=Paper=
{{Paper
|id=Vol-2547/paper08
|storemode=property
|title=Augmented reality as a tool for open science platform by research collaboration in virtual teams
|pdfUrl=https://ceur-ws.org/Vol-2547/paper08.pdf
|volume=Vol-2547
|authors=Mariya P. Shyshkina,Maiia V. Marienko
|dblpUrl=https://dblp.org/rec/conf/aredu/ShyshkinaM19
}}
==Augmented reality as a tool for open science platform by research collaboration in virtual teams==
https://ceur-ws.org/Vol-2547/paper08.pdf
107
Augmented reality as a tool for open science platform by
research collaboration in virtual teams
Mariya P. Shyshkina[0000-0001-5569-2700] and Maiia V. Marienko[0000-0002-8087-962X]
Institute of Information Technologies and Learning Tools of the NAES of Ukraine,
9, M. Berlynskoho Str., Kyiv, 04060, Ukraine
{shyshkina, popel}@iitlt.gov.ua
Abstract. The provision of open science is defined as a general policy aimed at
overcoming the barriers that hinder the implementation of the European Research
Area (ERA). An open science foundation seeks to capture all the elements needed
for the functioning of ERA: research data, scientific instruments, ICT services
(connections, calculations, platforms, and specific studies such as portals).
Managing shared resources for the community of scholars maximizes the benefits
to society. In the field of digital infrastructure, this has already demonstrated great
benefits. It is expected that applying this principle to an open science process will
improve management by funding organizations in collaboration with
stakeholders through mechanisms such as public consultation. This will increase
the perception of joint ownership of the infrastructure. It will also create clear
and non-discriminatory access rules, along with a sense of joint ownership that
stimulates a higher level of participation, collaboration and social reciprocity.
The article deals with the concept of open science. The concept of the European
cloud of open science and its structure are presented. According to the study, it
has been shown that the structure of the cloud of open science includes an
augmented reality as an open-science platform. An example of the practical
application of this tool is the general description of MaxWhere, developed by
Hungarian scientists, and is a platform of aggregates of individual 3D spaces.
Keywords: ERA, EGI, EOSC-hub, EOSC, European Open Science Cloud.
1 Introduction
In order for researchers to be able to focus on their work, newly developed electronic
computing resources and cloud services should not only offer the functions necessary
to solve the problems of large data, but also work smoothly and intuitively, without
emphasizing the technical details of the cloud-based environments Thus, today’s
demands of the research and education community require a holistic approach in the
development of the next generation of intelligent networks, which should work in
concert with the components of distributed application.
___________________
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0).
108
1.1 The problem statement
Calculations that are traditionally used to store and process large amounts of data
remain difficult to use, both in terms of programming and in terms of data management.
This is especially emphasized by the latest trends in modern research, which are
becoming more and more manageable and associated with big data [10]. The latter
require the processing of a huge amount of distributed computing in an easy way. Most
of the current high-tech data tasks can easily be rolled into a list of independent tasks
that can be handled in parallel (for example, using a cloud platform and do not require
additional software), while the problem of distributed computing, storage and fast data
remains unresolved.
In order to focus on their research, researchers need to be able to analyze and process
data specific to the program intuitively. Users do not need to understand the core cloud
infrastructure software blocks that need to deal with distributed computing, storage, and
interconnection issues. The examples that cover these problems can be found in
virtually all branches of science, such as bioinformatics, geological science, high-
quality streaming video and real-time processing, or the design work of a large group
of scientists geographically distant from one another [4].
Cloud computing in all of its available models, such as IaaS, PaaS and SaaS [5],
plays an important role in this attempt to facilitate collaborative research by not
exploring and managing the details of the underlying infrastructure in order to be able
to use it for joint data processing. By providing abstraction of resources and simple
automation tools, modern cloud platforms simplify most routing tasks such as
installation, maintenance, backup, security, and more. Thus, cloud applications have
become an important tool for modern researchers. Moreover, today, they are, as a rule,
the best way to solve the problem of big data [4].
To solve research-related problems, modern science needs support from computing
infrastructures, so many European and national initiatives deal with distributed,
networked and cloud-based infrastructures. One of them is the Helix-Nebula project,
the European Network Infrastructure (EGI), the European Open Cloud of Science
(EOSC-hub). Due to the high demand for research applications, similar services related
to data storage, for the processing of a huge amount of data are increasing interest from
the scientific community. It is expected that these services will provide both
productivity and features that allow more flexible and cost-effective use of such
services. Easy multi-platform data access, long-term storage, performance support, and
cost of data access are elements that can be differentiated into one system. In order to
meet the needs of the scientific community regarding infrastructure in Poland, several
national projects were also launched. The results of the PL-Grid family of projects
provide a computing infrastructure for large-scale simulations and calculations at high-
performance computing clusters supported by domain-based services, solutions and
environments. Pioneer’s infrastructure serves high-bandwidth optical networks that
connect the main computer centers used in the infrastructure of PL-Grid. Since the
scientific data obtained through simulation, sensors or devices used by scientific
applications should be stored for further research in appropriate repositories, such
109
services are in high demand [7]. Some requirements put forward by users relate to
aspects of service quality and its proper level [8].
1.2 Analysis of recent research and publications
For Ukrainian science, issues relating to the European cloud of open science are new
and little studied. However, certain work is already being met and scientists are actively
interested in the issues. Olekcey O. Petrenko [9] investigated the changes taking place
in service-oriented architectures in connection with the transfer of applied applications
in the cloud environment, in particular, to the European cloud of open science.
Valerii Yu. Bykov [2] investigated the scientific and methodological basis for the
creation and development of a cloud-based environment in the context of open
scientific priorities and the formation of the European Research Area (ERA). Their
work outlines the conceptual and terminological justification of cloud computing, as
well as the main features of such a medium. Ukrainian scientists describe the main
methodological principles of designing and developing the environment, on the
example of the principles of open science, open education, as well as the specific
principles inherent in cloud-based systems.
1.3 The purpose of the article
On the basis of analysis of the structure of an open science platform, it is shown that
complemented reality serves as its tool and on a separate software product to determine
its practical value in scientific research.
2 Theoretical background
Scientists around the world are increasingly using cloud-based technologies to perform
computational tasks. Cloud resources can be distributed on demand, scaled according
to different usage patterns, and reduced costs for individual groups of scientists to
support their own infrastructure.
Olekcey O. Petrenko in [9, p. 13-14] notes that service-oriented approach that is
based on the present-day largest European project for the creation of the European Open
Science Cloud for Research (EOS), which began in 2017 and which motivates research
into the technology of hosting many SOA applications in the cloud, which will soon
serve 1,7 million scientists and 80 million professionals from various fields of science
and technology.
Major research infrastructures are planned on an EU-wide scale in the context of the
ESFRI roadmap, aimed at providing scientists with the appropriate tools for research.
More and more demands on data volumes and computing power are put forward.
Projects such as Indigo-Datacloud, EGI, European Cloud Science, HelixNebula, are
considering the introduction of cloud services for the European academic community
[1].
110
Indigo-DataCloud develops intermediate software for implementing a variety of
cloud-based services, from authentication, workload and data management, and
collects a catalog of cloud services. The project just released the second software,
ElectricIndigo.
The Indigo project is primarily aimed at bridging the gap between cloud-developers
and the services provided by existing cloud service providers, instead of providing their
own cloud-based services.
EGI coordinates a unified cloud, originally based on OCCI and CDMI, as web
services interfaces to access OpenNebula and OpenStack cluster resources or public
service providers. This approach is to provide an additional level of abstraction over
the resources provided by national energy conservation programs and remain separate
and independent of each other.
HelixNebula explores how best to use commercial cloud service providers in the
purchase of cloud infrastructure for research and education. This approach is to create
a private-government partnership for the purchase of hybrid clouds.
The third phase of the prototype, which involves three contract consortia, has
recently begun. The European Commission promotes the European cloud of open
science as a common basis for supporting open science and research, covering a wide
range of issues ranging from technical, accessible and managerial to building
infrastructure. Many of these projects are funded by research or meet the needs of
specific communities, such as providing prototype or pilot-level services to a limited
group of users, with limited resources, as well as groups within the EGI Federated
Cloud Initiative. Moving from the prototype stage to the production stage, offering
large volumes of resources for a large community, is a challenge in terms of efforts and
resources. Creating a well-equipped and supported platform for cloud computing
requires a significant investment of large commercial cloud providers or public
organizations that decide to invest in creating a real cloud infrastructure for science.
One of the possible alternatives to a central approach to large-scale financing is the
federative approach, where the infrastructure is built up from the bottom up, combining
medium / large objects into large ones, to reach the appropriate scale [1].
Within the framework of the European Commission’s strategy for creating a single
digital market, the European Commission officially launched the European Open
Educational Initiative (EOSC) in April 2016. EOSC promotes not only scientific
excellence and data reuse, but also job creation and competitiveness in Europe, as well
as contributing to pan-European cost efficiencies in scientific infrastructures by
promoting unprecedented scale.
The experts outlined the basic principles of the cloud of open science [3]:
1. EOSC needs to integrate with other electronic infrastructures and initiatives in the
world by introducing a light, interconnected system of services and data that fits the
federal model.
2. The term “open” refers to the availability of services and data in accordance with the
appropriate non-discriminatory policy (“not all data and tools may be open”, and
“free data and services do not exist”).
3. The EOSC should include all academic disciplines.
111
4. The term “cloud” should not relate to ICT infrastructure, but to universal access to
data, software, standards, expertise and policy frameworks for science and
innovation-driven data.
The general view of most relevant stakeholders for the European cloud of open science
lies in the fact that this cloud should [9]:
─ to be a system of services provided by different suppliers;
─ relying on existing electronic infrastructures, so developer efforts should focus on
the integration / interoperability of cloud services;
─ continuously develop and integrate new services and tools as soon as they become
available, freely distributed to users;
─ to take into account the needs of users as a leading motive for the development of
the European cloud of open science.
In the vision of experts, EOSC will be an accessible infrastructure for modern research
and innovation that employs the Internet of accessible data and interoperability and
reusable services. It should be based on standards, best practices and infrastructures
supplemented by adequate human experience. The fair principles should be maintained,
and particular attention should be paid to the reuse of open and confidential data. Data
should be with a multitude of elements (standard, tools, protocols) that provide the
possibility and ease of reuse. In addition, there is a need to implement a science data
processing profession to ensure professional data management and long-term
management. In Europe, European research infrastructures specializing in the domain,
and cross-sectoral ICT electronic infrastructures as well as other disciplinary and
interdisciplinary collaborations and services have already been established. They can
be considered the basis for EOSC. However, the implementation of ambitions to
increase unimpeded access, reliable reuse of data and other digital research objects, as
well as cooperation between different services and infrastructures (which guarantees
non-discriminatory access and reuse of data both to the public and to the public and
private sector), requires further improvement of this landscape in order to transform the
ever-increasing amount of data on knowledge as a renewable, sustainable ground for
innovation in turn to meet the global needs. EOSC is an instrument defined by the
European Commission to facilitate such development towards the implementation of
the Open Science. This idea highlights the strong link between ERA implementation
through Open Science, Open Science and EOSC. In this context, the High-Level Expert
Group, developed by the European Commission, reported on the list of key trends of
Open Science that should be taken into account in the EOSC project. They cover several
aspects, such as new ways of scientific communication (for example, programs,
software conveyors and data itself), new incentives for promoting data dissemination
and sharing of tools, facilitating the formation of data processing professionals,
interdisciplinary collaboration, support for innovative SMEs, the creation of
ecosystems, methodologies and tools for the reproduction of current published research,
etc. [3].
112
3 Research methodology
The ERA was endorsed by the European Council in 2000 as a way of building a single,
open-world research area based on a domestic market in which researchers, scientific
knowledge and technology circulate freely and through which the European Union and
its members strengthen their scientific and technological bases, their competitiveness
and the ability to collectively address the challenges of today [3].
According to Olekcey O. Petrenko, EOSC is an interdisciplinary environment for
research, innovation and educational goals [9, p. 59].
According to the first report of the High-Level Expert Group on the EOSC appointed
by the European Commission, EOSC was identified as an open source support
environment for accelerating the transition to more effective open science and open
innovation in digital the single market by removing technical, legislative and human
barriers to reuse data and research tools. Indeed, the term “cloud” was interpreted as a
metaphor that helps convey the idea of fidelity and community [3].
4 About Open Science platform
Now consider the platforms and tools of one of the major European electronic
infrastructures, EGI, which will cover how they can be the basis for an open science
fund and then EOSC. EGI, an advanced computing engine for research, is a federated
electronic infrastructure created to provide advanced computing services for research
and innovation. EGI’s infrastructure is primarily state-funded and has over 300 data
centers and cloud providers throughout Europe and around the world. Its principles are
based on an open academic community, and its mission is to create and provide open
solutions for research and research infrastructures by combining digital capabilities,
resources and expertise between communities and across national boundaries. EGI
architecture is organized in platforms [3]:
─ Basic Infrastructure Platform for Managed Distributed Infrastructure;
─ Cloud infrastructure for managing the unified regional infrastructure;
─ An open data platform that provides easy access to large and distributed data sets;
─ A platform for cooperation, for the exchange of information and community co-
ordination,
─ Joint platforms, specialized service portfolios designed for specific academic
communities.
The platform architecture allows any type and any number of shared platforms to
coexist on physical infrastructure.
4.1 Augmented reality platform as a tool for open science
EGI launched the production phase of the cloud federation to serve research
communities in May 2014, the EGI Federated Cloud. It integrates community, private
and/or public clouds into a scalable computing platform for data and/or computing
113
applications and services. Its architecture is based on the concept of an abstract cloud
management environment (CMF), which supports a set of cloud interfaces for
communities. Each Infrastructure Resource Center manages an instance of this CMF
according to its own technological advantage and integrates it with the federation by
interacting with the EGI’s core infrastructure [3]. This integration is carried out using
public interfaces supported by CMF, which minimizes the impact on the work of the
site. Suppliers are organized in the area that uncover homogeneous interfaces and group
resources dedicated to serving specific communities and/or platforms.
EGI Federated Cloud is based on a hybrid model where private, community, and
public clouds can be integrated and already offer some tools that a service center must
provide, such as virtualization and easy sharing and reuse of tools.
Each Infrastructure Resource Center manages an CMF instance according to its own
technological advantage and integrates it with the federation by interacting with the
EGI core infrastructure. Suppliers are organized in the areas of homogeneous interfaces
(IaaS). Community platforms can use resources from one or more areas using these
interfaces. AppDB VMOps enables the automatic deployment of virtual devices at all
resource centers that support a specific community.
Olekcey O. Petrenko [9] explores the FIWARE directory as the main tool for
creating web services for EOSC. Some of the services included in the FIWARE
directory can be linked to the augmented reality:
─ AEON Cloud Messaging: Real-time service provides cloud services (channels) for
the transfer of unlimited number of entities, sharing unlimited amount of
information, as well as services for managing actors involved in cloud environments.
─ Complex Event Processing (CEP) – Proactive Technology Online: CEP analyzes
real-time events by responding to situations rather than on individual events.
Situations include composite events (for example, sequential), operator distribution
by events (e.g., aggregation), and lack of operators.
─ Cloud Rendering: The service defines a common way of requesting, receiving, and
managing the video stream of a remote 3D application.
4.2 Practical application of augmented reality
Today, the Institute of Information Technologies and Training of the NAES of Ukraine
is a partner of Visegrad Fund’s Strategic Grant No. 21810100 “V4 + Academic
Research Consortium for the Integration of Databases, Robotics and Language
Technologies” [2]. As an example, let’s look at one of the services developed by one
of the partners of this project (Óbuda University Budapest, Magyarország), which can
be included in the open science platform: MaxWhere (Hungary). MaxWhere combines
several new technologies. The cognitive navigation technology (CogiNav) allows users
to navigate smoothly across 3D spaces using only a laptop and mouse [5].
MaxWhere is the platform for managing all forms of digital content in 3D spaces.
The main product – MaxWhere, which is largely similar to graphics engines (like Unity,
Unreal), however, differs from them, since it has been optimized not for gaming
114
applications, but for everyday digital life and professional industry. MaxWhere can be
used in education and research.
Maxwhere [6] includes fast and innovative interfaces. This allows you to switch
projects and go to different scientific communities, distribute research results in the
fastest way. This is a combination of other applications that exist to organize the
teamwork of scholars. 3D graphics will diversify your work without compromising
performance. It can also be used by students to increase productivity and study data
research.
Browser23 introduces a new web surfing philosophy: instead of having a limited
number of tabs next to users, limiting their ability to switch between them and searching
now, it allows you to set browser windows in 3D space, grouped by topics that are
scaled for size and significance. The newly developed Ultra Sharing technology, which
allows users to create VR offices that contain a large number of documents, and even
complete the workflows of the project, and split these offices with one click [6].
Research shows that all these solutions combine an extremely effective way of
visualizing, exchanging and manipulating large volumes of information while
maintaining low cognitive load – a huge asset for understanding, configuring and
managing large digital networking systems.
In 2017, MaxWhere was released as a tool for presenting 3D slides in interactive
spaces. This solution is a blend between PowerPoint and Prezi, expanded with 3D
objects. From a technological point of view, MaxWhere combines 3D space with web
technologies. In this way, the world of open-source software (for example, Node.js,
NPM and Node-RED) can be directed to MaxWhere applications.
5 Conclusions and prospects for further research
To date, the implementation of the European Research Area (ERA), as depicted by the
European Council, can not be considered fully achieved. The implementation of an
open and integrated environment for cross-border unimpeded access to advanced digital
resources, services and opportunities facilitating the reuse of data and research services
is accelerated by the initiative of the European Commission “European Open Science
Cloud”. Open science is seen as a natural paradigm for the promotion and development
of such events. It can remove the barrier between neighboring communities, provide
interdisciplinary cooperation, reinforce the need for knowledge sharing and allow free
and unrestricted access. The advantages of the approach to open science and, in
particular, the advantages of joint resources for the introduction of European
infrastructure and the management of European open science were considered. We have
analyzed the possible approach to the implementation of EOSC through open scientific
communities. The EOSC architecture is based on the cloud hub federation, where the
cloud hub provides data, services and features in a standard and consistent way. Hubs
support the cloud provisioning paradigm to facilitate sharing, reuse, and combined data
and tooling with virtualization. In addition, the federation of hubs provides a multi-
layered organizational structure that complies with European policies, norms,
restrictions and business models, and allows the creation of a community that can
115
combine the various types of experiences available in each center. That is, an existing
environment with several suppliers
EOSC is governed by special tools, processes and tools that determine the EOSC
integration and management system owned, maintained, and developed by EOSC in
accordance with the Commons management model. EOSC cloud nodes services are
provided by many stakeholders: data providers, European research infrastructures,
electronic infrastructures, research and local, regional and national institutions. The use
of data directly benefits EOSC and the acceptance of open academic communities,
using technologies, services and resources provided in the context of existing European
electronic infrastructures. EOSC and electronic infrastructures can become a pole of
engagement for designing and implementing appropriate solutions for managing and
using a large number of data sets. This will allow you to create an integrated
environment for rapid development, prototyping and service delivery for service
platforms and scientific applications.
References
1. Attardi, G., Barchiesi, A., Colla, A., Galeazzi, F., Marzulli, G., Reale, M.: Declarative
Modeling for Building a Cloud Federation and Cloud Applications. arXiv:1706.05272
[cs.DC]. https://arxiv.org/pdf/1706.05272 (2017). Accessed 25 Dec 2018
2. Bykov, V.Yu., Shyshkina, M.P.: The Conceptual Basis of the University Cloud-Based
Learning and Research Environment Formation and Development in View Of The Open
Science Priorities. Information Technologies and Learning Tools 68(6), 1–19 (2018).
doi:10.33407/itlt.v68i6.2609
3. Ferrari, T., Scardaci, D., Andreozzi, S.: The Open Science Commons for the European
Research Area. In: Mathieu, P.P., Aubrecht, C. (eds.) Earth Observation Open Science and
Innovation. ISSI Scientific Report Series, vol. 15, pp. 43–68. Springer, Cham (2018).
doi:10.1007/978-3-319-65633-5_3
4. Filiposka, S., Demchenko, Yu., Karaliotas, T., de Vos, M., Regvart, D.: Distributed cloud
services based on programmable agile networks. In: Proceedings of TERENA networking
conference (TNC16), Prague, 13-16 June 2016
5. Markova, O.M., Semerikov, S.O., Striuk, A.M., Shalatska, H.M., Nechypurenko, P.P.,
Tron, V.V.: Implementation of cloud service models in training of future information
technology specialists. In: Kiv, A.E., Soloviev, V.N. (eds.) Proceedings of the 6th Workshop
on Cloud Technologies in Education (CTE 2018), Kryvyi Rih, Ukraine, December 21,
2018. CEUR Workshop Proceedings 2433, 499–515. http://ceur-ws.org/Vol-
2433/paper34.pdf (2019). Accessed 10 Sep 2019
6. MaxWhere is the hungarian winner of the IoT category - Startup Europe Awards.
http://startupeuropeawards.eu/maxwhere-is-the-hungarian-winner-of-the-iot-category
(2018). Accessed 25 Dec 2018
7. Merzlykin, O.V., Semerikov, S.O., Sokolyuk, A.N.: Theoretical and methodological
foundations of the using cloud technologies as a tool of high school students’ research
competencies forming in profile physics learning. Vydavnychyi tsentr Kryvorizkoho
natsionalnoho universytetu, Kryvyi Rih (2018)
8. Nikolow, D., Slota, R., Polak, S., Pogoda, M., Kitowski, J.: Policy-based SLA storage
management model for distributed data storage services. Computer Science 19(4), 403–429
(2018)
116
9. Petrenko, O.O.: Strategy development of service-oriented systems in a cloud environment.
Dissertation, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic
Institute” (2018)
10. Volkova, N.P., Rizun, N.O., Nehrey, M.V.: Data science: opportunities to transform
education. In: Kiv, A.E., Soloviev, V.N. (eds.) Proceedings of the 6th Workshop on Cloud
Technologies in Education (CTE 2018), Kryvyi Rih, Ukraine, December 21, 2018. CEUR
Workshop Proceedings 2433, 48–73. http://ceur-ws.org/Vol-2433/paper03.pdf (2019).
Accessed 10 Sep 2019