Otmane Azeroual

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• Dr.-Ing.
• Senior Researcher & Lecturer at Deutsches Zentrum für Hochschul- und Wissenschaftsforschung GmbH

In today’s world, big data has rapidly evolved, presenting organiza-tions with a multitude of challenges in managing, integrating, and leveraging their most valuable resource. As data volumes and complexity continue to grow, the question arises: How can organizations effectively and efficiently manage their data to extract valuable insights? Two ap...

The age of digitization has led to a significant increase in the amount and variety of data, particularly within the research domain, where data previously stored in paper form has now been digitized and integrated into research management processes. The rapid growth of Big Data, driven by technologies like the Internet of Things, presents challeng...

In today’s landscape of research management, the integration of Information Technology (IT) methods and data science has emerged as a powerful paradigm for enhancing decision-making processes. This paper examines the central role of IT-supported research management, such as Research Information Systems (RIS), in leveraging data science methods for...

Climate change and the rapid depletion of natural resources present significant global challenges that demand innovative and sustainable solutions. Traditional resource management approaches are increasingly inadequate in addressing these complexities, creating a pressing need for advanced technologies. Artificial Intelligence (AI) and Data Science...

Zusammenfassung In der Ära rasanter technologischer Fortschritte erweisen sich traditionelle Methoden des Forschungsinformationsmanagements als unzureichend. Präsentiert wird eine Projektskizze, die das Konzept „Data Management 4.0“ einführt. Dieses Konzept nutzt Künstliche Intelligenz (KI), um Forschungsinformationssysteme signifikant zu verbesser...

The scientific landscape in France and Germany is undergoing a profound transformation characterized by the increasing integration of Current Research Information Systems (CRIS). These systems are essential for the management and evaluation of scientific activities and play a central role in the transition to Open Science and research ethics. This...

Data quality (DQ) is a fundamental element for the reliability and utility of data across various domains. The emergence of generative AI technologies, such as GPT-4, has introduced innovative methods for automating data cleaning, validation, and enhancement processes. This paper investigates the role of generative AI, particularly ChatGPT, in tran...

As the systems driven by artificial intelligence (AI) become increasingly integrated across various applications, ensuring their security is paramount to mitigate potential risks and vulnerabilities. Threat intelligence plays a pivotal role in identifying, analysing, and mitigating cybersecurity threats, particularly those targeting AI systems. Sec...

Zusammenfassung Das digitale Zeitalter ist geprägt von rasanter Entwicklung, Wachstum, Innovation und Disruption. Organisationen müssen sich an die neue digitale Landschaft anpassen, um wettbewerbsfähig zu bleiben. Die digitale Transformation umfasst mehr als nur die Implementierung neuer Technologien. Eine digitale Transformationsstrategie ist ein...

900 mm Diameter GRP ( Glass Reinforced Plastic Fibre) pipeline for portable water installation. All the fittings can be made on site. Light in weight so has to be careful while encasing with concrete. Due to its light weight during encasing with concrete buoyant effect is acted on pipe and pipe get lifted so encasing activity is done very carefully...

Definition In the context of open science, universities, research-performing and funding organizations and authorities worldwide are moving towards more responsible research assessment (RRA). In 2022, the European Coalition for Advancing Research Assessment (CoARA) published an agreement with ten commitments, including the recognition of the “diver...

Zusammenfassung Die Veröffentlichung von Forschungsaktivitäten und -ergebnissen sowie die verschiedenen Beteiligten stellen den Datenaustausch, die Exploration und die Visualisierung vor große Herausforderungen. Für die vom Bundesministerium für Bildung und Forschung (BMBF) geförderte National Academics Panel Study (Nacaps) hat das Deutsche Zentrum...

This paper presents multi- and interdisciplinary approaches for finding the appropriate AI technologies for research information. Professional research information management (RIM) is becoming increasingly important as an expressly data-driven tool for researchers. It is not only the basis of scientific knowledge processes, but also related to othe...

The paper offers a comprehensive examination of the ethical considerations surrounding the management of research information within an organization. It includes a summary of survey findings and an overview of ongoing research efforts. Special attention is given to ethical standards pertaining to data quality, data models, and data formats, which a...

While the topics of CRIS and FAIR are not new, after decades of research on CRIS, CRIS and their FAIRness remain a relatively overlooked dimension of CRIS. To address this problem, we conduct a systematic literature review (SLR) that connects the fragmented knowledge accumulated through the observation of CRIS development/maturing dynamics and atte...

The carbon market is the most important policy tool for achieving carbon peak and carbon neutralization. Enterprises are significant players in the carbon market, and this study aimed to identify if their willingness to participate is connected to the carbon market’s stability and, at the same time, whether it is also relevant for policy design and...

Data quality in companies is decisive and critical to the benefits their products and services can provide. However, in heterogeneous IT infrastructures where, e.g., different applications for Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), product management, manufacturing, and marketing are used, duplicates, e.g., mult...

The volume of data in companies and in the private sector is already gigantic today. Mobile devices such as smartphones constantly collect data on all possible environmental conditions. When surfing the Internet, everyone leaves an endless digital trail. The Internet of Things (IoT) promises comprehensive networking of all everyday devices and prod...

The use of Elastic Stack (ELK) solutions and Knowledge Graphs (KGs) has attracted a lot of attention lately, with promises of vastly improving business performance based on new business insights and better decisions. This allows organizations not only to reap the ultimate benefits of data governance but also to consider the widest possible range of...

The digital support for scientific reasoning presents contrasting results. Bibliometric services are improving, but not academic assessment; no service for scholars relies on logs of web usage to base query strategies for relevance judgments (or assessor shifts). Our Scientific Knowledge Graph GRAPHYP innovates with interpretable patterns of web us...

Nowadays, there are billions interconnected devices forming Cyber-Physical Systems (CPS), Internet of Things (IoT) and Industrial Internet of Things (IIoT) ecosystems. With an increasing number of devices and systems in use, amount and the value of data, the risks of security breaches increase. One of these risks is posed by open data sources, whic...

Best Mobile Application for 24x7 Water Supply Network reducing overall cost of project from 100 percent to about 45 to 50 percent and saving almost 40 to 50 percent.

Remarkable Achievements By Hydraulic Engineer Sanjay Tarakant Jha from Vapi Municipality INDIA

Consolidation of the research information improves the quality of data integration, reducing duplicates between systems and enabling the required flexibility and scalability when processing various data sources. We assume that the combination of a data lake as a data repository and a data wrangling process should allow low-quality or “bad” data to...

Current research information systems (CRIS) evaluate research performance and are intended to contribute to the continuous improvement of research. Based on former research on the ethical dimensions of CRIS, our paper presents the results of a survey with a small sample of representatives of ethics committees from different European countries on et...

When collecting, storing and providing research information, it should be taken into account whether and how the research information will be published. It is important under what framework conditions the data will be used further, what rights the researchers involved have to the research information, whether the research group or the project will...

Digitization in the research domain refers to the increasing integration and analysis of research information in the process of research data management. However, it is not clear whether it is used and, more importantly, whether the data are of sufficient quality, and value and knowledge could be extracted from them. FAIR principles (Findability, A...

The variety and diversity of published content are currently expanding in all fields of scholarly communication. Yet, scientific knowledge graphs (SKG) provide only poor images of the varied directions of alternative scientific choices, and in particular scientific controversies, which are not currently identified and interpreted. We propose to use...

This paper focuses on the issue of the transparency maturity of open data ecosystems seen as the key for the development and maintenance of sustainable, citizen-centered, and socially resilient smart cities. This study inspects smart cities’ data portals and assesses their compliance with transparency requirements for open (government) data. The ex...

Zusammenfassung Forschungsinformationssysteme evaluieren Forschungsleistungen und sollen zur kontinuierlichen Verbesserung der Forschung beitragen. Basierend auf einer Online-Umfrage und auf Interviews mit Experten der Organisation euroCRIS, gibt dieser Beitrag einen Überblick über die ethischen Aspekte im Bereich des Forschungsinformationsmanageme...

The cognitive manifold of published content is currently expanding in all areas of science. However, Scientific Knowledge Graphs (SKGs) only provide poor pictures of the adversarial directions and scientific controversies that feed the production of knowledge. In this Article, we tackle the understanding of the design of the information space of a...

The data management process is characterised by a set of tasks where data quality management (DQM) is one of the core components. Data quality, however, is a multidimensional concept, where the nature of the data quality issues is very diverse. One of the most widely anticipated data quality challenges, which becomes particularly vital when data co...

Recommendation (recommender) systems have played an increasingly important role in both research and industry in recent years. In the area of publication data, for example, there is a strong need to help people find the right research information through recommendations and scientific reports. The difference between search engines and recommendatio...

The use of research information systems (RIS) depends to a large extent on the quality of the data recorded there. Scientifically proven methods and procedures are required to efficiently ensure high data quality. This paper proposes a concept for managing the quality of research data that was developed by the author as part of the dissertation. It...

Dieses Kapitel geht vertiefend auf einzelne Besonderheiten von FIS mit einer positiven Auswirkung auf die Datenqualität ein, nebenher wird auf die vorkommende Datenqualitätsprobleme und deren konkreten Ursachen eingegangen. Dazu sollen Verfahren, die zur Verbesserung von Datenqualität in FIS führen, untersucht werden.

Dieses Kapitel führt ein Proof-of-Concept durch. Es basiert auf dem in dieser Dissertation im Rahmen von FIS für Hochschulen und AUFs entwickelten Lösungsverfahren.

Dieses Kapitel führt in die inhaltlichen und konzeptionellen Grundlagen über das deutsche Hochschulsystem, sowie die Forschungsinformationen und die Verwendung von Forschungsinformationssystemen ein, um ein einheitliches Verständnis zu erzielen.

Für die im Kapitel 3 geformte Lösung zur Verbesserung der Datenqualität in FIS legt dieses Kapitel die Nutzerakzeptanz von FIS und die Abhängigkeit mit der Datenqualität anhand der Umfrageergebnisse dar.

Der Umgang mit Forschungsinformationen hat in den letzten Jahren einen hohen Stellenwert erlangt und ist als Thema und Aufgabe anerkannt worden. Hochschulen und AUFs brauchen Forschungsinformationen zum Monitoring und zur Evaluierung ihrer Forschungsaktivitäten und für strategische Entscheidungen über unterschiedliche Anwendungs- und Nutzungsszenar...

The open science policy questions the criteria and procedures of research assessment, while at the same time emphasizing the fundamental principles of scientific ethics, such as transparency, openness and integrity. In this context, since 2020 we have been conducting an analysis of the ethical dimension of information systems dedicated to research...

Since the turn of the millennium, the volume of data has increased significantly in both industries and scientific institutions. The processing of these volumes and variety of data we are dealing with are unlikely to be accomplished with conventional software solutions. Thus, new technologies belonging to the big data processing area, able to distr...

Collecting, integrating and storing input of research information from a variety of heterogeneous data sources and different independent information systems into the research information system (RIS) can result in various data errors and abnormalities, which, on the one hand, can have a different negative impact on the quality of the data and, on t...

Nowadays, there are billions interconnected devices forming Cyber-Physical Systems, Internet of Things (IoT) and Industrial Internet of Things (IIoT) ecosystems. With an increasing number of devices and systems in use, amount and the value of data, the risks of security breaches increase. One of these risks is posed by open data sources, by which a...

PurposeThe purpose of this paper is to present empirical evidence on the implementation, acceptance and quality-related aspects of research information systems (RIS) in academic institutions.Design/methodology/approachThe study is based on a 2018 survey with 160 German universities and research institutions.FindingsThe paper presents recent figures...

Unlimited change in scientific terminology challenges integrity in scientific knowledge graph (SKG) representation, while current data and modeling standards, mostly document oriented, hardly allow a resilient semantic upgrade of scholarly content. Moreover, results of a “multimodal knowledge acquisition” are required for an efficient upgrade of se...

The topic of Ethics and CRIS has been raised at previous euroCRIS membership meetings but has never specifically been addressed at any euroCRIS event before. Following the publication of their paper "Research Ethics, Open Science and CRIS" in MDPI Publications in 2020, https://doi.org/10.3390/publications8040051, the presenters have conducted a sur...

The outburst of the COVID-19 pandemic has boosted the need for seamless, unrestricted, fast, and free access to the latest research results on the virus, on its treatment, prevention, protocols, and so on. Open access to publications and research data, suddenly, became self-evident, not only for researchers in life and medical sciences but also for...

Zusammenfassung Die Bedeutung von Daten für Gesellschaft und Wirtschaft kann nicht überschätzt werden und nimmt im Zuge von Digitalisierung weiter zu. Die Nachnutzung vorhandener Daten bietet erhebliche Vorteile auf wissenschaftlicher, politischer, sozialer, kultureller und insbesondere wirtschaftlicher Ebene. Die Öffnung von Datensammlungen (Open...

Data migration is required to run data-intensive applications. Legacy data storage systems are not capable of accommodating the changing nature of data. In many companies, data migration projects fail because their importance and complexity are not taken seriously enough. Data migration strategies include storage migration, database migration, appl...

Data quality has been considerably faced with more attention in recent years. While improving the quality of any type of information system needs to apply data quality dimensions, this process is a strategic decision of any organization. Current Research Information System (CRIS) is a state of the art information system which manages different proc...

In the context of open science, good research data management(RDM), including data sharing and data reuse, has become a majorgoal of research policy. However, studies and monitors reveal thatopen science practices are not yet widely mainstream. Rewardsand incentives have been suggested as a solution, to facilitate andaccelerate the development of o...

Big data have become a global strategic issue, as increasingly large amounts of unstructured data challenge the IT infrastructure of global organizations and threaten their capacity for strategic forecasting. As experienced in former massive information issues, big data technologies, such as Hadoop, should efficiently tackle the incoming large amou...

Research infrastructures (RI) offer researchers a multitude of research opportunities and services and play a key role in the performance, innovative strength and international competitiveness of science. As an important part of the generation and use of new knowledge and technologies, they are essential for research policies. Because of their stra...

The purpose of this paper is to analyze how current research information systems (CRIS) take into account ethical issues, especially in the environment of open science. The analysis is based on a review of the literature on research information management, CRIS, open science and research ethics. The paper provides a framework for the assessment of...

Current research information systems (CRIS) and institutional repositories (IR) were developed as clearly distinguished systems, with different objectives and functionalities, standards and data models, and for different needs and user groups. While academic librarians are often deeply committed to the management of open access and IR, they are les...

Databases such as research data management systems (RDMS) provide the research data in which information is to be searched for. They provide techniques with which even large amounts of data can be evaluated efficiently. This includes the management of research data and the optimization of access to this data, especially if it cannot be fully loaded...

Researchers need to be able to integrate ever-increasing amounts of data into their institutional databases, regardless of the source, format, or size of the data. It is then necessary to use the increasing diversity of data to derive greater value from data for their organization. The processing of electronic data plays a central role in modern so...

The quality assurance of publication data in collaborative knowledge bases and in current research information systems (CRIS) becomes more and more relevant by the use of freely available spatial information in different application scenarios. When integrating this data into CRIS, it is necessary to be able to recognize and assess their quality. On...

In our present paper, the influence of data quality on the success of the user acceptance of research information systems (RIS) is investigated and determined. Until today, only a little research has been done on this topic and no studies have been carried out. So far, just the importance of data quality in RIS, the investigation of its dimensions...

The provision, processing and distribution of research information are increasingly supported by the use of research information systems (RIS) at higher education institutions. National and international exchange formats or standards can support the validation and use of research information and increase their informative value and comparability th...

With the steady increase in the number of data sources to be stored and processed by higher education and research institutions, it has become necessary to develop Research Information Systems, which will store this research information in the long term and make it accessible for further use, such as reporting and evaluation processes, institutiona...

To provide scientific institutions with comprehensive and well-maintained documentation of their research information in a current research information system (CRIS), they have the best prerequisites for the implementation of text and data mining (TDM) methods. Using TDM helps to better identify and eliminate errors, improve the process, develop th...

With the increased accessibility of research information, the demands on research information systems (RIS) that are expected to automatically generate and process knowledge are increasing. Furthermore, the quality of the RIS data entries of the individual sources of information causes problems. If the data is structured in RIS, users can read and...

Purpose The purpose of this paper is to present empirical evidence on the implementation, acceptance and quality-related aspects of research information systems (RIS) in academic institutions. Design/methodology/approach The study is based on a 2018 survey with 160 German universities and research institutions. Findings The paper presents recent...

The purpose of this paper is to explore the impact of the cloud technology on current research information systems (CRIS). Based on an overview of published literature and on empirical evidence from surveys, the paper presents main characteristics, delivery models, service levels and general benefits of cloud computing. The second part assesses how...

The purpose of this paper is to explore the impact of the cloud technology on current research information systems (CRIS). Based on an overview of published literature and on empirical evidence from surveys, the paper presents main characteristics, delivery models, service levels and general benefits of cloud computing. The second part assesses how...

Integrating data from a variety of heterogeneous internal and external data sources (e.g. CERIF and RCD data models with different modeling languages) in a federated database system such as “Research Information Management System (RIMS)” is becoming more challenging for (inter-)national universities and research institutions. Data quality is an imp...

For the permanent establishment and use of a RIS in universities and academic institutions, it is absolutely necessary to ensure the quality of the research information, so that the stakeholders of the science system can make an adequate and reliable basis for decision-making. However, to assess and improve data quality in RIS, it must be possible...

The topic of data integration from external data sources or independent IT-systems has received increasing attention recently in IT departments as well as at management level, in particular concerning data integration in federated database systems. An example of the latter are commercial research information systems (RIS), which regularly import, c...

Collecting, integrating, storing and analyzing data in a database system is nothing new in itself. To introduce a current research information system (CRIS) means that scientific institutions must provide the required information on their research activities and research results at a high quality. A one-time cleanup is not sufficient; data must be...

The collection, transfer and integration of research information into different research Information systems can result in different data errors that can have a variety of negative effects on data quality. In order to detect errors at an early stage and treat them efficiently, it is necessary to determine the clean-up measures and the new technique...

In order to introduce an integrated research information system, this will provide scientific institutions with the necessary information on research activities and research results in assured quality. Since data collection, duplication, missing values, incorrect formatting, inconsistencies, etc. can arise in the collection of research data in diff...

The rapid increase in data volumes in companies has meant that momentous and comprehensive information gathering is barely possible by manual means. Business intelligence solutions can help here. They provide tools with appropriate technologies to assist with the collection, integration, storage, editing, and analysis of existing data. While almost...

In the implementation and use of research information systems (RIS) in scientific institutions, text data mining and semantic technologies are a key technology for the meaningful use of large amounts of data. It is not the collection of data that is difficult, but the further processing and integration of the data in RIS. Data is usually not unifor...

In the implementation and use of research information systems (RIS) in scientific institutions, text data mining and semantic technologies are a key technology for the meaningful use of large amounts of data. It is not the collection of data that is difficult, but the further processing and integration of the data in RIS. Data is usually not unifor...

Die Abbildung von Forschungsinformationen wird heute vermehrt durch den Einsatz von Forschungsinformationssystemen (FIS) unterstützt. Um Fehler in den Datenquellen beim Import ins FIS frühzeitig zu entdecken, zu korrigieren und zu verbessern, gilt es die neuen Techniken bzw. Methoden zu Data Cleansing, Data Aggregation und Data Profiling zu ermitte...

The implementation of research information systems at German universities and research institutions is currently a topical subject. With their help, the documentation and reporting of the research activities of the respective institution can be supported and a significant part of the data incurring there can be managed. As there are usually many da...

In recent years, research information systems (RIS) have become an integral part of the university’s IT landscape. At the same time, many universities and research institutions are still working on the implementation of such information systems. Research information systems support institutions in the measurement, documentation, evaluation and comm...

The rapid increase in data volumes in companies has meant that momentous and comprehensive information gathering is barely possible by manual means. Business intelligence solutions can help here. They provide tools with appropriate technologies to assist with the collection, integration, storage, editing, and analysis of existing data. While almost...

The success or failure of a RIS in a scientific institution is largely related to the quality of the data available as a basis for the RIS applications. The most beautiful Business Intelligence (BI) tools (reporting, etc.) are worthless when displaying incorrect, incomplete, or inconsistent data. An integral part of every RIS is thus the integratio...

The rapid increase in data volumes in companies has meant that momentous and comprehensive information gathering is barely possible by manual means. Business intelligence solutions can help here. They provide tools with appropriate technologies to assist with the collection, integration, storage, editing, and analysis of existing data. While almost...

The collection, transfer and integration of research information into different research information systems can result in different data errors that can have a variety of negative effects on data quality. In order to detect errors at an early stage and treat them efficiently, it is necessary to determine the clean-up measures and the new technique...

In order to introduce an integrated research information system, this will provide scientific institutions with the necessary information on research activities and research results in assured quality. Since data collection, duplication, missing values, incorrect formatting, inconsistencies, etc. can arise in the collection of research data in diff...