You are invited to use the opportunity to test Elsevier’s scientific production analytical tool SciVal

October 21, 2022

We are pleased to announce that Elsevier has granted a free temporary access to SciVal analytical tool till November 15, 2022.

The tool is accessible from the Scopus database website interface:


Or via internet address: https://www.scival.com/

SciVal – is an analytical tool designated for a rapid, convenient and comprehensive assessment and analysis of scientific output. The tool utilizes data from Scopus database, covering over 55 M publications (from 1996), published in over 24,000 serial sources by over 5,000 publishers. These data allows to analyze the scientific output of over 20,000 scientific institutions and their researchers from over 230 countries.

The tool consists of separate analysis modules, allowing to assess and visualize the coverage, impact, and prioritized areas of scientific research, evaluate the progress by comparing the data within various contexts and levels; discover collaboration and even financing opportunities, identify the most relevant and the most perspective research areas and their trends, and to generate various reports.

Overview module
This module allows to evaluate scientific output of a selected institution (or their group, e.g. entire alliance), of a researcher (or research group), of a country or a region, or published in a particular Scopus indexed source by various aspects and in accordance with the selected science classification scheme.  The overview provides the numbers of publications and their views, citation data, the most prominent research topics, the most productive authors, awarded grants and their financing information, technological impact of publications (patent citations), and even societal impact (media mentions (in English media). Publications can be additionally assessed by their represented scientific categories, their alignment with the Sustainable Development Goals (SDGs), Scopus sources and their represented quartiles (Q) based on the selected metric (CiteScore, SJR, or SNIP). Moreover, the main indicators of scientific output used in the global university rankings (QS, ARWU, THE) are also provided with the ability of further analysis (in case of THE rankings), which are highly relevant in assessing university’s progress and in formulating future strategies. All aforementioned aspects can also be applied in evaluating individual research areas, topics or their clusters, as well as any other publication sets.

Benchmarking module
This module is especially useful in determining research priorities and formulating strategies since it allows to assess the progress and strongest points of analyzed entities as well as trach their changes in time within the contexts of all levels (from individual researchers to countries and regions). It should be noted that entities of different types and levels can be analyzed together at the same time (e.g., you can benchmark individual researchers or publication sets against whole institutions, research areas, countries, regions, and so on).

Collaboration module
This module allows to assess current and potential collaboration opportunities based on publication and their citation data visually (in the map) or in the table format within global, country or region, or specific sector context.

Trends module
This module is dedicated to assess general indicators and tendencies in particular research areas and to identify countries or regions, institutions and researchers who have excelled in a specific field. The organizations that funded the most research in the analyzed research area, the sources indexed by Scopus, where the research from that field was published most often, and the key phrases or words used most often in the analyzed research area are also distinguished in this module.

Report module
This module allows to rapidly generate data reports of analyzed entities by using report templates provided by SciVal or by their partners, or by creating customized reports. In any case, separate parts of reports can be easily edited. Reports can also be compiled from or enriched with the data generated within other analysis modules.

Within all modules the performed analysis can be specified by changing the time-frame and/or applying additional filters. It is also possible to choose the metrics and indicators to be used in the analysis. It should be noted, that all modules are interrelated. Therefore, while transferring from one module to another, not only the analyzed entity (if applicable according to the analysis type), but also all additional previously applied filters remains fixed within the modules.

All data, their visualizations (graphs), publication sets, and reports generated in SciVal can be saved, exported, and shared with other SciVal users (in this case, the registration to the SciVal account is required, but if you have a personal Scopus account, you do not need to create a new account – you can sing-in to SciVal with the Scopus account’s credentials).
SciVal can also be used to analyze external data. For instance, you can import and analyze the results of search performed in Scopus database.

Additional information about the SciVal tool and its usage
The very home page of the tool provides a wealth of information and additional links about the SciVal tool and how to use it:

The tool is also described on the Elsevier website.

More detailed and in depth information about the SciVal modules and their application, along with the practical examples, is provided in the recorded virtual seminars
Scopus, SciVal & Rankings: What is good to know? (Passcode: ILP1Y+@7)
SciVal Camp 2022 Day 1 (Passcode: 9PVP0J*$)
SciVal Camp 2022 Day 2 (Passcode: Q@zwiDG1)
SciVal Camp 2022 Day 3 (Passcode: q8w!^Kit)

Additionally, we are inviting you to join the upcoming virtual Elsevier seminar “Scopus & SciVal towards reporting data” to learn more about how you can use Scopus and SciVal in your work, which will be held on October 25th.

Register here >>> 

 

Related news

Interdisciplinarity in practice: how Electronics and Medical Engineering students developed a Human motion analysis system
Interdisciplinarity in practice: how Electronics and Medical Engineering students developed a Human motion analysis system
Modern engineering solutions are increasingly created through collaboration between specialists from different fields. The university environment provides an opportunity to combine diverse competencies and develop solutions that would be difficult to achieve within the boundaries of a single discipline. Such collaboration was also at the heart of a bachelor’s thesis project in which VILNIUS TECH students Laura Venckutė (Faculty of Electronics) and Abderrazak El Aamrani (Faculty of Mechanics) combined expertise in electronics and medical engineering to develop a human motion recognition and evaluation system. From an Idea to Interdisciplinary Collaboration At the beginning of the project, students from the Medical Engineering and Electronics Engineering study programmes sought to address a problem relevant to both sports and rehabilitation: the lack of accessible systems capable of automatically evaluating human movements and providing immediate feedback. As the project authors point out, incorrect movements can reduce training effectiveness and increase the risk of injuries during rehabilitation, sports activities, or everyday tasks. For this reason, they decided to look for a technological solution that could help objectively assess movement quality. The idea emerged from previous projects and experience gained during their studies, while an important catalyst was the opportunity for collaboration proposed by their supervisors. From the outset, it was clear that the project would require expertise from different fields, as motion analysis involves not only developing a technical system but also defining meaningful criteria for evaluating human movement. [caption id="attachment_120707" align="alignnone" width="2048"] Electronics and Medical Engineering students developed a Human motion analysis system[/caption] The students brought different, yet closely interconnected and complementary competencies to the project. The Electronics Engineering student was responsible for computer vision, embedded systems, and system integration, while the Medical Engineering student contributed expertise in biomechanics and human movement assessment. Although responsibilities were divided according to individual areas of expertise, key decisions were made collaboratively. From the Initial Concept to a Functional System In the early stages, the team planned to develop a system capable of analysing a broader range of movement patterns and performing more advanced analytical functions. However, as the project progressed, technical limitations, available hardware resources, and the scope of the bachelor’s thesis had to be taken into account. As a result, some ideas had to be abandoned. According to the team members, no major disagreements arose during the project. Decisions were made by discussing possible alternatives, evaluating how well they aligned with the project objectives, and, whenever possible, testing different approaches in practice. When technical and medical requirements conflicted, the team sought solutions that best balanced project goals and implementation constraints. The final outcome of the project is a human motion recognition and feedback system based on a pose estimation algorithm designed for basketball shooting analysis. The system detects a person in real time, estimates body posture, evaluates shooting technique according to biomechanical criteria, and subsequently provides feedback to the user. The Value of Interdisciplinarity and Future Opportunities During testing, the system performed better than expected. It successfully analysed the movements of users of different heights and maintained reliable performance at distances of up to 12 metres. According to the students, not only did the technical results exceed expectations, but the collaboration process itself also proved highly successful. In their view, such a project could theoretically be completed by a specialist from a single field. In practice, however, this would be difficult and inefficient. The project required both expertise in electronics and an understanding of human movement analysis. Without competencies from both fields, considerably more time would have been needed for learning unfamiliar topics and identifying appropriate solutions. Looking ahead, the students see opportunities to further develop the project by improving system stability, optimising resource usage, expanding the range of supported movement patterns, and increasing motion recognition accuracy. Although they are not yet certain whether they will continue working in this specific area, they hope to further deepen their expertise in related fields of technology and engineering. Supervisors’ Insights: Interdisciplinarity as a Foundation of Future Engineering The thesis supervisors emphasise that the nature of the project itself required collaboration across disciplines. However, the greatest value of the project lies not only in the technical solution that was developed, but also in the students’ ability to work together effectively. Professor Kristina Daunoravičienė, lecturer in the Medical Engineering study programme, notes that developing a human posture recognition and evaluation system requires both an understanding of human movement and biomechanics, as well as the ability to create a technical system capable of collecting, processing, and presenting information to the user. „The need for different knowledge and competencies made this topic an excellent platform for collaboration between Medical Engineering and Electronics Engineering students. Such projects foster not only technical solutions but also the ability to understand the logic, limitations, and priorities of other disciplines,“ says Prof. Dr Kristina Daunoravičienė. Although the students were initially unfamiliar with one another and came from different engineering backgrounds, a shared goal quickly became the foundation of successful cooperation. According to the supervisor, Medical Engineering contributed the perspective of human movement assessment and result interpretation, while Electronics Engineering provided expertise in system architecture, prototyping, and optimisation. According to Prof. Dr K. Daunoravičienė, the most important outcome of the project is not only the developed prototype and its comparison with the Xsens motion analysis system: „Equally important are the competencies of collaboration, communication, trust, initiative, and the ability to learn from one another. These are the qualities that allow good ideas to become real, functioning solutions.“ Associate Professor Dr Vytautas Abromavičius of the Faculty of Electronics also points out that in the era of artificial intelligence, technical expertise alone is no longer sufficient. Clear communication, the ability to understand specialists from different fields, and working together towards a common goal are becoming increasingly important. „This bachelor’s thesis demonstrated that our students communicated exceptionally well and were able to explain specialised professional terminology in a simple and understandable way. This mutual understanding enabled them to effectively combine knowledge from different disciplines and achieve an excellent result,“ says Assoc. Prof. Dr Vytautas Abromavičius. According to him, the need for interdisciplinary projects in modern engineering continues to grow. Every real-world product developed for the market consists of multiple interconnected components; therefore, a broader understanding of the problem leads to better product applicability and a more complete final outcome.
More
VILNIUS TECH Professor A. Čenys Represents Baltic States at Google Leadership Summit
VILNIUS TECH Professor A. Čenys Represents Baltic States at Google Leadership Summit
Prof. Antanas Čenys, a prominent researcher at VILNIUS TECH and the SustAInLivWork project, participated by personal invitation from Google in the exclusive Google for Education Higher Education Leader Series EMEA in London. Prof. Čenys was the only AI and cybersecurity expert from the Baltic countries to be personally invited to this high-level summit. The exclusive event brought together higher education leaders, technology pioneers, and innovation stakeholders from across Europe, the Middle East, and Africa. The summit focused on shaping the future of Artificial Intelligence, digital transformation, cybersecurity, and driving responsible innovation within the global academic and industrial landscapes. The insights and discussions from the London summit strongly resonate with the core mission of the SustAInLivWork project: strengthening Europe’s capacity to develop, deploy, and scale trustworthy AI solutions while simultaneously building the advanced skills, critical infrastructures, and innovation ecosystems required for a sustainable digital future. Through SustAInLivWork, VILNIUS TECH and its partners are actively delivering: An International AI Cluster: bridging the gap between research excellence, industry, and public sector stakeholders; Advanced Innovation Services: driving AI and data-driven solutions for various sectors; AI Skills Development: establishing lifelong learning opportunities and specialized training; Cross-Regional Collaboration: accelerating practical AI adoption and ensuring positive societal impact. The summit also underscored the rapidly growing importance of cybersecurity as a fundamental pillar for secure AI deployment. This focus perfectly aligns with ongoing initiatives led by VILNIUS TECH, including specialized cybersecurity skills development programmes supported by Google.org, aimed at strengthening digital resilience and cyber competence across Europe. As Europe accelerates its comprehensive AI transformation, structured collaboration between universities, industry leaders, policymakers, and major technology providers becomes increasingly paramount. SustAInLivWork and VILNIUS TECH remain committed to contributing to this evolutionary journey by building strong bridges between cutting-edge research, thriving innovation ecosystems, and sustainable societal progress.
More