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Advancing Research Data Management in Universities of Science and Technology
(Meyrin : CERN, 2020-02-13) Björnemalm, Matthias; Cappellutti, Federica; Dunning, Alastair; Gheorghe, Dana; Goraczek, Malgorzata Zofia; Hausen, Daniela; Hermann, Sibylle; Kraft, Angelina; Martinez Lavanchy, Paula; Prisecaru, Tudor; Sànchez, Barbara; Strötgen, Robert
The white paper ‘Advancing Research Data Management in Universities of Science and Technology’ shares insights on the state-of-the-art in research data management, and recommendations for advancement. A core part of the paper are the results of a survey, which was distributed to our member institutions in 2019 and addressed the following aspects of research data management (RDM): (i) the establishment of a RDM policy at the university; (ii) the provision of suitable RDM infrastructure and tools; and (iii) the establishment of RDM support services and trainings tailored to the requirements of science and technology disciplines. The paper reveals that while substantial progress has been made, there is still a long way to go when it comes to establishing “advanced-degree programmes at our major universities for the emerging field of data scientist”, as recommended in the seminal 2010 report ‘Riding the Wave’, and our white paper offers concrete recommendations and best practices for university leaders, researchers, operational staff, and policy makers. The topic of RDM has become a focal point in many scientific disciplines, in Europe and globally. The management and full utilisation of research data are now also at the top of the European agenda, as exemplified by Ursula von der Leyen addressat this year’s World Economic Forum.However, the implementation of RDM remains divergent across Europe. The white paper was written by a diverse team of RDM specialists, including data scientists and data stewards, with the work led by the RDM subgroup of our Task Force Open Science. The writing team included Angelina Kraft (Head of Lab Research Data Services at TIB, Leibniz University Hannover) who said: “The launch of RDM courses and teaching materials at universities of science and technology is a first important step to motivate people to manage their data. Furthermore, professors and PIs of all disciplines should actively support data management and motivate PhD students to publish their data in recognised digital repositories.” Another part of the writing team was Barbara Sanchez (Head of Centre for Research Data Management, TU Wien) and Malgorzata Goraczek (International Research Support / Data Management Support, TU Wien) who added:“A reliable research data infrastructure is a central component of any RDM service. In addition to the infrastructure, proper RDM is all about communication and cooperation. This includes bringing tools, infrastructures, staff and units together.” Alastair Dunning (Head of 4TU.ResearchData, Delft University of Technology), also one of the writers, added: “There is a popular misconception that better research data management only means faster and more efficient computers. In this white paper, we emphasise the role that training and a culture of good research data management must play.”
Analysing the evolution of computer science events leveraging a scholarly knowledge graph: a scientometrics study of top-ranked events in the past decade
(Dordrecht [u.a.] : Springer Science + Business Media B.V., 2021) Lackner, Arthur; Fathalla, Said; Nayyeri, Mojtaba; Behrend, Andreas; Manthey, Rainer; Auer, Sören; Lehmann, Jens; Vahdati, Sahar
The publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.
Audio Ontologies for Intangible Cultural Heritage
(Bramhall, Stockport ; EasyChair Ltd., 2022-04-12) Tan, Mary Ann; Posthumus, Etienne; Sack, Harald
Cultural heritage portals often contain intangible objects digitized as audio files. This paper presents and discusses the adaptation of existing audio ontologies intended for non-cultural heritage applications. The resulting alignment of the German Digital Library-Europeana Data Model (DDB-EDM) with Music Ontology (MO) and Audio Commons Ontology (ACO) is presented.
Binomische Kommunikation : Aktivierung des Selbsterneuerungspotentials am Beispiel wissenschaftlicher Bibliotheken
(Frankfurt am Main [u.a.] : Peter Lang, 2003) Huesmann, Anna-Maria; Geißler, Harald; Petersen, Jendrik
Die Abhandlung untersucht theoretisch und empirisch Einflußbereiche, die sich auf den nachhaltigen Erfolg von Veränderungsprozessen in wissenschaftlichen Bibliotheken, als Dienstleistungsunternehmen des öffentlichen Sektors, auswirken können. Fokussiert wird der strategische Erfolgsfaktor zwischenmenschliche Kommunikation. Isoliert werden einige, aus der Qualität der interpersonalen Kompetenz resultierende, kommunikative Barrieren. Aufbauend auf die hergeleiteten Konsequenzen wird abschließend die andragogische Methode der Binomischen Kommunikation entwickelt und vorgestellt. Hierbei handelt es sich um eine dialogische, verständigungsorientierte, auf gründlichen Reflexionen und überprüftem Wissen basierte Vorgehensweise, die das Selbsterneuerungspotential der Mitarbeiter aktiviert und damit die permanente und nachhaltig wirkende Innovation des Dienstleistungsunternehmens sichert.
Combining statistical and machine learning methods to explore German students’ attitudes towards ICT in PISA
(London : Taylor & Francis, 2021) Lezhnina, Olga; Kismihók, Gábor
In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students’ attitudes towards information and communication technology (ICT) in relation to mathematical and scientific literacy measured by the Programme for International Student Assessment (PISA) in 2015 and 2018. Implementations of the random forest (RF) algorithm were applied to impute missing data and to predict students’ proficiency levels in mathematics and science. Hierarchical linear models (HLM) were built to explore relationships between attitudes towards ICT and mathematical and scientific literacy with the focus on the nested structure of the data. ICT autonomy was an important variable in RF models, and associations between this attitude and literacy scores in HLM were significant and positive, while for other ICT attitudes the associations were negative (ICT in social interaction) or non-significant (ICT competence and ICT interest). The need for further research on ICT autonomy is discussed, and benefits of combining statistical and machine learning approaches are outlined.
A comprehensive quality assessment framework for scientific events
(Dordrecht [u.a.] : Springer Science + Business Media B.V., 2020) Vahdati, Sahar; Fathalla, Said; Lange, Christoph; Behrend, Andreas; Say, Aysegul; Say, Zeynep; Auer, Sören
Systematic assessment of scientific events has become increasingly important for research communities. A range of metrics (e.g., citations, h-index) have been developed by different research communities to make such assessments effectual. However, most of the metrics for assessing the quality of less formal publication venues and events have not yet deeply investigated. It is also rather challenging to develop respective metrics because each research community has its own formal and informal rules of communication and quality standards. In this article, we develop a comprehensive framework of assessment metrics for evaluating scientific events and involved stakeholders. The resulting quality metrics are determined with respect to three general categories—events, persons, and bibliometrics. Our assessment methodology is empirically applied to several series of computer science events, such as conferences and workshops, using publicly available data for determining quality metrics. We show that the metrics’ values coincide with the intuitive agreement of the community on its “top conferences”. Our results demonstrate that highly-ranked events share similar profiles, including the provision of outstanding reviews, visiting diverse locations, having reputed people involved, and renowned sponsors.
Concept for Setting up an LTA Working Group in the NFDI Section "Common Infrastructures"
(Zenodo, 2022-04-12) Bach, Felix; Degkwitz, Andreas; Horstmann, Wolfram; Leinen, Peter; Puchta, Michael; Stäcker, Thomas
NFDI consortia have a variety of disparate and distributed information infrastructures, many of which are as yet only loosely or poorly connected. A major goal is to create a Research Data Commons (RDC) . The RDC concept1 includes, for example, shared cloud services, an application layer with access to high-performance computing (HPC), collaborative workspaces, terminology services, and a common authentication and authorization infrastructure (AAI). The necessary interoperability of services requires, in particular, agreement on protocols and standards, the specification of workflows and interfaces, and the definition of long-term sustainable responsibilities for overarching services and deliverables. Infrastructure components are often well-tested in NFDI on a domain-specific basis, but are quite heterogeneous and diverse between domains. LTA for digital resources has been a recurring problem for well over 30 years and has not been conclusively solved to date, getting urgency with the exponential growth of research data, whether it involves demands from funders - the DFG requires 10 years of retention - or digital artifacts that must be preserved indefinitely as digital cultural heritage. Against this background, the integration of the LTA into the RDC of the NFDI is an urgent desideratum in order to be able to guarantee the permanent usability of research data. A distinction must be2 made between the archiving of the digital objects as bitstreams (this can be numeric or textual data or complex objects such as models), which represents a first step towards long-term usability, and the archiving of the semantic and software-technical context of the digital original objects, which entails far more effort. Beyond the technical embedding of the LTA in the system environment of a multi-cloud-based infrastructure, a number of technically differentiated requirements of the NFDI's subject consortia are part of the development of a basic service for the LTA and for the re-use of research data.3 The need for funding for the development of a basic LTA service for the NFDI consortia results primarily from the additional costs associated with the technical and organizational development of a cross-NFDI, decentralized network structure for LTA and the sustainable subsequent use of research data. It is imperative that the technical actors are able to act within the network as a technology-oriented community, and that they can provide their own services as part of the support for also within a federated infrastructure. The working group "Long Term Archiving" (LTA) is to develop the requirements of the technical consortia for LTA and, on this basis, strategic approaches for the implementation of a basic service LTA. The working group consists of members of various NFDI consortia covering the humanities, natural science and engineering disciplines and experts from a variety of pertinent infrastructures with strong overall connections to the nestor long-term archiving competence network. The close linkage of NFDI consortia with experienced4 partners in the field of LTA ensures that a) the relevant technical state-of-the-art is present in the group and b) the knowledge of data producers about contexts of origin and data users interact directly. This composition enables the team to take an overarching view that spans the requirements of the disciplines and consortia, also takes into account interdisciplinary needs, and at the same time brings in the existing know-how in the infrastructure sector.
The Concept of Identifiability in ML Models
(Setúbal : SciTePress - Science and Technology Publications, Lda., 2022) von Maltzan, Stephanie; Bastieri, Denis; Wills, Gary; Kacsuk, Péter; Chang, Victor
Recent research indicates that the machine learning process can be reversed by adversarial attacks. These attacks can be used to derive personal information from the training. The supposedly anonymising machine learning process represents a process of pseudonymisation and is, therefore, subject to technical and organisational measures. Consequently, the unexamined belief in anonymisation as a guarantor for privacy cannot be easily upheld. It is, therefore, crucial to measure privacy through the lens of adversarial attacks and precisely distinguish what is meant by personal data and non-personal data and above all determine whether ML models represent pseudonyms from the training data.
ConfIDent: Enter the Feedback Loop
(Meyrin : CERN, 2020-01-29) Strömert, Philip
Slides from session at PIDapalooza2020, January 29th 2020, Lisbon, Portugal.
Crowdsourcing Scholarly Discourse Annotations
(New York, NY : ACM, 2021) Oelen, Allard; Stocker, Markus; Auer, Sören
The number of scholarly publications grows steadily every year and it becomes harder to find, assess and compare scholarly knowledge effectively. Scholarly knowledge graphs have the potential to address these challenges. However, creating such graphs remains a complex task. We propose a method to crowdsource structured scholarly knowledge from paper authors with a web-based user interface supported by artificial intelligence. The interface enables authors to select key sentences for annotation. It integrates multiple machine learning algorithms to assist authors during the annotation, including class recommendation and key sentence highlighting. We envision that the interface is integrated in paper submission processes for which we define three main task requirements: The task has to be . We evaluated the interface with a user study in which participants were assigned the task to annotate one of their own articles. With the resulting data, we determined whether the participants were successfully able to perform the task. Furthermore, we evaluated the interface’s usability and the participant’s attitude towards the interface with a survey. The results suggest that sentence annotation is a feasible task for researchers and that they do not object to annotate their articles during the submission process.
Der Gold-Standard für OER-Materialien: Ein Kompendium für die professionelle Erstellung von Open Educational Resources (OER)
(Hamburg : Verlag ZLL21 e.V., 2020) Fahrenkrog, Gabriele; Muuß-Merholz, Jöran; Fabri, Blanche
[No abstract available]
Effects of Open Access. Literature study on empirical research 2010–2021
(Hannover : Technische Informationsbibliothek (TIB), 2024) Hopf, David; Dellmann, Sarah; Hauschke, Christian; Tullney, Marco
Open access — the free availability of scholarly publications — intuitively offers many benefits. At the same time, some academics, university administrators, publishers, and political decision-makers express reservations. Many empirical studies on the effects of open access have been published in the last decade. This report provides an overview of the state of research from 2010 to 2021. The empirical results on the effects of open access help to determine the advantages and disadvantages of open access and serve as a knowledge base for academics, publishers, research funding and research performing institutions, and policy makers. This overview of current findings can inform decisions about open access and publishing strategies. In addition, this report identifies aspects of the impact of open access that are potentially highly relevant but have not yet been sufficiently studied.
Identifying and correcting invalid citations due to DOI errors in Crossref data
(Dordrecht [u.a.] : Springer Science + Business Media B.V., 2022) Cioffi, Alessia; Coppini, Sara; Massari, Arcangelo; Moretti, Arianna; Peroni, Silvio; Santini, Cristian; Shahidzadeh Asadi, Nooshin
This work aims to identify classes of DOI mistakes by analysing the open bibliographic metadata available in Crossref, highlighting which publishers were responsible for such mistakes and how many of these incorrect DOIs could be corrected through automatic processes. By using a list of invalid cited DOIs gathered by OpenCitations while processing the OpenCitations Index of Crossref open DOI-to-DOI citations (COCI) in the past two years, we retrieved the citations in the January 2021 Crossref dump to such invalid DOIs. We processed these citations by keeping track of their validity and the publishers responsible for uploading the related citation data in Crossref. Finally, we identified patterns of factual errors in the invalid DOIs and the regular expressions needed to catch and correct them. The outcomes of this research show that only a few publishers were responsible for and/or affected by the majority of invalid citations. We extended the taxonomy of DOI name errors proposed in past studies and defined more elaborated regular expressions that can clean a higher number of mistakes in invalid DOIs than prior approaches. The data gathered in our study can enable investigating possible reasons for DOI mistakes from a qualitative point of view, helping publishers identify the problems underlying their production of invalid citation data. Also, the DOI cleaning mechanism we present could be integrated into the existing process (e.g. in COCI) to add citations by automatically correcting a wrong DOI. This study was run strictly following Open Science principles, and, as such, our research outcomes are fully reproducible.
INSPIRE: A European training network to foster research and training in cardiovascular safety pharmacology
(Amsterdam : Elsevier B.V., 2020) Guns, P.-J.D.; Guth, B.D.; Braam, S.; Kosmidis, G.; Matsa, E.; Delaunois, A.; Gryshkova, V.; Bernasconi, S.; Knot, H.J.; Shemesh, Y.; Chen, A.; Markert, M.; Fernández, M.A.; Lombardi, D.; Grandmont, C.; Cillero-Pastor, B.; Heeren, R.M.A.; Martinet, W.; Woolard, J.; Skinner, M.; Segers, V.F.M.; Franssen, C.; Van Craenenbroeck, E.M.; Volders, P.G.A.; Pauwelyn, T.; Braeken, D.; Yanez, P.; Correll, K.; Yang, X.; Prior, H.; Kismihók, G.; De Meyer, G.R.Y.; Valentin, J.-P.
Safety pharmacology is an essential part of drug development aiming to identify, evaluate and investigate undesirable pharmacodynamic properties of a drug primarily prior to clinical trials. In particular, cardiovascular adverse drug reactions (ADR) have halted many drug development programs. Safety pharmacology has successfully implemented a screening strategy to detect cardiovascular liabilities, but there is room for further refinement. In this setting, we present the INSPIRE project, a European Training Network in safety pharmacology for Early Stage Researchers (ESRs), funded by the European Commission's H2020-MSCA-ITN programme. INSPIRE has recruited 15 ESR fellows that will conduct an individual PhD-research project for a period of 36 months. INSPIRE aims to be complementary to ongoing research initiatives. With this as a goal, an inventory of collaborative research initiatives in safety pharmacology was created and the ESR projects have been designed to be complementary to this roadmap. Overall, INSPIRE aims to improve cardiovascular safety evaluation, either by investigating technological innovations or by adding mechanistic insight in emerging safety concerns, as observed in the field of cardio-oncology. Finally, in addition to its hands-on research pillar, INSPIRE will organize a number of summer schools and workshops that will be open to the wider community as well. In summary, INSPIRE aims to foster both research and training in safety pharmacology and hopes to inspire the future generation of safety scientists.
OER Recommendations to Support Career Development
(Piscataway, NJ : IEEE, 2020) Tavakoli, Mohammadreza; Faraji, Ali; Mol, Stefan T.; Kismihók, Gábor
This Work in Progress Research paper departs from the recent, turbulent changes in global societies, forcing many citizens to re-skill themselves to (re)gain employment. Learners therefore need to be equipped with skills to be autonomous and strategic about their own skill development. Subsequently, high-quality, on-line, personalized educational content and services are also essential to serve this high demand for learning content. Open Educational Resources (OERs) have high potential to contribute to the mitigation of these problems, as they are available in a wide range of learning and occupational contexts globally. However, their applicability has been limited, due to low metadata quality and complex quality control. These issues resulted in a lack of personalised OER functions, like recommendation and search. Therefore, we suggest a novel, personalised OER recommendation method to match skill development targets with open learning content. This is done by: 1) using an OER quality prediction model based on metadata, OER properties, and content; 2) supporting learners to set individual skill targets based on actual labour market information, and 3) building a personalized OER recommender to help learners to master their skill targets. Accordingly, we built a prototype focusing on Data Science related jobs, and evaluated this prototype with 23 data scientists in different expertise levels. Pilot participants used our prototype for at least 30 minutes and commented on each of the recommended OERs. As a result, more than 400 recommendations were generated and 80.9% of the recommendations were reported as useful.
Offene Bildungsinfrastrukturen : Anforderungen an eine OER-förderliche IT-Infrastruktur
(Hannover : Technische Informationsbibliothek, 2023) Wannemacher, Klaus; Stein, Mathias; Kaemena, Alena
Offene Bildungsinfrastrukturen sollen den freien Zugang zu (Hochschul-)Bildung unterstützen. Sie ermögli-chen Studierenden den uneingeschränkten Zugriff auf frei verfügbare Lehr- und Lernmaterialien (OER Open Educational Resources), erweitern hochschuldidaktische Möglichkeiten und tragen zur Sichtbarkeit von Lehrexpertise bei. Zudem leisten sie einen Beitrag zur Qualitätsförderung von Studium und Lehre und unterstützen den Kompetenzaufbau bei Lehrenden und Studierenden. Die Gesamtheit der offenen Bildungsinfrastrukturen differenziert sich weiter aus. Angesichts der vielfältigen Landschaft der OER-förderlichen IT-Infrastrukturen für die Hochschulen und der unzureichenden Integration von OER-Portalen, -Plattformen und -Tools erscheinen verstärkte Bemühungen um bessere Voraussetzungen zur Herstellung von Interoperabilität zwischen Informations- und Weiterbildungsportalen im Bereich der Hochschullehre geboten. Zu diesem Zweck führten das nordrhein-westfälische OER-Portal ORCA.nrw und das HIS-Institut für Hochschulentwicklung (HIS-HE) in Kooperation mit der Stiftung Innovation in der Hochschullehre eine Untersuchung durch, die auf Grundlage einer Erhebung des gegenwärtigen Entwicklungsstands Anregungen zur Herstellung von Interoperabilität zwischen Informations- und Weiterbildungsportalen im Hochschulkontext ge-ben möchte. Mittels einer Literaturanalyse, eines hybriden Expert:innen-Workshops sowie leitfadengestützter Expert:innen-Interviews wurde eine überblicksartige Darstellung OER-förderlicher IT-Infrastrukturen für den Hochschulbereich unter besonderer Berücksichtigung lehrbezogener und didaktischer Implikationen er-arbeitet. Zudem wurden Anforderungen an eine offene Bildungsinfrastruktur aus technischer, hochschuldidaktischer und bildungsorganisatorischer Perspektive ermittelt und potenzielle künftige Entwicklungsschritte definiert. Im Rahmen der durchgeführten Erhebungsschritte zeigte sich, dass sich die Landschaft der offenen Bildungsinfrastrukturen im Hochschulsektor kontinuierlich ausdifferenziert und durch ein hohes Maß an Vielfalt geprägt ist. Sie umfasst Vernetzungseinrichtungen, OER-Repositorien und -Referatorien, Informations- und Weiterbildungsportale sowie Stand-alone-Lösungen wie lokale Installationen von Lernmanagementsystemen (LMS) an Hochschulen. Das Bestreben zum Schaffen von Aggregationsmechanismen für OER (vgl. OERSI, Digitale Vernetzungsinfrastruktur Bildung u. ä.) befindet sich in einem frühen Stadium. Die dezentrale Verortung offener Bildungsinfrastrukturen scheint dem Ziel der leichten Auffindbarkeit und ausgiebigen Weiternutzung offener Lehr- und Lernmaterialien teilweise entgegenzustehen. Als zentrale Herausforderung erweist sich daher die Vernetzung bestehender Portale und Tools durch die Nutzung eines allgemein anerkannten Metadatenprofils und Standardvokabulars für Lehr- und Lernmaterialien, eine stärkere Vernetzung bestehender Infrastrukturen durch einen Aggregationsmechanismus für digitale Lernressourcen sowie eine verbesserte Interoperabilität entsprechender Infrastrukturen durch das Schaffen von Schnittstellen und das Nutzen von Plugins. Zugleich wurde deutlich, dass technische, organisatorische und didaktische Unterstützungsdienste für eine ausgiebige Nutzung von OER bislang noch zurück-haltend angeboten werden. Es bedarf mittelfristig einer stärkeren Automatisierung im Bereich der Veröffentlichung von OER sowie einer stärkeren Einbeziehung von Communitys of Practice in die weitere Ausdifferenzierung der Infrastrukturen. Auch mangelt es bislang an empirischen Erhebungen zu der Praxis und den Bedarfslagen der Produzent:innen und Nutzer:innen von OER. Zudem wird die Entwicklung OER-förderlicher IT-Infrastrukturen bislang noch zu selten auf einer strategischen Ebene adressiert und forciert. Eine Analyse gängiger Anwendungsfälle für die Entwicklung und Nutzung von OER wurde bislang noch kaum geleistet. Zugleich zeigen sich vielversprechende Bestrebungen zur Etablierung eines auf die spezifischen Belange offener Lehre an den Hochschulen zugeschnittener Metadatenprofile. Auf einer organisationalen Ebene könnten künftig neben OER-Plattformen und Hochschulen mit lokalen Installationen von LMS auch Hochschulbibliotheken als Betreiber und Dienstleister für OER-förderliche IT-Infrastrukturen auftreten.
Open-Access-Finanzierung
(Bonn : Bundesinstitut für Berufsbildung (BIBB), 2022) Kändler, Ulrike; Wohlgemuth, Michael; Ertl, Hubert; Rödel, Bodo
[no abstract available]
Orte des Gestapoterrors im heutigen Niedersachsen
(Meyrin : CERN, 2020-12-09) Doerry, Janine; Blümel, Ina; Cartellieri, Simone; Heller, Lambert; Wagner, Jens-Christian
Auszug aus dem Antrag im MWK-Förderprogramm Pro*Niedersachsen – Kulturelles Erbe – Sammlungen und Objekte
Publizieren in wissenschaftlichen Zeitschriften
(Bielefeld : Transcript, 2020) Kaier, Christian; van Edig, Xenia
Zeitschriftenartikel sind die von Wissenschaftlerinnen und Wissenschaftlern insgesamt am häufigsten gewählte Publikationsform. Ein Verständnis der Arbeits- und Funktionsweise wissenschaftlicher Zeitschriften sowie von Rollen und Publikationsprozessen ist daher im Bereich der Publikationsberatung essenziell. Dieser Beitrag soll dafür Grundlagen und weiterführende Hinweise bieten.
Scholarly event characteristics in four fields of science: a metrics-based analysis
(Berlin : Springer Nature, 2020) Fathalla, S.; Vahdati, S.; Lange, C.; Auer, Sören
One of the key channels of scholarly knowledge exchange are scholarly events such as conferences, workshops, symposiums, etc.; such events are especially important and popular in Computer Science, Engineering, and Natural Sciences.However, scholars encounter problems in finding relevant information about upcoming events and statistics on their historic evolution.In order to obtain a better understanding of scholarly event characteristics in four fields of science, we analyzed the metadata of scholarly events of four major fields of science, namely Computer Science, Physics, Engineering, and Mathematics using Scholarly Events Quality Assessment suite, a suite of ten metrics.In particular, we analyzed renowned scholarly events belonging to five sub-fields within Computer Science, namely World Wide Web, Computer Vision, Software Engineering, Data Management, as well as Security and Privacy.This analysis is based on a systematic approach using descriptive statistics as well as exploratory data analysis. The findings are on the one hand interesting to observe the general evolution and success factors of scholarly events; on the other hand, they allow (prospective) event organizers, publishers, and committee members to assess the progress of their event over time and compare it to other events in the same field; and finally, they help researchers to make more informed decisions when selecting suitable venues for presenting their work.Based on these findings, a set of recommendations has been concluded to different stakeholders, involving event organizers, potential authors, proceedings publishers, and sponsors. Our comprehensive dataset of scholarly events of the aforementioned fields is openly available in a semantic format and maintained collaboratively at OpenResearch.org.

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