Towards Citizen-Centered Smart Services Research Insights from a Project

Authors: Ejub Kajan, Emir Ugljanin, Ulfeta Marovac, Aldina Avdić, Adela Ljajić

Keywords: open government, smart cities, social machines

Abstract:

This paper presents research on citizen-centered smart services from the perspective of a long-term project. Initially intended for E-Government services in social, economic and biological domains, it is naturally extended to smart city services due to the common goals of citizen-centered services, common data sources, similar technologies, and the like. It is also overlapped with some international cooperation with similar goals. Both, E-Government and Smart Cities, feed with information that originates from their sensors, citizens and IoT, and, in return, provide smart services that aim to improve the quality of life and achieve more efficient management in the different environments in which they operate. The sensing is provided by listening to citizen opinions via social media, like Facebook, X (formerly, Twitter), and the like, and other Web 2.0 methods like crowdsensing and crowdsourcing, etc. The emerging world of IoT allows to sense some environmental phenomena like temperature, air pollutants, traffic congestion, fire, flooding, and to evidence some illegal behavior on the streets, for example. Development and deployment of citizen-centered services are analyzed through the prism of four dimensions, namely (1) modeling and decision-making, (2) sensing and analyzing, (3) willingness and engagement, and (4) openness and transparency. In addition, key technological enablers that drive the full achievement of these dimensions are briefly discussed. To address the challenges several issues are discusses. These include the enormous amount of data with high velocity, value and variety, the complexity of Serbian language and grammar with the absence of linguistic resources, and the limitations of IoT resources, to mention a few. These challenges are discussed by related work and a brief overview of proposed solutions with special emphasis on a framework, design of several specialized social machines, text processing in Serbian language, sentiment analysis, business process management and an excerpt of developed and deployed services. We briefly outline the main contributions of published work, including the key and technologies utilized, all supported by several experimental results. We conclude by identifying some unresolved problems and proposing future research directions.

References:

[1] E. ABU-SHANAB, Y. HARB, E-government research insights: Text mining analysis, Electronic Commerce Research and Applications, 38 (2019), p. 100892. [2] S. J. ANDRIOLE, Business impact of web 2.0 technologies, Commun. ACM, 53 (2010), pp. 67–79. [3] L. ATZORI, A. IERA, G. MORABITO, M. NITTI, The Social Internet of Things (SIoT) – When Social Networks Meet the Internet of Things: Concept, Architecture and Network Characterization, Computer Networks, 56 (2012). [4] A. AVDIĆ, Realizacija servisa pametnog zdravstva i njihova integracija u koncept pametnih gradova, Doktorska disertacija, (2021). [5] A. AVDIĆ , E. KAJAN, D. JANKOVIĆ , D. AVDIĆ, Towards context-aware smart healthcare platform, International Journal of Electrical Engineering and Computing, 3 (2019), pp. 26–31. [6] A. AVDIĆ, U. MAROVAC, D. JANKOVIĆ, Automated labeling of terms in medical reports in serbian, Turkish Journal of Electrical Engineering and Computer Sciences, 28 (2020), pp. 3285–3303. [7] A. R. AVDIĆ, U. A. MAROVAC, D. S. JANKOVIĆ, Normalization of health records in the serbian languagewith the aim of smart health services realization, Facta Universitatis, Series: Mathematics and Informatics, (2020), pp. 825–841. [8] T. BERNERS-LEE, M. FISCHETTI, Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by Its Inventor, Harper San Francisco, 1st ed., 1999. [9] K. BRITO, A. ALVES, S. E. FERREIRA, V. BUR´E GIO, G. . CARDOSO, S. ROMERO, Evolution of the web of social machines: A systematic review and research challenges, IEEE Transactions on Computational Social Systems, 7 (2020), pp. 373–388. [10] V. BUR´E GIO, N. FACI, E. KAJAN, Z. MAAMAR, M. SELLAMI, Bringing semantics to the social web, in 4th International Conference: Contemporary Problems of Mathematics, Mechanics and Informatics, Novi Pazar, 2016, pp. 27–28. [11] V. A. BUR´EGIO, E. KAJAN, M. SELLAMI, N. FACI, Z. MAAMAR, D. BENSLIMANE, Revisiting software engineering in the social era, IJSSOE, 6 (2016), pp. 36–46. [12] V. A. BUR´EGIO, Z. MAAMAR, S. L. MEIRA, An Architecture and Guiding Framework for the Social Enterprise, IEEE Internet Computing, 19 (January-February 2015). [13] L. CAMARGO, J. PAULETTI, A. PERNAS, A. YAMIN, Viso approach: A socialization proposal for the internet of things objects, Future Generation Computer Systems, 150 (2024), pp. 326–340. [14] M. CHEN, S. MAO, Y. LIU, Big data: A survey, Mobile networks and applications, 19 (2014), pp. 171–209. [15] H. CHOURABI, T. NAM, S. WALKER, J. GIL-GARCIA, S. MELLOULI, K. NAHON, T. PARDO, H. SCHOLL, Understanding Smart Cities: An Integrative Framework, in Proceedings of the 45th Hawaii International Conference on System Sciences (HICSS’2012), Jan 2012, pp. 2289–2297. [16] G. G. CHOWDHURY, Natural language processing, Annual review of information science and technology, 37 (2003), pp. 51–89. [17] N. F. F. DA SILVA, E. HRUSCHKA, E. R. HRUSCHKA, Tweet sentiment analysis with classifier ensembles, Decision Support Systems, 66 (2014), pp. 170 – 179. [18] T. H. DAVENPORT J. E. SHORT, The New Industrial Engineering: Information Technology and Business Process Redesign, Sloan Management Review, 31 (1990), pp. 19–41. [19] C. DIAMANTINI, A. MIRCOLI, D. POTENA, E. STORTI, Social information discovery enhanced by sentiment analysis techniques, Future Generation Computer Systems, (2018). [20] Ć. DOLIĆANIN, E. KAJAN, D. RANDJELOVIC, B. STOJANOVIC, Handbook of research on democratic strategies and citizen-centered E-government services, Information Science Reference, 2015. [21] F. DORLOFF, E. KAJAN, Balancing of heterogeneity and interoperability in e-business networks: The role of standards and protocols, IJEBR, 8 (2012), pp. 15–33. [22] M. DUMAS, M. LA ROSA, J. MENDLING, H. REIJERS, Fundamentals of Business Process Management, Springer, 978-3-642-33142-8, 2013. [23] M. GIATSOGLOU, M. G. VOZALIS, K. DIAMANTARAS, A. VAKALI, G. SARIGIANNIDIS, K. CHATZISAVVAS, Sentiment analysis leveraging emotions and word embeddings, Expert Systems with Applications, 69 (2017), pp. 214 – 224. [24] J. HENDLER, T. BERNERS-LEE, From the semantic web to social machines: A research challenge for ai on the world wide web, Artificial Intelligence, 174 (2010), pp. 156 – 161. [25] M. HU, B. LIU, Mining and summarizing customer reviews, in Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, 2004, pp. 168–177. [26] M. S. JANITA, F. J. F. MIRANDA, Quality in e-government services: A proposal of dimensions from the perspective of public sector employees, Telematics and Informatics, 35 (2018), pp. 457 – 469. [27] E. KAJAN, Software engineering a forty years research retrospective, Scientific Publications of the State University of Novi Pazar Series A: Applied Mathematics, Informatics and mechanics, 12 (2020), pp. 83–98. [28] E. KAJAN, A. AVDIĆ, U. MAROVAC, A. LJAJIĆ, G. ŠIMIĆ , J. STANKOVIĆ, Enhancing local economic development using collective intelligence, in 2015 23rd Telecommunications Forum Telfor (TELFOR), IEEE, 2015, pp. 882–885. [29] E. KAJAN, N. FACI, Z. MAAMAR, M. SELLAMI, E. UGLJANIN, H. KHEDDOUCI, D. STOJANOVIĆ, D. BENSLIMANE, Real-time tracking and mining of social media, Computer Science and Information Systems, 17 (2020), pp. 1–24. [30] E. KAJAN, Z. MAAMAR, Knowledge engineering in the social era, in 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys), Haikou, Hainan, China, December 20-22, 2021, IEEE, 2021, pp. 2150–2155. [31] E. KAJAN, A. PLJASKOVIĆ, A. CRNIŠANIN, Normalizacija tekstualnih dokumenata na sprskom jeziku u cilju efikasnijeg pretraživanja u sistemima e-uprave, Etran, Zlatibor, jun, (2012). [32] P. KOLLOCK, The economies of online cooperation: Gifts and public goods in cyberspace, Communities in cyberspace, 239 (1999). [33] C. KRSTEV, R. STANKOVIĆ, I. OBRADOVIĆ , D. VITAS, M. UTVIĆ, Automatic construction of a morphological dictionary of multi-word units, in Advances in Natural Language Processing: 7th International Conference on NLP, IceTAL 2010, Reykjavik, Iceland, August 16-18, 2010 7, Springer, 2010, pp. 226–237. [34] A. B. LJAJIĆ, Obrada negacije u kratkim neformalnim tekstovima u cilju poboljšanja klasifikacije sentimenta, Doktorska disertacija, (2019). [35] A. LJAJIC, U. MAROVAC, Improving sentiment analysis for twitter data by handling negation rules in the serbian language, Comput. Sci. Inf. Syst., 16 (2019), pp. 289–311. [36] A. LJAJIĆ, U. MAROVAC, A. AVDIĆ , Processing of negation in sentiment analysis for the serbian language, in IcETRAN 2017 Conference proceedings At, Serbia, June 2017. [37] A. LJAJIĆ , U. MAROVAC, M. STANKOVIĆ, Comparison of the influence of different normalization methods on tweet sentiment analysis in the serbian language, Facta Universitatis, Series: Mathematics and Informatics, (2019), pp. 683–696. [38] A. LJAJIĆ, M. STANKOVIĆ, U. MAROVAC, Detection of negation in the serbian language, in Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics, WIMS ’18, New York, NY, USA, 2018, Association for Computing Machinery. [39] V. LOWNDES, L. PRATCHETT, G. STOKER, Diagnosing and remedying the failings of official participation schemes: The clear framework, Social Policy and Society, 5 (2006), pp. 281–291. [40] Z. MAAMAR, V. A. BUR´EGIO, M. SELLAMI, N. S. ROSA, Z. PENG, Z. SUBIN, N. PRAKASH, D. BENSLIMANE, R. SILVA, Bridging the gap between the business and social worlds: A data artifact-driven approach, Trans. Large Scale Data Knowl. Centered Syst., 35 (2017), pp. 27–49. [41] Z. MAAMAR, E. KAJAN, M. AL-KHAFAJIY, M. DOHAN, A. FAYOUMI, F. YAHYA, A multi-type artifact framework for cyber-physical, social systems design and development, Internet Things, 22 (2023), p. 100820. [42] Z. MAAMAR., E. KAJAN, I. GUIDARA, L. MOCTAR-M’BABA, M.SELLAMI, Bridging the gap between business processes and iot, in IDEAS 2020: 24th International Database Engineering & Applications Symposium, Seoul, Republic of Korea, August 12-14, 2020, ACM, 2020, pp. 2:1–2:10. [43] U. MAROVAC, A. AVDIĆ, D. JANKOVIĆ, S. MAROVAC, Creating resources for marking diagnoses in electronic health reports in serbian, (2020). [44] U. MAROVAC, A. AVDIC, A. LJAJIC, Creating a stop word dictionary in serbian, Scientific Publications of the State University of Novi Pazar Series A: Applied Mathematics, Informatics and mechanics, 13 (2021), pp. 17–26. [45] U. MAROVAC, A. LJAJIC, E. KAJAN, A. AVDIC, Towards the lexical resources for sentiment-reach informal texts – the serbian language case, in V CPMMI conference, Novi Pazar, Serbia, 2018, pp. 1–10. [46] U. MAROVAC, A. PLJASKOVIC, A. CRNISANIN, E. KAJAN, N-gram analysis of text documents in serbian language, in In Proceedings of the 20th Telecommunications Forum (TELFOR), Belgrade, Serbia, 2012, pp. 1385–1388. [47] U. MAROVAC, A. PLJASKOVIĆ, A. LJAJIĆ, E. KAJAN, N-gram analysis of text documents in serbian language, in Proceedings of the 20th Telecommunications Forum (TELFOR), Belgrade, Serbia, 2012, pp. 1385–1388. [48] H. MILI, G. TREMBLAY, G. B. JAOUDE, E. LEFEBVRE, L. ELABED, G. EL-BOUSSAIDI, Business process modeling languages: Sorting through the alphabet soup, ACM Comput. Surv., 43 (2010), pp. 4:1–4:56. [49] N. MILOŠEVIĆ, Stemmer for serbian language, arXiv preprint arXiv:1209.4471, (2012). [50] W. J. MITCHELL, Intelligent Cities. http://www.uoc.edu/uocpapers/5/dt/eng/mitchell.pdf, 2007. [51] A. NIGAM, N. CASWELL, Business Artifacts: An Approach to Operational Specification, IBM Systems Journal, 42 (2003), pp. 428–445. [52] M. PANKOWSKA, National frameworks: survey on standardization of e-government documents and processes for interoperability, Journal of theoretical and applied electronic commerce research, 3 (2008), pp. 64 – 82. [53] J. ROWLEY, The wisdom hierarchy: representations of the dikw hierarchy, Journal of information science, 33 (2007), pp. 163–180. [54] N. SHADBOLT, Knowledge acquisition and the rise of social machines, International Journal of Human-Computer Studies, 71 (2013), pp. 200 – 205. 25 Years of Knowledge Acquisition. [55] G. ŠIMIĆ , Z. JEREMIĆ, E. KAJAN, D. RANDJELOVIĆ , A. PRESNALL, A framework for delivering e-government support, Acta Polytechnica Hungarica, 11 (2014), pp. 79–96. [56] E. UGLJANIN, Platforma za intrakciju sa društvenim mrežama i internetom stvari u pametnim gradovima, Doktorska disertacija, (2023). [57] E. UGLJANIN, E. KAJAN, Z. MAAMAR, M. ASIM, V. BUR´E GIO, Immersing citizens and things into smart cities: a social machine-based and data artifact-driven approach, Computing, (2020), pp. 1–20. [58] E. UGLJANIN, D. STOJANOVIĆ, E. KAJAN, Z. MAAMAR, B2s4b: A platform for smart city business processes management and adaptation, Studies in Informatics and Control, 31 (2022), pp. 75–86. [59] E. UGLJANIN, D. H. STOJANOVIĆ, E. KAJAN, Z. MAAMAR, Initiating and tracking social actions to adapt and improve smart city’s business processes, in 2017 25th Telecommunication Forum (TELFOR), IEEE, 2017, pp. 1–4. [60] E. UGLJANIN, D. STOJANOVIĆ, E. KAJAN, Z. MAAMAR, Re-engineering of smart city’s business processes based on social networks and internet of things, Facta Universitatis, Series: Automatic Control and Robotics, 16 (2018), pp. 275–286. [61] J. A. ZACHMAN, The information systems management system: A framework for planning, SIGMIS Database, 9 (1977), pp. 8–13.