The technology of scientific and practical communications: InGraph case study

Authors

Dmytro Domin, InGraph LTD; Dimitri Lunin, InGraph LTD; Olena Domina, Scientific Route OÜ; Anton Komyshan, Simon Kuznets Kharkiv National University of Economics; Kristina Veski Saparali; Vitalii Osadchyi, Translation.in.ua
Keywords: Information-technological Platform InGraph, scientific and practical communications, Actors, scientific content, quality of scientific content, effectiveness of scientific activity, feedback mechanism for quality assessment, capitalization of scientific works

Synopsis

The InGraph Platform is presented as an information-technological product's scientific and practical implementation. The logical, structural, informational, and technological implementation of this Platform provides a usable service to all subjects of scientific activity who create scientific works and use them: authors, reviewers, as well as end users engaged in science and practice. The platform's mechanisms, which enable the interaction of all its users with each other, form the technology of scientific and practical communications on the principle «everyone gets what s/he needs, at a minimal time cost». Such technology, implemented through the Platform, creates the following possibilities for its users: self-realization, altruistic opportunities, social prospects, economic opportunities, and organizational capabilities. This allows us to argue about the multi-vector nature of the Platform, which creates an alternative model for the dissemination of scientific knowledge.

The InGraph Platform's concept implements the transition from a one-dimensional model of «scientist for scientist» or «science for science» to a two-dimensional model of «science for improving human well-being», thereby emphasizing the provision of practical needs based on the results of research as a priority for science. Such needs can be considered in the context of improving human well-being. Opportunities for users to find and receive the scientific and practical information they need are realized owing to the developed principle based on three-level access to content.

The developed feedback mechanism implemented on the Platform makes it possible to assess the objectivity of reviewers and offer opportunities for rating scientists, teams, and institutions while creating a comfort zone for users of scientific content. It also prevents events associated with the evaluation of content by incompetent users and minimizes the risks of collusion schemes between subjects of scientific activity.

The proposed procedure for assessing the price of scientific works submitted by authors on the basis of closed access, in the form of a function of their scientific quality and level of scientific novelty, makes it possible to implement the transparency of the formation of the cost of scientific content. The transactional mechanism of the Platform implements such a system of distribution of goods in which the dominant role is given to the authors of scientific works. Authors, at the same time, always have the opportunity to personally choose whether to provide their works in closed or open access, without any payment for publication in the latter case.

ISBN 978-9916-9850-0-7 (eBook)
ISBN 978-9916-9850-1-4 (EPUB)

ISBN 978-9916-9516-9-9 (Hardback)

--------------------------------------------------------------------------------------------------------------

How to Cite: Domin, D., Lunin, D., Domina, O., Komyshan, A., Veski Saparali, K., Osadchyi, V.; Domin, D. (Ed.) (2022). The technology of scientific and practical communications: InGraph case study. Tallinn: Scientific Route OÜ, 184. doi: https://doi.org/10.21303/978-9916-9516-9-9

--------------------------------------------------------------------------------------------------------------

Indexing:

arch engpaper Zenodo45 openaire45 scilitdimen ester

Chapters

  • Chapter 1 Effectiveness of scientific activity and motivation for its subjects
  • Chapter 2 The information-technology platform InGraph: The essence and concept of development
  • Chapter 3 Information technology solutions for the Author’s cabinet
  • Chapter 4 Information-technological solutions for the Reviewer’s account
  • Chapter 5 Efficiency of feedback-based scientific and practical communication technology provided by the InGraph platform solutions

Downloads

Download data is not yet available.

Author Biographies

Dmytro Domin, InGraph LTD

Doctor of Technical Sciences, Professor
Member of the Management Board
https://orcid.org/0000-0002-7946-3651
Corresponding author
E-mail: prtcopy@gmail.com

Dimitri Lunin, InGraph LTD
Olena Domina, Scientific Route OÜ

Member of the Management Board
https://orcid.org/0000-0002-3093-3085

Anton Komyshan, Simon Kuznets Kharkiv National University of Economics

Senior Software Engineer
https://orcid.org/0000-0002-3958-9698

Kristina Veski Saparali
Vitalii Osadchyi, Translation.in.ua

References

Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102 (46), 16569–16572. doi: https://doi.org/10.1073/pnas.0507655102

Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69 (1), 131–152. doi: https://doi.org/10.1007/s11192-006-0144-7

Egghe, L. (2010). The Hirsch index and related impact measures. Annual Review of Information Science and Technology, 44 (1), 65–114. doi: https://doi.org/10.1002/aris.2010.1440440109

Kosmulski, М. (2006). A new Hirsch-type index saves time and works equally well as the original h-index. International Society for Sciento- metrics and Informetrics, 3 (2), 4–6.

Zhang, C.-T. (2009). The e-Index, Complementing the h-Index for Excess Citations. PLoS ONE, 4 (5), e5429. doi: https://doi.org/10.1371/journal.pone.0005429

Gagolewski, M., Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174. doi: https://doi.org/10.1016/j.ins.2013.12.004

Biloshchytskyi, A., Kuchansky, A., Andrashko, Y., Biloshchytska, S., Kuzka, O., Terentyev, О. (2017). Evaluation methods of the results of scientific research activity of scientists based on the analysis of publication citations. Eastern-European Journal of Enterprise Technologies, 3 (2 (87)), 4–10. doi: https://doi.org/10.15587/1729-4061.2017.103651

Šubelj, L., van Eck, N. J., Waltman, L. (2016). Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods. PLOS ONE, 11 (4), e0154404. doi: https://doi.org/10.1371/journal.pone.0154404

Bolelli, L., Ertekin, S., Giles, C. L. (2006). Clustering scientific literature using sparse citation graph analysis. European Conference on Principles of Data Mining and Knowledge Discovery. Berlin, Heidelberg: Springer, 30–41. doi: https://doi.org/10.1007/11871637_8

Gomaa, W. H., Fahmy, A. A. (2013). A survey of text similarity approaches. International Journal of Computer Applications, 68 (13), 13–18.

Islam, A., Milios, E., Keselj, V. (2012). Text similarity using google trigrams. Advances in Artificial Intelligence. Berlin, Heidelberg: Sprin- ger, 312–317. doi: http://doi.org/10.1007/978-3-642-30353-1_29

Dhillon, I. S., Guan, Y., Kulis, B. (2007). Weighted Graph Cuts without Eigenvectors A Multilevel Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29 (11), 1944–1957. doi: https://doi.org/10.1109/tpami.2007.1115

Waltman, L., van Eck, N. J. (2013). A smart local moving algorithm for large-scale modularity-based community detection. The European Physical Journal B, 86 (11). doi: https://doi.org/10.1140/epjb/e2013-40829-0

Blondel, V. D., Guillaume, J.-L., Lambiotte, R., Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008 (10), P10008. doi: https://doi.org/10.1088/1742-5468/2008/10/p10008

Yang, J., Leskovec, J. (2013). Overlapping community detection at scale: a nonnegative matrix factorization approach. Proceedings of the sixth ACM international conference on Web search and data mining. ACM, 587–596. doi: https://doi.org/10.1145/2433396.2433471

Pons, P., Latapy, M. (2006). Computing Communities in Large Networks Using Random Walks. Journal of Graph Algorithms and Applications, 10 (2), 191–218. doi: https://doi.org/10.7155/jgaa.00124

Lizunov, P., Biloshchytskyi, A., Kuchansky, A., Andrashko, Y., Biloshchytska, S. (2019). Improvement of the method for scientific publications clustering based on n-gram analysis and fuzzy method for selecting research partners. Eastern-European Journal of Enterprise Technologies, 4 (4 (100)), 6–14. doi: https://doi.org/10.15587/1729-4061.2019.175139

Islam, A., Inkpen, D. (2008). Semantic text similarity using corpus-based word similarity and string similarity. ACM Transactions on Knowledge Discovery from Data, 2 (2), 1–25. doi: https://doi.org/10.1145/1376815.1376819

Teslia, I., Latysheva, T. (2016). Development of conceptual frameworks of matrix management of project and programme portfolios. Eastern-European Journal of Enterprise Technologies, 1 (3 (79)), 12–18. doi: https://doi.org/10.15587/1729-4061.2016.61153

Dumais, S. T. (2005). Latent semantic analysis. Annual Review of Information Science and Technology, 38 (1), 188–230. doi: https://doi.org/10.1002/aris.1440380105

Lizunov, P., Biloshchytskyi, A., Kuchansky, A., Andrashko, Y., Biloshchytska, S. (2020). The use of probabilistic latent semantic analysis to identify scientific subject spaces and to evaluate the completeness of covering the results of dissertation studies. Eastern-European Journal of Enterprise Technologies, 4 (4 (106)), 21–28. doi: https://doi.org/10.15587/1729-4061.2020.209886

Glänzel, W. (2012). Bibliometric methods for detecting and analysing emerging research topics. El Profesional de La Informacion, 21 (2), 194–201. doi: https://doi.org/10.3145/epi.2012.mar.11

Ovelgönne, M., Geyer-Schulz, A. (2013). An ensemble learning strategy for graph clustering. Contemporary Mathematics, 588, 187–205. doi: https://doi.org/10.1090/conm/588/11701

Biloshchytskyi, A., Kuchansky, A., Andrashko, Y., Biloshchytska, S., Kuzka, O., Shabala, Y., Lyashchenko, T. (2017). A method for the identification of scientists’ research areas based on a cluster analysis of scientific publications. Eastern-European Journal of Enterprise Technologies, 5 (2 (89), 4–11. doi: https://doi.org/10.15587/1729-4061.2017.112323

Hirsch, J. E. (2007). Does the h index have predictive power? Proceedings of the National Academy of Sciences, 104 (49), 19193–19198. doi: https://doi.org/10.1073/pnas.0707962104

Petersen, A. M., Stanley, H. E., Succi, S. (2011). Statistical regularities in the rank-citation profile of scientists. Scientific Reports, 1 (1). doi: https://doi.org/10.1038/srep00181

Schulz, C., Mazloumian, A., Petersen, A. M., Penner, O., Helbing, D. (2014). Exploiting citation networks for large-scale author name disambiguation. EPJ Data Science, 3 (1). doi: https://doi.org/10.1140/epjds/s13688-014-0011-3

Digital Object Identifier System. Available at: https://www.doi.org/

Biloshchytskyi, A., Myronov, O., Reznik, R., Kuchansky, A., Andrashko, Y., Paliy, S., Biloshchytska, S. (2017). A method to evaluate the scientific activity quality of HEIs based on a scientometric subjects presentation model. Eastern-European Journal of Enterprise Technologies, 6 (2 (90)), 16–22. doi: https://doi.org/10.15587/1729-4061.2017.118377

Sreeramana, A. P., Kumar, P. M. (2016). ABC Model of Research Productivity and Higher Educational Institutional Ranking. International Journal of Education and Management Engineering, 6 (6), 74–84. doi: https://doi.org/10.5815/ijeme.2016.06.08

Lakshmi, T. M., Venkatesan, V. P., Martin, A. (2016). An Identification of Better Engineering College with Conflicting Criteria using Adaptive TOPSIS. International Journal of Modern Education and Computer Science, 8 (5), 19–31. doi: https://doi.org/10.5815/ijmecs.2016.05.03

Baden-Fuller, C., Ravazzolo, F., Schweizer, T. (2000). Making and Measuring Reputations. Long Range Planning, 33 (5), 621–650. doi: https://doi.org/10.1016/s0024-6301(00)00064-9

Wolszczak-Derlacz, J. (2017). An evaluation and explanation of (in)efficiency in higher education institutions in Europe and the U.S. with the application of two-stage semi-parametric DEA. Research Policy, 46 (9), 1595–1605. doi: https://doi.org/10.1016/j.respol.2017.07.010

Kuchansky, А., Andrashko, Yu., Biloshchytskyi, А., Danchenko, O., Ilarionov, O., Vatskel, I., Honcharenko, T. (2018). The method for evaluation of educational environment subjects’ performance based on the calculation of volumes of m-simplexes. Eastern-European Journal of Enterprise Technologies, 2 (4 (92)), 15–25. doi: https://doi.org/10.15587/1729-4061.2018.126287

Michelucci, D., Foufou, S. (2004). Using Cayley-Menger determinants for geometric constraint solving. Proceedings of the 9th ACM symposium on Solid modeling and applications. Eurographics Association, 285–290.

Biloshchytskyi, A., Kuchansky, A., Paliy, S., Biloshchytska, S., Bronin, S., Andrashko, Y. et al. (2018). Development of technical component of the methodology for projectvector management of educational environments. Eastern-European Journal of Enterprise Technologies, 2 (2 (92)), 4–13. doi: https://doi.org/10.15587/1729-4061.2018.126301

Kolesnіkov, O., Gogunskii, V., Kolesnikova, K., Lukianov, D., Olekh, T. (2016). Development of the model of interaction among the project, team of project and project environment in project system. Eastern-European Journal of Enterprise Technologies, 5 (9 (83)), 20–26. doi: https://doi.org/10.15587/1729-4061.2016.80769

Kolesnikova, K., Lukianov, D., Gogunskii, V., Iakovenko, V., Oborska, G., Negri, A. et al. (2017). Communication management in social networks for the actualization of publications in the world scientific community on the example of the network researchgate. Eastern-European Journal of Enterprise Technologies, 4 (3 (88)), 27–35. doi: https://doi.org/10.15587/1729-4061.2017.108589

Hnatiienko, H., Snytyuk, V., Tmienova, N., Voloshyn, O. (2021). Determining the effectiveness of scientific research of universities staff. CEUR Workshop Proceedings, 2833, 164–176.

Otte, E., Rousseau, R. (2002). Social network analysis: a powerful strategy, also for the information sciences. Journal of Information Science, 28 (6), 441–453. doi: https://doi.org/10.1177/016555150202800601

Barab si, A. L., Jeong, H., N da, Z., Ravasz, E., Schubert, A., Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and Its Applications, 311 (3-4), 590–614. doi: https://doi.org/10.1016/s0378-4371(02)00736-7

Hou, H., Kretschmer, H., Liu, Z. (2007). The structure of scientific collaboration networks in Scientometrics. Scientometrics, 75 (2), 189–202. doi: https://doi.org/10.1007/s11192-007-1771-3

Newman, M. E. J. (2001). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, 98 (2), 404–409. doi: https://doi.org/10.1073/pnas.98.2.404

Garcez, M., Sbragia, R., Kruglianskas, I. (2014). Factors for selection partners in innovation projects – qualitative evidences from non-equity bilateral alliances in Brazilian petrochemical leader. Review of Administration and Innovation – RAI, 11/2, 241–272. doi: https://doi.org/10.5773/rai.v11i2.1292

Feng, W. D., Chen, J., Zhao, C. J. (2000). Partners Selection Process and Optimization Model for Virtual corporations Based on Genetic Algorithms. Journal of Tsinghua University (Science and Technology), 40, 120–124.

Biloshchytskyi, A., Kuchansky, A., Andrashko, Y., Omirbayev, S., Mukhatayev, A., Faizullin, A., Toxanov, S. (2021). Development of the set models and a method to form information spaces of scientific activity subjects for the steady development of higher education establishments. Eastern-European Journal of Enterprise Technologies, 3 (2 (111)), 6–14. doi: https://doi.org/10.15587/1729-4061.2021.233655

Xu, H., Kuchansky, A., Gladka, M. (2021). Devising an individually oriented method for selection of scientific activity subjects for implementing scientific projects based on scientometric analysis. Eastern-European Journal of Enterprise Technologies, 6 (3 (114)), 93–100. doi: https://doi.org/10.15587/1729-4061.2021.248040

A Guide to the Project Management Body of Knowledge (PMBOK® Guide) (2016). Project Management Institute, 618. Available at: https://pdfroom.com/books/a-guide-to-the-project-management-body-of- knowledge-pmbok-guide/Zavd9vZOgKD

Cartwright, C., Yinger, M. (2007). Project management competency development framework. Paper presented at PMI® Global Congress 2007 – EMEA. Budapest: Newtown Square: Project Management Institute.

Pollack, J., Matous, P. (2019). Testing the impact of targeted team building on project team communication using social network analysis. International Journal of Project Management, 37 (3), 473–484. doi: https://doi.org/10.1016/j.ijproman.2019.02.005

Fu, F., Hauert, C., Nowak, M. A., Wang, L. (2008). Reputation-based partner choice promotes cooperation in social networks. Physical Review E, 78 (2). doi: https://doi.org/10.1103/physreve.78.026117

Kuchansky, A., Biloshchytskyi, A., Andrashko, Y., Wang, Y. (2022). Devising a competence method to build information spaces for executors of educational projects in a dynamic environment. Eastern-European Journal of Enterprise Technologies, 1 (3 (115)), 66–73. doi: https://doi.org/10.15587/1729-4061.2022.253043

Clarivate. Available at: https://clarivate.com/

ScimagoJR. Available at: https://www.scimagojr.com

Scopus. Available at: https://www.scopus.com/

Eastern-European Journal of Enterprise Technologies. Available at: https://jet.com.ua/en/

Archive. Eastern-European Journal of Enterprise Technologies. Available at: http://journals.uran.ua/eejet/issue/archive

PC TECHNOLOGY CENTER. Available at: https://entc.com.ua/en/

EUREKA: Physics and Engineering. Available at: http://journal.eu-jr.eu/engineering/

Scientific Route O . Available at: https://route.ee/en

ScienceRise: Pharmaceutical Science. Available at: https://pharm.sr.org.ua/en/

Archive. ScienceRise: Pharmaceutical Science. Available at: http://journals.uran.ua/sr_pharm/issue/archive

Metrics. Google Scholar. Available at https://scholar.google.com/citations?view_op=metrics_intro&hl=en

Webometrics Ranking of World Universities. Available at: https://www.webometrics.info/en

InGraph. Available at: https://ingraph.org/

ORCID. Available at: https://orcid.org/

Domina, O. (2020). Features of finding optimal solutions in network planning, EUREKA: Physics and Engineering, 6, 82–96. doi: https://doi.org/10.21303/2461-4262.2020.001471

Frolova, L. (2011). Identification provision of energy saving on the basis of audit process moulding machines shaking. Technology Audit and Production Reserves, 2 (2 (2)), 8–13. doi: https://doi.org/10.15587/2312-8372.2011.4859

Vasenko, Yu. A. (2011). Wear resistance of titanium doped simulation of iron on the data passive experiment. Technology Audit and Production Reserves, 2 (2 (2)), 3–8. doi: https://doi.org/10.15587/2312-8372.2011.4858

Domina, O. (2021). Solution of the compromise optimization problem of network graphics on the criteria of uniform personnel loading and distribution of funds. Technology Audit and Production Reserves, 1 (4 (57)), 14–21. doi: https://doi.org/10.15587/2706-5448.2021.225527

Demin, D. (2017). Strength analysis of lamellar graphite cast iron in the «carbon (C) – carbon equivalent (Ceq)» factor space in the range of C=(3.425–3.563) % and Ceq=(4.214–4.372) %. Technology Audit and Production Reserves, 1 (1 (33)), 24–32. doi: https://doi.org/10.15587/2312-8372.2017.93178

Demin, D. (2018). Investigation of structural cast iron hardness for castings of automobile industry on the basis of construction and analysis of regression equation in the factor space «carbon (C) – carbon equivalent (Ceq)». Technology Audit and Production Reserves, 3 (1 (41)), 29–36. doi: https://doi.org/10.15587/2312-8372.2018.109097

Domin, D. (2013). Artificial orthogonalization in searching of optimal control of technological processes under uncertainty conditions. Eastern-European Journal of Enterprise Technologies, 5 (9 (65)), 45–53. doi: https://doi.org/10.15587/1729-4061.2013.18452

Domina, O. (2020). Selection of alternative solutions in the optimization problem of network diagrams of project implementation. Technology Audit and Production Reserves, 4 (4 (54)), 9–22. doi: https://doi.org/10.15587/2706-5448.2020.210848

Akimov, O., Penzev, P., Marynenko, D., Saltykov, L. (2018). Identification of the behavior of properties of a cold-hardening glass-liquid mixture with propylene-carbonate different in dosing components. Technology Audit and Production Reserves, 2 (3 (46)), 4–9. doi: https://doi.org/10.15587/2312-8372.2019.169748

Chibichik, O., Sil’chenko, K., Zemliachenko, D., Korchaka, I., Makarenko, D. (2017). Investigation of the response surface describing the mathematical model of the effects of the Al/Mg rate and temperature on the Al-Mg alloy castability. ScienceRise, 5 (2), 42–45. doi: https://doi.org/10.15587/2313-8416.2017.101923

Demin, D. (2017). Synthesis of optimal control of technological processes based on a multialternative parametric description of the final state. Eastern-European Journal of Enterprise Technologies, 3 (4 (87)), 51–63. doi: https://doi.org/10.15587/1729-4061.2017.105294

Demin, D. (2019). Development of «whole» evaluation algorithm of the control quality of «cupola – mixer» melting duplex process. Technology Audit and Production Reserves, 3 (1 (47)), 4–24. doi: https://doi.org/10.15587/2312-8372.2019.174449

Kharchenko, S., Barsuk, A., Karimova, N., Nanka, A., Pelypenko, Y., Shevtsov, V. et al. (2021). Mathematical model of the mechanical properties of Ti-alloyed hypoeutectic cast iron for mixer blades. EUREKA: Physics and Engineering, 3, 99–110. doi: https://doi.org/10.21303/2461-4262.2021.001830

Kuryn, M. (2011). Determination of optimum performance liquid glass of magnetization mixtures with liquid glass. Technology Audit and Production Reserves, 2 (2 (2)), 14–20. doi: https://doi.org/10.15587/2312-8372.2011.4860

Kuryn, M. (2012). Synthesis of cold-hardening mixtures with given set of properties and optimization of technological regimes of their manufacturing. Technology Audit and Production Reserves, 1 (1 (3)), 25–29. doi: https://doi.org/10.15587/2312-8372.2012.4872

Demin, D. (2013). Adaptive modeling in problems of optimal control search termovremennoy cast iron. Eastern-European Journal of Enterprise Technologies, 6 (4 (66)), 31–37. doi: https://doi.org/10.15587/1729-4061.2013.19453

Makarenko, D. (2017). Investigation of the response surfaces describing the mathematical model of the influence of temperature and BeO content in the composite materials on the yield and ultimate strength. Technology Audit and Production Reserves, 3 (3 (35)), 13–17. doi: https://doi.org/10.15587/2312-8372.2017.104895

Demin, D. (2017). Synthesis of nomogram for the calculation of suboptimal chemical composition of the structural cast iron on the basis of the parametric description of the ultimate strength response surface. ScienceRise, 8 (37), 36–45. doi: https://doi.org/10.15587/2313-8416.2017.109175

Frolova, L., Shevchenko, R., Shpyh, A., Khoroshailo, V., Antonenko, Y. (2021). Selection of optimal Al-Si combinations in cast iron for castings for engineering purposes. EUREKA: Physics and Engineering, 2, 99–107. doi: http://doi.org/10.21303/2461-4262.2021.001694

Dotsenko, Y., Dotsenko, N., Tkachyna, Y., Fedorenko, V., Tsybulskyi, Y. (2018). Operation optimization of holding furnaces in special casting shops. Technology Audit and Production Reserves, 6 (1 (44)), 18–22. doi: https://doi.org/10.15587/2312-8372.2018.150585

Dymko, I. (2018). Choice of the optimal control strategy for the duplex-process of induction melting of constructional iron. EUREKA: Physics and Engineering, 4, 3–13. doi: https://doi.org/10.21303/2461-4262.2018.00669

Domina, O., Lunin, D., Barabash, O., Balynska, O., Paida, Y., Mikhailova, L., Niskhodovska, O. (2018). Algorithm for selecting the winning strategies in the processes of managing the state of the system «supplier – consumer» in the presence of aggressive competitor. Eastern- European Journal of Enterprise Technologies, 6 (3 (96)), 48–61. doi: https://doi.org/10.15587/1729-4061.2018.152793

Cover for The technology of scientific and practical communications: InGraph case study
Published
December 13, 2022

Details about the available publication format: PDF

PDF
ISBN-13 (15)
978-9916-9850-0-7

Details about the available publication format: EPUB

EPUB
ISBN-13 (15)
978-9916-9850-1-4

Details about the available publication format: HARDBACK

HARDBACK
ISBN-13 (15)
978-9916-9516-9-9