation":[{"name":"University of Technology Sydney, Sydney, New SouthWales, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1677-9525","authenticated-orcid":false,"given":"Jinjun","family":"Chen","sequence":"additional","affiliation":[{"name":"Swinburne University of Technology, Melbourne, Victoria, Australia"}]}],"member":"320","published-online":{"date-parts":[[2019,6,18]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2006.10.002"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2008.928756"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2017.08.017"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/s100706662"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2015.04.006"},{"key":"e_1_2_1_6_1","unstructured":"Amazon. 2015. Amazon API. Retrieved from https:\/\/aws.amazon.com\/documentation\/machine-learning\/.  Amazon. 2015. Amazon API. Retrieved from https:\/\/aws.amazon.com\/documentation\/machine-learning\/."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2005.854505"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2017.05.001"},{"key":"e_1_2_1_9_1","first-page":"125","article-title":"Support vector clustering","author":"Ben-Hur Asa","year":"2001","journal-title":"J. Machine Learn. Res. 2"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"volume-title":"Torr","year":"2016","author":"Bertinetto Luca","key":"e_1_2_1_11_1"},{"volume-title":"Smart sustainable cities of the future: An extensive interdisciplinary literature review","year":"2017","author":"Bibri Simon Elias","key":"e_1_2_1_12_1"},{"key":"e_1_2_1_13_1","unstructured":"BigML. 2011. BigML API. Retrieved from https:\/\/bigml.com\/api.  BigML. 2011. BigML API. Retrieved from https:\/\/bigml.com\/api."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2017.09.003"},{"volume-title":"Olshen","year":"1984","author":"Breiman Leo","key":"e_1_2_1_15_1"},{"volume-title":"Arun Kumar Sangaiah, and Zhigao Zheng","year":"2017","author":"Chahal Manisha","key":"e_1_2_1_16_1"},{"volume-title":"Proceedings of the 14th International Conference on Artificial Intelligence and Statistics. 215--223","year":"2011","author":"Coates Adam","key":"e_1_2_1_17_1"},{"volume-title":"Ng","year":"2012","author":"Coates Adam","key":"e_1_2_1_18_1"},{"key":"e_1_2_1_19_1","unstructured":"DELL. 2016. Saensuk Pilots Smart City in Collaboration with DELL and Intel. Retrieved from https:\/\/www.dell.com\/learn\/us\/en\/uscorp1\/press-releases\/2016-07-26-saensuk-smart-city-pilots-first-healthcare-iot-project-with-dell-intel.  DELL. 2016. Saensuk Pilots Smart City in Collaboration with DELL and Intel. Retrieved from https:\/\/www.dell.com\/learn\/us\/en\/uscorp1\/press-releases\/2016-07-26-saensuk-smart-city-pilots-first-healthcare-iot-project-with-dell-intel."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2010.06.012"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2016.01.010"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2014.2339817"},{"key":"e_1_2_1_23_1","unstructured":"dnp systems. 2017. Physical Security and Access Control Systems. Retrieved from http:\/\/www.dnpsys.com\/solution.php.  dnp systems. 2017. Physical Security and Access Control Systems. Retrieved from http:\/\/www.dnpsys.com\/solution.php."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2016.07.007"},{"key":"e_1_2_1_25_1","unstructured":"Google. 2013. Google Prediction API. Retrieved from https:\/\/cloud.google.com\/prediction\/docs\/.  Google. 2013. Google Prediction API. Retrieved from https:\/\/cloud.google.com\/prediction\/docs\/."},{"volume-title":"CURE: An efficient clustering algorithm for large databases. In ACM Sigmod Rec.","year":"1998","author":"Guha Sudipto","key":"e_1_2_1_26_1"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2017.2725638"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2016.05.002"},{"volume-title":"The Elements of Statistical Learning","author":"Hastie Trevor","key":"e_1_2_1_30_1"},{"volume-title":"Hinton and Terrence Joseph Sejnowski","year":"1999","author":"Geoffrey","key":"e_1_2_1_31_1"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2016.2642643"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/79.180705"},{"volume-title":"Independent Component Analysis","author":"Hyv\u00e4rinen Aapo","key":"e_1_2_1_35_1"},{"key":"e_1_2_1_36_1","unstructured":"IBM. 2012. IBM\u2019s Smarter Cities Challenge: Boston Report. Retrieved from https:\/\/www.smartercitieschallenge.org\/assets\/cities\/boston-united-states\/documents\/boston-united-states-full-report-2012.pdf.  IBM. 2012. IBM\u2019s Smarter Cities Challenge: Boston Report. Retrieved from https:\/\/www.smartercitieschallenge.org\/assets\/cities\/boston-united-states\/documents\/boston-united-states-full-report-2012.pdf."},{"key":"e_1_2_1_37_1","unstructured":"IBM. 2012. IBM\u2019s Smarter Cities Challenge: Louisville Summary Report. Retrieved from https:\/\/www.prd-ibm-smarter-cities-challenge.s3.amazonaws.com\/applications\/louisville-united-states-summary-2012.pdf.  IBM. 2012. IBM\u2019s Smarter Cities Challenge: Louisville Summary Report. Retrieved from https:\/\/www.prd-ibm-smarter-cities-challenge.s3.amazonaws.com\/applications\/louisville-united-states-summary-2012.pdf."},{"key":"e_1_2_1_38_1","unstructured":"IBM. 2013. IBM Watson API. Retrieved from https:\/\/www.ibm.com\/watson\/developercloud\/doc\/index.html.  IBM. 2013. IBM Watson API. Retrieved from https:\/\/www.ibm.com\/watson\/developercloud\/doc\/index.html."},{"volume-title":"IBM\u2019s Smarter Cities Challenge Report: Suffolk County","year":"2014","author":"IBM.","key":"e_1_2_1_39_1"},{"volume-title":"Walaa Nagy, and Biao Song.","year":"2017","author":"Mofijul Islam Md.","key":"e_1_2_1_40_1"},{"volume-title":"Modern Multivariate Statistical Techniques","author":"Izenman Alan Julian","key":"e_1_2_1_41_1","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-78189-1"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2009.09.011"},{"volume-title":"SAMS: A seamless and authorized multimedia streaming framework for WMSN-based IoMT","year":"2018","author":"Jan Mian Ahmad","key":"e_1_2_1_43_1"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02289588"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nancom.2012.10.001"},{"volume-title":"Optimal power\/rate trade-off for Internet of multimedia things lifetime maximization under dynamic links capacity. Future Generation Computer Systems 93 (April","year":"2019","author":"Khernane Nesrine","key":"e_1_2_1_46_1"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.1990.137622"},{"volume-title":"Self-organizing Maps","author":"Kohonen Teuvo","key":"e_1_2_1_48_1"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1002\/widm.30"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2015.2425364"},{"key":"e_1_2_1_51_1","first-page":"21","article-title":"Big data, analytics and the path from insights to value","volume":"52","author":"LaValle Steve","year":"2011","journal-title":"MIT Sloan Manag. Rev."},{"volume-title":"Deep learning. Nature 521, 7553","year":"2015","author":"LeCun Yann","key":"e_1_2_1_52_1"},{"volume-title":"Proceedings of the 26th International Conference on Machine Learning. ACM, 609--616","author":"Lee Honglak","key":"e_1_2_1_53_1"},{"volume-title":"Maglio","year":"2018","author":"Lim Chiehyeon","key":"e_1_2_1_54_1"},{"key":"e_1_2_1_55_1","first-page":"19","article-title":"Online learning for matrix factorization and sparse coding","author":"Mairal Julien","year":"2010","journal-title":"J. Mach. Learn. Res. 11"},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459452"},{"volume-title":"Bach","year":"2009","author":"Mairal Julien","key":"e_1_2_1_57_1"},{"key":"e_1_2_1_58_1","first-page":"9","article-title":"Multimedia streaming in information-centric networking: A survey and future perspectives","volume":"125","author":"Majeed Muhammad Faran","year":"2017","journal-title":"Computer Networks"},{"key":"e_1_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.3390\/s16111872"},{"key":"e_1_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1600514"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2017.2715719"},{"key":"e_1_2_1_62_1","unstructured":"Microsoft. 2015. Microsoft Azure API. Retrieved from https:\/\/azure.microsoft.com\/en-us\/services\/cognitive-services\/.  Microsoft. 2015. Microsoft Azure API. Retrieved from https:\/\/azure.microsoft.com\/en-us\/services\/cognitive-services\/."},{"key":"e_1_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2008.080404"},{"volume-title":"Foundations of Machine Learning","author":"Mohri Mehryar","key":"e_1_2_1_64_1"},{"key":"e_1_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2016.2605581"},{"volume-title":"Proceedings of the 27th International Conference on Machine Learning (ICML\u201910)","author":"Nair Vinod","key":"e_1_2_1_66_1"},{"key":"e_1_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2017.01.027"},{"key":"e_1_2_1_68_1","first-page":"1","article-title":"Sparse autoencoder. CS294A Lect","volume":"72","author":"Ng Andrew","year":"2011","journal-title":"Notes"},{"key":"e_1_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.1600263"},{"key":"e_1_2_1_70_1","unstructured":"OECD. 2015. The OECD Model Survey on ICT Access and Usage by Households and Individuals. Retrieved from https:\/\/www.oecd.org\/sti\/ieconomy\/.  OECD. 2015. The OECD Model Survey on ICT Access and Usage by Households and Individuals. Retrieved from https:\/\/www.oecd.org\/sti\/ieconomy\/."},{"volume-title":"Proceedings of the 10th International Conference on Connected Smart Cities (CSC\u201917)","year":"2017","author":"Shahat Osman Ahmed M.","key":"e_1_2_1_71_1"},{"volume-title":"Qualitative Research","author":"Patton Michael Quinn","key":"e_1_2_1_72_1"},{"key":"e_1_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2017.05.027"},{"key":"e_1_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-014-1683-5"},{"key":"e_1_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2017.08.006"},{"key":"e_1_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2016.2541999"},{"key":"e_1_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1186\/2047-2501-2-3"},{"key":"e_1_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2014.2308176"},{"volume-title":"Proceedings of the 28th International Conference on Machine Learning (ICML\u201911)","year":"2011","author":"Rifai Salah","key":"e_1_2_1_79_1"},{"key":"e_1_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2014.04.002"},{"key":"e_1_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.290.5500.2323"},{"volume-title":"Data Analytics","author":"Runkler Thomas A.","key":"e_1_2_1_82_1"},{"key":"e_1_2_1_83_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2726902"},{"key":"e_1_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2016.130"},{"key":"e_1_2_1_85_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"e_1_2_1_86_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2016.05.013"},{"key":"e_1_2_1_87_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2018.01.053"},{"volume-title":"Proceedings of the International Conference on Learning Representations.","year":"2015","author":"Simonyan Karen","key":"e_1_2_1_88_1"},{"key":"e_1_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2016.12.021"},{"key":"e_1_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2722378"},{"volume-title":"Proceedings of the 48th Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 384--394","year":"2010","author":"Turian Joseph","key":"e_1_2_1_91_1"},{"volume-title":"Syed Mohsin Matloob Bokhari, and Mian Ahmad","year":"2017","author":"Usman Muhammad","key":"e_1_2_1_92_1"},{"key":"e_1_2_1_93_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2537200"},{"key":"e_1_2_1_94_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.08.059"},{"key":"e_1_2_1_95_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2018.02.030"},{"volume-title":"Xiangjian He, and Jinjun Chen.","year":"2018","author":"Usman Muhammad","key":"e_1_2_1_96_1"},{"key":"e_1_2_1_97_1","doi-asserted-by":"publisher","DOI":"10.1109\/TrustCom.2016.0114"},{"volume-title":"Xiangjian He, and Priyadarsi Nanda.","year":"2018","author":"Usman Muhammad","key":"e_1_2_1_98_1"},{"key":"e_1_2_1_99_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2017.2739744"},{"volume-title":"surveillance and law in a pre-crime society: Understanding the consequences of technology based strategies.Technol.-Led Polic. 20","year":"2011","author":"Brakel Rosamunde Van","key":"e_1_2_1_100_1"},{"key":"e_1_2_1_101_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-017-0923-9"},{"key":"e_1_2_1_102_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCC.2016.44"},{"key":"e_1_2_1_103_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2015.11.026"},{"key":"e_1_2_1_104_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.320"},{"key":"e_1_2_1_105_1","unstructured":"Wikipedia. 2017. Surveillance Issues in Smart Cities. Retrieved from https:\/\/en.wikipedia.org\/wiki\/Surveillance_issues_in_smart_cities.  Wikipedia. 2017. Surveillance Issues in Smart Cities. Retrieved from https:\/\/en.wikipedia.org\/wiki\/Surveillance_issues_in_smart_cities."},{"key":"e_1_2_1_106_1","unstructured":"Wikipedia. 2018. Comparison of Deep Learning Software. Retrieved from: https:\/\/en.wikipedia.org\/wiki\/Comparison_of_deep_learning_software.  Wikipedia. 2018. Comparison of Deep Learning Software. Retrieved from: https:\/\/en.wikipedia.org\/wiki\/Comparison_of_deep_learning_software."},{"key":"e_1_2_1_107_1","doi-asserted-by":"publisher","DOI":"10.1016\/0169-7439(87)80084-9"},{"key":"e_1_2_1_108_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.79"},{"key":"e_1_2_1_109_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2017.2678522"},{"key":"e_1_2_1_110_1","first-page":"2","article-title":"GrIMS: Green information-centric multimedia streaming framework in vehicular ad hoc networks","volume":"28","author":"Xu Changqiao","year":"2018","journal-title":"IEEE Trans. Circ. Syst. Vid. Technol."},{"volume-title":"Proceedings of the 14th International Conference on Data Engineering. IEEE, 324--331","year":"1998","author":"Xu Xiaowei","key":"e_1_2_1_111_1"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR\u201909)","year":"2009","author":"Yang Jianchao","key":"e_1_2_1_112_1"},{"key":"e_1_2_1_113_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2013.2262270"},{"key":"e_1_2_1_114_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jii.2016.03.004"},{"key":"e_1_2_1_115_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2014.2306328"},{"key":"e_1_2_1_116_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-3586-9"},{"key":"e_1_2_1_117_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2015.11.050"},{"key":"e_1_2_1_118_1","unstructured":"Paul Zikopoulos Chris Eaton etal 2011. Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media.  Paul Zikopoulos Chris Eaton et al. 2011. Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media."}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3323334","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3323334","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:17Z","timestamp":1750202597000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3323334"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,18]]},"references-count":118,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,5,31]]}},"alternative-id":["10.1145\/3323334"],"URL":"https:\/\/doi.org\/10.1145\/3323334","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"type":"print","value":"0360-0300"},{"type":"electronic","value":"1557-7341"}],"subject":[],"published":{"date-parts":[[2019,6,18]]},"assertion":[{"value":"2018-05-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-02-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-06-18","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}