bluuebunny/crossref_metadata_2025_split huggingface dataset:
Digital Research Infrastructure
Authors: Stührenberg Maik , Schonefeld Oliver , Witt Andreas 
Published: March 2021

AbstractDigital research infrastructures can be divided into four categories: large equipment, IT infrastructure, social infrastructure, and information infrastructure. Modern research institutions often employ both IT infrastructure and information infrastructure, such as databases or large-scale research data. In addition, information infrastructure depends to some extent on IT infrastructure. In this paper, we discuss the IT, information, and legal infrastructure issues that research institutions face.
CLARIN-D: An IT-Based Research Infrastructure for the Humanities and Social Sciences
Authors: Heyer Gerhard , Böhlke Volker 
Published: March 2021

AbstractThe paper discusses the idea of bridging the gap between computer sciences and the humanities by referring to an e-humanities infrastructure that provides tools and services for well-defined and frequently encountered tasks. The main goal of this infrastructure is to enable researchers in the humanities and social sciences to better exploit their potential by reusing available digital resources, and thus to increase the efficiency of e-humanities projects. CLARIN-D is an example of such a research infrastructure. The paper provides a brief overview of the basic principles and services of the CLARIN-D infrastructure, such as metadata harvesting, federated content search, and chaining Web services.
Designing External Knowledge Communication in a Research Network The Case of Sustainable Land Management
Authors: Köhler Thomas , Weith Thomas , Herbst Sabrina , Gaasch Nadin 
Published: March 2021

AbstractDesigning knowledge communication with external partners is a core activity of research networks. In science, such communication has been addressed only recently and is still considered as non-academic activity. Successful communication with practitioners, that is knowledge transfer, is a crucial factor for effective research. In the age of online communication, this requires special attention and skills, for example related to social media communication. Based on our own empirical results derived from interviews, the authors identify what factors affect the communication process and how the design of communication content may be influenced.To do so, successful examples of communication with external stakeholders are presented. For the theoretical basis, science communication, knowledge communication, knowledge management, and knowledge transfer were selected and consolidated. Although the findings stem from a research network specializing in sustainable land management, they can be transferred to other academic collaborations. Our results indicate that external communication is effective when knowledge has been transferred between academics and practitioners.
Conclusion
Authors: Theisen-Womersley Gail 
Published: March 2021

AbstractThe number of refugees across the globe is growing dramatically—a trend predicted to continue due to a global increase in social and political instability as well as socioeconomic conflicts. In places where violence is seen as a necessary factor in achieving peace, ongoing armed conflict, and displacement will likely contribute to continued psychological impairment and suffering among those affected (Morina et al., .Frontiers in Psychiatry 9:433, 2018). Indeed, research overwhelmingly attests to the alarmingly high rates of PTSD among this population (Schouler-Ocak, M., Laban, C. J., Bäärnhielm, S., Kastrup, M. C., Dein, S., & Wintrob, R. (2019). Transcultural psychiatry: Refugee, asylum seeker and immigrant patients over the globe. In A. Javad & K. Fountoulakis (Eds.), Advances in Psychiatry (pp. 637–655). Cham: Springer.).
Research Data Infrastructures and Engineering Metadata
Authors: Horsch Martin Thomas , Chiacchiera Silvia , Cavalcanti Welchy Leite , Schembera Björn 
Published: March 2021

AbstractThis chapter introduces metadata models as a semantic technology for knowledge representation to describe selected aspects of a research asset. The process of building a hierarchical metadata model is reenacted in this chapter and highlighted by the example of EngMeta. Moreover, an overview on data infrastructures is given, the general architecture and functions are disscussed, and multiple examples of data infrastructures in materials modelling are given.
Semantic Technology for Simulations and Molecular Particle-Based Methods
Authors: Horsch Martin Thomas , Chiacchiera Silvia , Cavalcanti Welchy Leite , Schembera Björn 
Published: March 2021

AbstractIn this Chapter we discuss the role of ontologies for simulations, in the context of materials modelling in general and of molecular particle-based methods in particular. After a brief overview of the literature and possible applications, we present the VIMMP ontologies that allow to describe software capabilities and to further specify the various algorithms via the involved variables: the VImmp Ontology of Software (VISO) and the Vimmp Ontology of Variables (VOV).
Applications of the Metadata Standards
Authors: Horsch Martin Thomas , Chiacchiera Silvia , Cavalcanti Welchy Leite , Schembera Björn 
Published: March 2021

AbstractThis chapter addresses issues related to the practical use of the metadata standards, including syntactic interoperability and concrete scenarios from molecular modelling and simulation. It discusses challenges that arise from semantic heterogeneity, wherever multiple interoperability standards are concurrently employed for identical or overlapping domains of knowledge, or where domain ontologies need to be matched to top-level ontologies such as the European Materials and Modelling Ontology (EMMO).
PASTA: An Efficient Proactive Adaptation Approach Based on Statistical Model Checking for Self-Adaptive Systems
Authors: Shin Yong-Jun , Cho Eunho , Bae Doo-Hwan 
Published: March 2021

AbstractProactive adaptation, in which the adaptation for a system’s reliable goal achievement is performed by predicting changes in the environment, is considered as an effective alternative to reactive adaptation, in which adaptation is performed after observing changes. When predicting the environmental changes, the prediction may be uncertain, so it is necessary to verify and confirm an adaptation’s consequences before execution. To resolve the uncertainty, probabilistic model checking (PMC) has been utilized for verification of adaptation tactics’ effects on the goal of a self-adaptive system (SAS). However, PMC-based approaches have limitations on the state-explosion problem of complex SAS model verification and the modeling languages supported by the model checkers. In this paper, to overcome the limitations of the PMC-based approaches, we propose an efficient Proactive Adaptation approach based on STAtistical model checking (PASTA). Our approach allows SASs to mitigate the uncertainty of the future environment, faster than the PMC-based approach, by producing statistically sufficient samples for verification of adaptation tactics based on statistical model checking (SMC) algorithms. We provide algorithmic processes, a reference architecture, and an open-source implementation skeleton of PASTA for engineers to apply it for SAS development. We evaluate PASTA on two SASs using actual data and show that PASTA is efficient comparing to the PMC-based approach. We also provide a comparative analysis of the advantages and disadvantages of PMC- and SMC-based proactive adaptation to guide engineers’ decision-making for SAS development.
CoVeriTest with Adaptive Time Scheduling (Competition Contribution)
Authors: Jakobs Marie-Christine , Richter Cedric 
Published: March 2021

AbstractCoVeriTest, which is integrated in the analysis framework CPAchecker, adopts verification technology for test-case generation. It encodes individual test goals as reachability queries, which are then processed by verifiers. To increase the effectiveness on a broad class of testing tasks, CoVeriTest leverages the strengths of two different analyses: an explicit value analysis and predicate abstraction. Similar to TestComp’20, the two analyses are interleaved and the time duration of an interleaving segment is calculated dynamically. However, the calculation of the time duration focuses on the predicted future performance instead of the past performance, thus, rewarding analyses that likely cover open test goals.
Engineering Secure Self-Adaptive Systems with Bayesian Games
Authors: Li Nianyu , Zhang Mingyue , Kang Eunsuk , Garlan David 
Published: March 2021

AbstractSecurity attacks present unique challenges to self-adaptive system design due to the adversarial nature of the environment. Game theory approaches have been explored in security to model malicious behaviors and design reliable defense for the system in a mathematically grounded manner. However, modeling the system as a single player, as done in prior works, is insufficient for the system under partial compromise and for the design of fine-grained defensive strategies where the rest of the system with autonomy can cooperate to mitigate the impact of attacks. To deal with such issues, we propose a new self-adaptive framework incorporating Bayesian game theory and model the defender (i.e., the system) at the granularity ofcomponents. Under security attacks, the architecture model of the system is translated into aBayesian multi-player game, where each component is explicitly modeled as an independent player while security attacks are encoded as variant types for the components. The optimal defensive strategy for the system is dynamically computed by solving the pure equilibrium (i.e., adaptation response) to achieve the best possible system utility, improving the resiliency of the system against security attacks. We illustrate our approach using an example involving load balancing and a case study on inter-domain routing.
An Abstract Contract Theory for Programs with Procedures
Authors: Lidström Christian , Gurov Dilian 
Published: March 2021

AbstractWhen developing complex software and systems, contracts provide a means for controlling the complexity by dividing the responsibilities among the components of the system in a hierarchical fashion. In specific application areas, dedicated contract theories formalise the notion of contract and the operations on contracts in a manner that supports best the development of systems in that area. At the other end, contract meta-theories attempt to provide a systematic view on the various contract theories by axiomatising their desired properties. However, there exists a noticeable gap between the most well-known contract meta-theory of Benveniste et al. [5], which focuses on the design of embedded and cyber-physical systems, and the established way of using contracts when developing general software, following Meyer’s design-by-contract methodology [18]. At the core of this gap appears to be the notion of procedure: while it is a central unit of composition in software development, the meta-theory does not suggest an obvious way of treating procedures as components.In this paper, we provide a first step towards a contract theory that takes procedures as the basic building block, and is at the same time an instantiation of the meta-theory. To this end, we propose an abstract contract theory for sequential programming languages with procedures, based on denotational semantics. We show that, on the one hand, the specification of contracts of procedures in Hoare logic, and their procedure-modular verification, can be cast naturally in the framework of our abstract contract theory. On the other hand, we also show our contract theory to fulfil the axioms of the meta-theory. In this way, we give further evidence for the utility of the meta-theory, and prepare the ground for combining our instantiation with other, already existing instantiations.
Analysis of Markov Jump Processes under Terminal Constraints
Authors: Backenköhler Michael , Bortolussi Luca , Großmann Gerrit , Wolf Verena 
Published: March 2021

AbstractMany probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints. We propose a solution to thisbridging problemfor the widely used class of population-structured Markov jump processes. The method is based on a state-space lumping scheme that aggregates states in a grid structure. The resulting approximate bridging distribution is used to iteratively refine relevant and truncate irrelevant parts of the state-space. This way, the algorithm learns a well-justified finite-state projection yielding guaranteed lower bounds for the system behavior under endpoint constraints. We demonstrate the method’s applicability to a wide range of problems such as Bayesian inference and the analysis of rare events.
On Satisficing in Quantitative Games
Authors: Bansal Suguman , Chatterjee Krishnendu , Vardi Moshe Y. 
Published: March 2021

AbstractSeveral problems in planning and reactive synthesis can be reduced to the analysis of two-player quantitative graph games.Optimizationis one form of analysis. We argue that in many cases it may be better to replace the optimization problem with thesatisficing problem, where instead of searching for optimal solutions, the goal is to search for solutions that adhere to a given threshold bound.This work defines and investigates the satisficing problem on a two-player graph game with the discounted-sum cost model. We show that while the satisficing problem can be solved using numerical methods just like the optimization problem, this approach does not render compelling benefits over optimization. When the discount factor is, however, an integer, we present another approach to satisficing, which is purely based on automata methods. We show that this approach is algorithmically more performant – both theoretically and empirically – and demonstrates the broader applicability of satisficing over optimization.
Improving Neural Network Verification through Spurious Region Guided Refinement
Authors: Yang Pengfei , Li Renjue , Li Jianlin , Huang Cheng-Chao , Wang Jingyi , Sun Jun , Xue Bai , Zhang Lijun 
Published: March 2021

AbstractWe propose a spurious region guided refinement approach for robustness verification of deep neural networks. Our method starts with applying the DeepPoly abstract domain to analyze the network. If the robustness property cannot be verified, the result is inconclusive. Due to the over-approximation, the computed region in the abstraction may be spurious in the sense that it does not contain any true counterexample. Our goal is to identify such spurious regions and use them to guide the abstraction refinement. The core idea is to make use of the obtained constraints of the abstraction to infer new bounds for the neurons. This is achieved by linear programming techniques. With the new bounds, we iteratively apply DeepPoly, aiming to eliminate spurious regions. We have implemented our approach in a prototypical tool DeepSRGR. Experimental results show that a large amount of regions can be identified as spurious, and as a result, the precision of DeepPoly can be significantly improved. As a side contribution, we show that our approach can be applied to verify quantitative robustness properties.
Resilient Capacity-Aware Routing
Authors: Schmid Stefan , Schnepf Nicolas , Srba Jiří 
Published: March 2021

AbstractTo ensure a high availability, communication networks provide resilient routing mechanisms that quickly change routes upon failures. However, a fundamental algorithmic question underlying such mechanisms is hardly understood: how to verify whether a given network reroutes flows alongfeasiblepaths, without violating capacity constraints, for up toklink failures? We chart the algorithmic complexity landscape of resilient routing under link failures, considering shortest path routing based on link weights as e.g. deployed in the ECMP protocol. We study two models: apessimisticmodel where flows interfere in a worst-case manner along equal-cost shortest paths, and anoptimisticmodel where flows are routed in a best-case manner, and we present a complete picture of the algorithmic complexities. We further propose a strategic search algorithm that checks only the critical failure scenarios while still providing correctness guarantees. Our experimental evaluation on a benchmark of Internet and datacenter topologies confirms an improved performance of our strategic search by several orders of magnitude.
Network Traffic Classification by Program Synthesis
Authors: Shi Lei , Li Yahui , Loo Boon Thau , Alur Rajeev 
Published: March 2021

AbstractWriting classification rules to identify interesting network traffic is a time-consuming and error-prone task. Learning-based classification systems automatically extract such rules from positive and negative traffic examples. However, due to limitations in the representation of network traffic and the learning strategy, these systems lack both expressiveness to cover a range of applications and interpretability in fully describing the traffic’s structure at the session layer. This paper presents Sharingan system, which uses program synthesis techniques to generate network classification programs at the session layer. Sharingan accepts raw network traces as inputs and reports potential patterns of the target traffic in NetQRE, a domain specific language designed for specifying session-layer quantitative properties. We develop a range of novel optimizations that reduce the synthesis time for large and complex tasks to a matter of minutes. Our experiments show that Sharingan is able to correctly identify patterns from a diverse set of network traces and generates explainable outputs, while achieving accuracy comparable to state-of-the-art learning-based systems.
FOREST: An Interactive Multi-tree Synthesizer for Regular Expressions
Authors: Ferreira Margarida , Terra-Neves Miguel , Ventura Miguel , Lynce Inês , Martins Ruben 
Published: March 2021

AbstractForm validators based on regular expressions are often used on digital forms to prevent users from inserting data in the wrong format. However, writing these validators can pose a challenge to some users.We presentForest, a regular expression synthesizer for digital form validations.Forestproduces a regular expression that matches the desired pattern for the input values and a set of conditions over capturing groups that ensure the validity of integer values in the input. Our synthesis procedure is based on enumerative search and uses a Satisfiability Modulo Theories (SMT) solver to explore and prune the search space. We propose a novel representation for regular expressions synthesis, multi-tree, which induces patterns in the examples and uses them to split the problem through a divide-and-conquer approach. We also present a new SMT encoding to synthesize capture conditions for a given regular expression. To increase confidence in the synthesized regular expression, we implement user interaction based on distinguishing inputs.We evaluatedForeston real-world form-validation instances using regular expressions. Experimental results show thatForestsuccessfully returns the desired regular expression in 70% of the instances and outperformsRegel, a state-of-the-art regular expression synthesizer.
Chancen der Digitalisierung – Transaktionskosten im traditionellen Geschäft senken, neue Interaktionen verstärken
Authors: Proff Harald , Ahrens Claudia , Neuroth Wencke , Proff Heike , Knobbe Florian , Szybisty Gregor , Sommer Stefan 
Published: March 2021

ZusammenfassungWir wollen in diesem Kapitel begründen, welche Chancen die Digitalisierung dem Management bietet:

Gemäß der Transaktionskostentheorie ermöglicht Digitalisierung eine Standardisierung von Schnittstellen und damit eine Verringerung von Interdependenzen entlang der Wertkette im traditionellen Geschäft und damit * eine Verringerung der (Transaktions-)Kosten

der internen Koordination durch bessere Standardisierung unternehmensinterner Schnittstellen, wodurch z. B. schneller mehr Varianten profitabel angeboten werden können,

der externen Koordination durch Standardisierung der Schnittstellen zu Lieferanten, wodurch eine Auslagerung von eigener Wertschöpfung auf kostengünstigere Lieferanten erleichtert wird sowie

der externen Koordination durch Standardisierung der Schnittstellen zu Kooperationspartnern, um durch gemeinsame Wertschöpfung Synergien zu erzielen und * dadurch auch eine Verringerung von Zielkonflikten zwischen Effizienz und Flexibilität, wodurch Handlungsspielräume für eine bessere Ausrichtung im Wettbewerb geschaffen werden.

Gemäß den Erklärungen der Interaktion ermöglicht Digitalisierung zudem eine bessere Zusammenarbeit mehrerer externer Akteure auf technischen Plattformen als Voraussetzung für innovative Kundenlösungen und Geschäftsmodelle in neuartigen Netzwerken (Ecosystems).

Damit schafft die Digitalisierung dem Management Handlungsspielräume und ermöglicht Gewinnpotenziale.
Nutzung der Chancen der Digitalisierung durch digitale Fähigkeiten – Unsicherheit bei langfristigen Veränderungen bewältigen
Authors: Proff Harald , Ahrens Claudia , Neuroth Wencke , Proff Heike , Knobbe Florian , Szybisty Gregor , Sommer Stefan 
Published: March 2021

ZusammenfassungWir wollen in diesem Kapitel zeigen, dass der Umgang mit der Digitalisierung Veränderungsfähigkeiten (Dynamic Capabilities) erfordert.

Diese Fähigkeiten helfen dabei, durch Verbesserung und Veränderung von Prozessen, Angeboten und Geschäftsmodellen (Kap. 10.1007/978-3-658-31456-9_3) die Chancen der Digitalisierung (Kap. 10.1007/978-3-658-31456-9_2) zu nutzen, weil sie es ermöglichen, die hohe Unsicherheit und Komplexität durch die Digitalisierung als langfristige Veränderung zu bewältigen.

Veränderungsfähigkeiten erlauben

die Wahrnehmung und das Erkennen von Umfeldveränderungen,

das Ergreifen neuer strategischer Optionen und

die Neu-Zusammenstellung von operativen Fähigkeiten (Operational Capabilities).

Veränderungsfähigkeiten – wie auch operative Fähigkeiten – sind für Unternehmen entscheidend, um im digitalen Wandel nicht zu spät zu kommen.Die Digitalisierung erfordert nicht nur eine Neuausrichtung der unternehmerischen Leistung (Kap. 10.1007/978-3-658-31456-9_3), sondern auch der digitalen Fähigkeiten und treibt auch darüber die Transformation von Unternehmen.
Die Chancen der Digitalisierung jetzt richtig nutzen – Ausblick
Authors: Proff Harald , Ahrens Claudia , Neuroth Wencke , Proff Heike , Knobbe Florian , Szybisty Gregor , Sommer Stefan 
Published: March 2021

ZusammenfassungKap. 7 fasst die Ergebnisse des Buches zusammen und zeigt die Bedeutung eines beidhändigen Managements in der digitalen Transformation.
Die Krise der darstellenden Künste und die Rolle der Kulturpolitik
Authors: Zimmer Annette , Mandel Birgit 
Published: March 2021

ZusammenfassungAus einer neoinstitutionellen Perspektive werden unterschiedliche Aspekte krisenhafter Entwicklungen in den darstellenden Künsten untersucht. Hierbei liegt der Fokus auf neuen Akteurskonstellationen und den sich daraus ergebenen Herausforderungen an kulturpolitische Prozesse, der Veränderungen der Leitungs- und Steuerungsstrukturen öffentlichgetragener Theater sowie der Infragestellung ihrer Legitimation. Die Beiträge eröffnen neue und komplexe Perspektiven auf veränderte Kontextbedingungen, Handlungsoptionen und Transformationsstrategien in den darstellenden Künsten.