scholarly journals Data, Models, and Decisions: How We Can Shape Our World by Not Predicting the Future

2021 ◽  
pp. 297-302
Author(s):  
Niki Popper
Keyword(s):  
Data Models ◽  
Modelling And Simulation ◽  
Social Discourse ◽  
The Future

AbstractModelling and simulation can be used for different goals and purposes. Prediction is only one of them, and, as this chapter highlights, it might not be the main goal—even if it was in the spotlight during the COVID-19 crisis. Predicting the future is a vanity. Instead, we aim to prevent certain events in the future by describing scenarios, or, even better, we try to actively shape the future according to our social, technological, or economic goals. Thus, modellers can contribute to debate and social discourse; this is one of the aims of Digital Humanism.

A Study of XML Models for Data Mining

Data Mining ◽  
2013 ◽  
pp. 1-27
Author(s):  
Sangeetha Kutty ◽  
Richi Nayak ◽  
Tien Tran
Keyword(s):  
Data Mining ◽  
Data Model ◽  
Data Representation ◽  
Data Models ◽  
Data Mining Techniques ◽  
Xml Documents ◽  
The Future ◽  
Future Data

With the increasing number of XML documents in varied domains, it has become essential to identify ways of finding interesting information from these documents. Data mining techniques can be used to derive this interesting information. However, mining of XML documents is impacted by the data model used in data representation due to the semi-structured nature of these documents. In this chapter, we present an overview of the various models of XML documents representations, how these models are used for mining, and some of the issues and challenges inherent in these models. In addition, this chapter also provides some insights into the future data models of XML documents for effectively capturing its two important features, structure and content, for mining.

A Study of XML Models for Data Mining

2011 ◽  
pp. 1-28
Author(s):  
Sangeetha Kutty ◽  
Richi Nayak ◽  
Tien Tran
Keyword(s):  
Data Mining ◽  
Data Model ◽  
Data Representation ◽  
Data Models ◽  
Data Mining Techniques ◽  
Xml Documents ◽  
The Future ◽  
Future Data

With the increasing number of XML documents in varied domains, it has become essential to identify ways of finding interesting information from these documents. Data mining techniques can be used to derive this interesting information. However, mining of XML documents is impacted by the data model used in data representation due to the semi-structured nature of these documents. In this chapter, we present an overview of the various models of XML documents representations, how these models are used for mining, and some of the issues and challenges inherent in these models. In addition, this chapter also provides some insights into the future data models of XML documents for effectively capturing its two important features, structure and content, for mining.

MoSeS: Modelling and Simulation for e-Social Science

2009 ◽  
Vol 367 (1898) ◽  
pp. 2781-2792 ◽  
Author(s):  
Paul Townend ◽  
Jie Xu ◽  
Mark Birkin ◽  
Andy Turner ◽  
Belinda Wu
Keyword(s):  
Social Science ◽  
Modelling And Simulation ◽  
Simulation Methodology ◽  
National Centre ◽  
The Future ◽  
Demographic Processes ◽  
Architecture Simulation ◽  
The Uk

MoSeS (Modelling and Simulation for e-Social Science) is a research node of the National Centre for e-Social Science. MoSeS uses e-Science techniques to execute an events-driven model that simulates discrete demographic processes; this allows us to project the UK population 25 years into the future. This paper describes the architecture, simulation methodology and latest results obtained by MoSeS.

scholarly journals THEORETICAL AND PRACTICAL UNIVERSALITY OF MEMORY AND OBLIVION CATEGORIES IN LITERATURE

2019 ◽  
pp. 70-75
Author(s):  
Valerii Bren
Keyword(s):  
Contemporary Art ◽  
Cultural Memory ◽  
Theoretical Basis ◽  
Past Experience ◽  
Literary Studies ◽  
Social Discourse ◽  
The Past ◽  
Balanced Approach ◽  
The Future ◽  
Individual Memory

This research is devoted to the concepts of memory and oblivion in terms of the universality of these categories for literature, and their interdisciplinary in history, culturology, and sociology. The theoretical basis for analysis in the artistic text is shown on the example of Ukrainian and foreign researchers, specified and illustrated manifestations in the Ukrainian novels by Y. Andrukhovych, O. Zabuzhko, S. Zhadan, O. Irvanetz, etc. Literature is the centre of individual and national cultural memory and a means of creating of it. However, it becomes a platform for social discourse of memory, as well as the preservation of individual memory as a genetic key in the text. Consequently, modern literary studies require a well-balanced approach and analysis of the ways, means, methods, and forms of its functioning in contemporary art. Such approach will enable an understanding of the past experience, as well as assessments of contemporary imprints of events in the future, on a qualitatively new level.

The Contribution of Data Modeling to the Future Development of CAD/CAM Databases

1991 ◽  
Author(s):  
Charles M. Eastman
Keyword(s):  
Future Development ◽  
Data Model ◽  
Data Modeling ◽  
Data Models ◽  
Product Data ◽  
Knowledge Domains ◽  
The Future ◽  
Cad Cam

Abstract Data modeling is proposed as a means to address the complexities of CAD/CAM databases. The distinctions between product data models and those in general databases are reviewed. A data model, called EDM, is presented that incorporates features that are defined to response to these differences. A review is given of data modeling analyses carried out thus far regarding database extensibility, including support for open-ended knowledge domains.

Translating Schemas Between Data Modelling Languages

2011 ◽  
pp. 1-15
Author(s):  
Peter McBrien
Keyword(s):  
Information Systems ◽  
Programming Languages ◽  
Data Model ◽  
Object Oriented ◽  
Data Models ◽  
Object Oriented Programming ◽  
Data Modelling ◽  
Modelling Language ◽  
Modelling Languages ◽  
The Future

Data held in information systems is modelled using a variety of languages, where the choice of language may be decided by functional concerns as well as non-technical concerns. This chapter focuses on data modelling languages, and the challenges faced in mapping schemas in one data modelling language into another data modelling language. We review the ER, relational and UML modelling languages (the later being representative of object oriented programming languages), highlighting aspects of each modelling language that are not representable in the others. We describe how a nested hypergraph data model may be used as an underlying representation of data models, and hence present the differences between the modelling languages in a more precise manner. Finally, we propose a platform for the future building of an automated procedure for translating schemas from one modelling language to another.

scholarly journals Modeling and Simulation of Processes in a Factory of the Future

2020 ◽  
Vol 10 (13) ◽  
pp. 4503 ◽  
Author(s):  
Patrik Grznár ◽  
Milan Gregor ◽  
Martin Krajčovič ◽  
Štefan Mozol ◽  
Marek Schickerle ◽  
...  
Keyword(s):  
Intelligent Manufacturing ◽  
Modelling And Simulation ◽  
Planning And Control ◽  
Current Trends ◽  
The Future ◽  
Factory Of The Future ◽  
The Individual ◽  
And Control ◽  
Behavioural Management ◽  
Factories Of The Future

Current trends in manufacturing, which are based on customisation and gradually customised production, are becoming the main initiator for the development of new manufacturing approaches. New manufacturing approaches are counted as the application of new behavioural management patterns that calculate the retained competencies of decision-making by the individual members of the system agent; the production becomes decentralised. The interaction of the members of such a system creates emergent behaviour, where the result cannot be accurately determined by ordinary methods and simulation must be applied. Modelling and simulation will, therefore, be an integral part of the planning and control of the processes of factories of the future. The purpose of the article is to describe the use of modelling and simulation processes in factories of the future. The first part of the article describes new manufacturing concepts that will be used in factories of the future, with a description of modelling and simulation routing in the frame of Industry 4.0. The next section describes how simulation is used for the control of manufacturing processes in factories of the future. The included subsection describes the implementation of this suggested pattern in the laboratory of ZIMS (Zilina Intelligent Manufacturing System), with an example of a metamodeling application and the results obtained.

Integrating Systems Modelling and Data Science

2016 ◽  
Vol 5 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Erik Pruyt
Keyword(s):  
Big Data ◽  
System Dynamics ◽  
Data Science ◽  
Modelling And Simulation ◽  
System Dynamics Modelling ◽  
The Future ◽  
Systems Modelling ◽  
Dynamics Modelling

Although System Dynamics modelling is sometimes referred to as data-poor modelling, it often is –or could be– applied in a data-rich manner. However, more can be done in the era of ‘big data'. Big data refers here to situations with much more available data than was until recently manageable. The field of data science makes big(ger) data manageable. This paper provides a perspective on the future of System Dynamics with a prominent place for bigger data and data science. It discusses different approaches for dealing with bigger data. It reviews methods, techniques and tools for dealing with bigger data in System Dynamics, and sheds light on the modelling phases for which data science is most useful. Finally, it provides several examples of current applications in which big data, data science, and System Dynamics modelling and simulation are being merged.

scholarly journals Possibilities of high-speed railway turnout data description

2021 ◽  
Vol 31 ◽  
pp. 18-26
Author(s):  
Adam Hlubuček
Keyword(s):  
Future Development ◽  
High Speed ◽  
Data Modeling ◽  
Data Models ◽  
High Speed Railway ◽  
Data Description ◽  
International Recommendation ◽  
Railway Infrastructure ◽  
The Future ◽  
Railway Turnout

This paper aims to summarize possibilities how to create data models of high-speed railway turnouts. The turnouts designed for high-speed operation require specific geometric solution. As the UIC RailTopoModel is considered an international recommendation in the field of data modeling of railway infrastructure, this issue is assessed in terms of models based on its principles. Solving this problem can affect the future development of the Multipurpose Railway Infrastructure Model gradually emerging at the CTU Railway Laboratory in Prague using the RailTopoModel principles.Whereas the RailTopoModel itself does not define any specific types of entities, the railML® 3.1 specifications are also used for assessment purposes. Turnouts are viewed both in terms of topology and in terms of functional infrastructure. In the final sections, recommendations are given on how to deal with the problems found, e. g. in terms of implementation into the Multipurpose Railway Infrastructure Model.

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