004 Datenverarbeitung; Informatik
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Im Bachelor-Studiengang (B. Sc.) IT Security an der Fachhochschule St. Pölten wurde im Wintersemester 2011/12 versuchsweise die Lehrorganisation im ersten Fachsemester verändert: Die Module bzw. Teilmodule wurden nicht mehr alle parallel zueinander unterrichtet, sondern jedes Modul wurde exklusiv über einige Wochen abgehalten. Im Beitrag werden die Auswirkungen und bisherigen Erfahrungen mit dieser Reorganisation der Lehre geschildert: So haben sich die Noten im Mittel um etwa eine Note verbessert, die Zahl derjenigen Studierenden, die durch Prüfungen durchfallen, ist drastisch gesunken. Die Zufriedenheit der Studierenden und Lehrenden ist so groß, dass diese Form der Lehrorganisation im gesamten Bachelor- und auch im Masterstudiengang übernommen wird.
Eine übliche Erzählung verknüpft lange Studienzeiten und hohe Abbrecherquoten im Informatikstudium zum einen mit der sehr gut bezahlten Nebentätigkeit von Studierenden in der Informatikbranche, die deutlich studienzeitverlängernd sei; zum anderen werde wegen des hohen Bedarfs an Informatikern ein formeller Studienabschluss von den Studierenden häufig als entbehrlich betrachtet und eine Karriere in der Informatikbranche ohne abgeschlossenes Studium begonnen. In dieser Studie, durchgeführt an der Universität Potsdam, untersuchen wir, wie viele Informatikstudierende neben dem Studium innerhalb und außerhalb der Informatikbranche arbeiten, welche Erwartungen sie neben der Bezahlung damit verbinden und wie sich die Tätigkeit auf ihr Studium und ihre spätere berufliche Perspektive auswirkt. Aus aktuellem Anlass interessieren uns auch die Auswirkungen der Covid-19-Pandemie auf die Arbeitstätigkeiten der Informatikstudierenden.
“Broadcast your gender.”
(2022)
Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.
“Broadcast your gender.”
(2022)
Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.
‘Modern talking’
(2024)
Despite growing interest, we lack a clear understanding of how the arguably ambiguous phenomenon of agile is perceived in government practice. This study aims to alleviate this puzzle by investigating how managers and employees in German public sector organisations make sense of agile as a spreading management fashion in the form of narratives. This is important because narratives function as innovation carriers that ultimately influence the manifestations of the concept in organisations. Based on a multi-case study of 31 interviews and 24 responses to a qualitative online survey conducted in 2021 and 2022, we provide insights into what public sector managers, employees and consultants understand (and, more importantly, do not understand) as agile and how they weave it into their existing reality of bureaucratic organisations. We uncover three meta-narratives of agile government, which we label ‘renew’, ‘complement’ and ‘integrate’. In particular, the meta-narratives differ in their positioning of how agile interacts with the characteristics of bureaucratic organisations. Importantly, we also show that agile as a management fad serves as a projection surface for what actors want from a modern and digital organisation. Thus, the vocabulary of agile government within the narratives is inherently linked to other diffusing phenomena such as new work or digitalisation.
E-Learning-Anwendungen bieten Chancen für die gesetzlich vorgeschriebene Inklusion von Lernenden mit Beeinträchtigungen. Die gleichberechtigte Teilhabe von blinden Lernenden an Veranstaltungen in virtuellen Klassenzimmern ist jedoch durch den synchronen, multimedialen Charakter und den hohen Informationsumfang dieser Lösungen kaum möglich.
Die vorliegende Arbeit untersucht die Zugänglichkeit virtueller Klassenzimmer für blinde Nutzende, um eine möglichst gleichberechtigte Teilhabe an synchronen, kollaborativen Lernszenarien zu ermöglichen. Im Rahmen einer Produktanalyse werden dazu virtuelle Klassenzimmer auf ihre Zugänglichkeit und bestehende Barrieren untersucht und Richtlinien für die zugängliche Gestaltung von virtuellen Klassenzimmern definiert. Anschließend wird ein alternatives Benutzungskonzept zur Darstellung und Bedienung virtueller Klassenzimmer auf einem zweidimensionalen taktilen Braille-Display entwickelt, um eine möglichst gleichberechtigte Teilhabe blinder Lernender an synchronen Lehrveranstaltungen zu ermöglichen. Nach einer ersten Evaluation mit blinden Probanden erfolgt die prototypische Umsetzung des Benutzungskonzepts für ein Open-Source-Klassenzimmer. Die abschließende Evaluation der prototypischen Umsetzung zeigt die Verbesserung der Zugänglichkeit von virtuellen Klassenzimmern für blinde Lernende unter Verwendung eines taktilen Flächendisplays und bestätigt die Wirksamkeit der im Rahmen dieser Arbeit entwickelten Konzepte.
We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean propositions only. Our translation is modular and heavily benefits from the expressive input language of ASP. The resulting approach, along with its implementation, allows for solving interesting constraint satisfaction problems in ASP, showing a good performance.
The exponential expanding of the numbers of web sites and Internet users makes WWW the most important global information resource. From information publishing and electronic commerce to entertainment and social networking, the Web allows an inexpensive and efficient access to the services provided by individuals and institutions. The basic units for distributing these services are the web sites scattered throughout the world. However, the extreme fragility of web services and content, the high competence between similar services supplied by different sites, and the wide geographic distributions of the web users drive the urgent requirement from the web managers to track and understand the usage interest of their web customers. This thesis, "X-tracking the Usage Interest on Web Sites", aims to fulfill this requirement. "X" stands two meanings: one is that the usage interest differs from various web sites, and the other is that usage interest is depicted from multi aspects: internal and external, structural and conceptual, objective and subjective. "Tracking" shows that our concentration is on locating and measuring the differences and changes among usage patterns. This thesis presents the methodologies on discovering usage interest on three kinds of web sites: the public information portal site, e-learning site that provides kinds of streaming lectures and social site that supplies the public discussions on IT issues. On different sites, we concentrate on different issues related with mining usage interest. The educational information portal sites were the first implementation scenarios on discovering usage patterns and optimizing the organization of web services. In such cases, the usage patterns are modeled as frequent page sets, navigation paths, navigation structures or graphs. However, a necessary requirement is to rebuild the individual behaviors from usage history. We give a systematic study on how to rebuild individual behaviors. Besides, this thesis shows a new strategy on building content clusters based on pair browsing retrieved from usage logs. The difference between such clusters and the original web structure displays the distance between the destinations from usage side and the expectations from design side. Moreover, we study the problem on tracking the changes of usage patterns in their life cycles. The changes are described from internal side integrating conceptual and structure features, and from external side for the physical features; and described from local side measuring the difference between two time spans, and global side showing the change tendency along the life cycle. A platform, Web-Cares, is developed to discover the usage interest, to measure the difference between usage interest and site expectation and to track the changes of usage patterns. E-learning site provides the teaching materials such as slides, recorded lecture videos and exercise sheets. We focus on discovering the learning interest on streaming lectures, such as real medias, mp4 and flash clips. Compared to the information portal site, the usage on streaming lectures encapsulates the variables such as viewing time and actions during learning processes. The learning interest is discovered in the form of answering 6 questions, which covers finding the relations between pieces of lectures and the preference among different forms of lectures. We prefer on detecting the changes of learning interest on the same course from different semesters. The differences on the content and structure between two courses leverage the changes on the learning interest. We give an algorithm on measuring the difference on learning interest integrated with similarity comparison between courses. A search engine, TASK-Moniminer, is created to help the teacher query the learning interest on their streaming lectures on tele-TASK site. Social site acts as an online community attracting web users to discuss the common topics and share their interesting information. Compared to the public information portal site and e-learning web site, the rich interactions among users and web content bring the wider range of content quality, on the other hand, provide more possibilities to express and model usage interest. We propose a framework on finding and recommending high reputation articles in a social site. We observed that the reputation is classified into global and local categories; the quality of the articles having high reputation is related with the content features. Based on these observations, our framework is implemented firstly by finding the articles having global or local reputation, and secondly clustering articles based on their content relations, and then the articles are selected and recommended from each cluster based on their reputation ranks.
Diversity is a term that is broadly used and challenging for informatics research, development and education. Diversity concerns may relate to unequal participation, knowledge and methodology, curricula, institutional planning etc. For a lot of these areas, measures, guidelines and best practices on diversity awareness exist. A systemic, sustainable impact of diversity measures on informatics is still largely missing. In this paper I explore what working with diversity and gender concepts in informatics entails, what the main challenges are and provide thoughts for improvement. The paper includes definitions of diversity and intersectionality, reflections on the disciplinary basis of informatics and practical implications of integrating diversity in informatics research and development. In the final part, two concepts from the social sciences and the humanities, the notion of “third space”/hybridity and the notion of “feminist ethics of care”, serve as a lens to foster more sustainable ways of working with diversity in informatics.
Analyses of metagenomes in life sciences present new opportunities as well as challenges to the scientific community and call for advanced computational methods and workflows. The large amount of data collected from samples via next-generation sequencing (NGS) technologies render manual approaches to sequence comparison and annotation unsuitable. Rather, fast and efficient computational pipelines are needed to provide comprehensive statistics and summaries and enable the researcher to choose appropriate tools for more specific analyses. The workflow presented here builds upon previous pipelines designed for automated clustering and annotation of raw sequence reads obtained from next-generation sequencing technologies such as 454 and Illumina. Employing specialized algorithms, the sequence reads are processed at three different levels. First, raw reads are clustered at high similarity cutoff to yield clusters which can be exported as multifasta files for further analyses. Independently, open reading frames (ORFs) are predicted from raw reads and clustered at two strictness levels to yield sets of non-redundant sequences and ORF families. Furthermore, single ORFs are annotated by performing searches against the Pfam database
Die Lehre von wissenschaftlichem Arbeiten stellt einen zentralen Aspekt in forschungsorientierten Studiengängen wie der Informatik dar. Trotz diverser Angebote werden mittel- und langfristig Mängel in der
Arbeitsqualität von Studierenden sichtbar. Dieses Paper analysiert daher das Profil der Studierenden, deren Anwendung des wissenschaftlichen Arbeitens, und das Angebot von Proseminaren zum Thema „Einführung in das wissenschaftliche Arbeiten“ einer deutschen Universität. Die Ergebnisse mehrerer Erhebungen zeigen dabei diverse Probleme bei Studierenden auf, u. a. bei dem Prozessverständnis, dem Zeitmanagement und der Kommunikation.
Die vorliegende Arbeit befasst sich mit der wissensbasierten Modellierung von Audio-Signal-Klassifikatoren (ASK) für die Bioakustik. Sie behandelt ein interdisziplinäres Problem, das viele Facetten umfasst. Zu diesen gehören artspezifische bioakustische Fragen, mathematisch-algorithmische Details und Probleme der Repräsentation von Expertenwissen. Es wird eine universelle praktisch anwendbare Methode zur wissensbasierten Modellierung bioakustischer ASK dargestellt und evaluiert. Das Problem der Modellierung von ASK wird dabei durchgängig aus KDD-Perspektive (Knowledge Discovery in Databases) betrachtet. Der grundlegende Ansatz besteht darin, mit Hilfe von modifizierten KDD-Methoden und Data-Mining-Verfahren die Modellierung von ASK wesentlich zu erleichtern. Das etablierte KDD-Paradigma wird mit Hilfe eines detaillierten formalen Modells auf den Bereich der Modellierung von ASK übertragen. Neunzehn elementare KDD-Verfahren bilden die Grundlage eines umfassenden Systems zur wissensbasierten Modellierung von ASK. Methode und Algorithmen werden evaluiert, indem eine sehr umfangreiche Sammlung akustischer Signale des Großen Tümmlers mit ihrer Hilfe untersucht wird. Die Sammlung wurde speziell für diese Arbeit in Eilat (Israel) angefertigt. Insgesamt werden auf Grundlage dieses Audiomaterials vier empirische Einzelstudien durchgeführt: - Auf der Basis von oszillographischen und spektrographischen Darstellungen wird ein phänomenologisches Klassifikationssystem für die vielfältigen Laute des Großen Tümmlers dargestellt. - Mit Hilfe eines Korpus halbsynthetischer Audiodaten werden verschiedene grundlegende Verfahren zur Modellierung und Anwendung von ASK in Hinblick auf ihre Genauigkeit und Robustheit untersucht. - Mit einem speziell entwickelten Clustering-Verfahren werden mehrere Tausend natürliche Pfifflaute des Großen Tümmlers untersucht. Die Ergebnisse werden visualisiert und diskutiert. - Durch maschinelles mustererkennungsbasiertes akustisches Monitoring wird die Emissionsdynamik verschiedener Lauttypen im Verlaufe von vier Wochen untersucht. Etwa 2.5 Millionen Klicklaute werden im Anschluss auf ihre spektralen Charakteristika hin untersucht. Die beschriebene Methode und die dargestellten Algorithmen sind in vielfältiger Hinsicht erweiterbar, ohne dass an ihrer grundlegenden Architektur etwas geändert werden muss. Sie lassen sich leicht in dem gesamten Gebiet der Bioakustik einsetzen. Hiermit besitzen sie auch für angrenzende Disziplinen ein hohes Potential, denn exaktes Wissen über die akustischen Kommunikations- und Sonarsysteme der Tiere wird in der theoretischen Biologie, in den Kognitionswissenschaften, aber auch im praktischen Naturschutz, in Zukunft eine wichtige Rolle spielen.
"Wir gehen multimedial. Kommt ihr mit?" war Aufruf und Leitmotiv der MultimeDies 2007. Es kamen sehr viele mit, vor allem Lehrende und Lernende der Universität Potsdam, aber auch Firmen. Diese Veranstaltung setzt eine Tradition fort, die im Bemühen steht über zukunftsweisende Technologien und Projekte, über Angebote und praktikable Lösungen an der Universität zu informieren. Die Vorträge wurden in kurzen Beiträgen zusammengestellt. Sie gliedern sich in zwei Gruppen, zum einen der Bereitstellung, zum anderen der Nutzung von Multimedia.
Knowledge-intensive business processes are flexible and data-driven. Therefore, traditional process modeling languages do not meet their requirements: These languages focus on highly structured processes in which data plays a minor role. As a result, process-oriented information systems fail to assist knowledge workers on executing their processes. We propose a novel case management approach that combines flexible activity-centric processes with data models, and we provide a joint semantics using colored Petri nets. The approach is suited to model, verify, and enact knowledge-intensive processes and can aid the development of information systems that support knowledge work.
Knowledge-intensive processes are human-centered, multi-variant, and data-driven. Typical domains include healthcare, insurances, and law. The processes cannot be fully modeled, since the underlying knowledge is too vast and changes too quickly. Thus, models for knowledge-intensive processes are necessarily underspecified. In fact, a case emerges gradually as knowledge workers make informed decisions. Knowledge work imposes special requirements on modeling and managing respective processes. They include flexibility during design and execution, ad-hoc adaption to unforeseen situations, and the integration of behavior and data. However, the predominantly used process modeling languages (e.g., BPMN) are unsuited for this task.
Therefore, novel modeling languages have been proposed. Many of them focus on activities' data requirements and declarative constraints rather than imperative control flow. Fragment-Based Case Management, for example, combines activity-centric imperative process fragments with declarative data requirements. At runtime, fragments can be combined dynamically, and new ones can be added. Yet, no integrated semantics for flexible activity-centric process models and data models exists.
In this thesis, Wickr, a novel case modeling approach extending fragment-based Case Management, is presented. It supports batch processing of data, sharing data among cases, and a full-fledged data model with associations and multiplicity constraints. We develop a translational semantics for Wickr targeting (colored) Petri nets. The semantics assert that a case adheres to the constraints in both the process fragments and the data models. Among other things, multiplicity constraints must not be violated. Furthermore, the semantics are extended to multiple cases that operate on shared data. Wickr shows that the data structure may reflect process behavior and vice versa. Based on its semantics, prototypes for executing and verifying case models showcase the feasibility of Wickr. Its applicability to knowledge-intensive and to data-centric processes is evaluated using well-known requirements from related work.
In this article, we propose a model for an understanding process that learners can use while studying programming. We focus on the “small step” method, in which students learn only a few concepts for one program to avoid having trouble with learning programming. We also analyze the difference in the description order between several C programming textbooks on the basis of the model. We developed a tool to detect “gaps” (a lot of concepts to be learned in a program) in programming textbooks.
Clustering in education is important in identifying groups of objects in order to find linked patterns of correlations in educational datasets. As such, MOOCs provide a rich source of educational datasets which enable a wide selection of options to carry out clustering and an opportunity for cohort analyses. In this experience paper, five research studies on clustering in MOOCs are reviewed, drawing out several reasonings, methods, and students’ clusters that reflect certain kinds of learning behaviours. The collection of the varied clusters shows that each study identifies and defines clusters according to distinctive engagement patterns. Implications and a summary are provided at the end of the paper.
First come, first served: Critical choices between alternative actions are often made based on events external to an organization, and reacting promptly to their occurrence can be a major advantage over the competition. In Business Process Management (BPM), such deferred choices can be expressed in process models, and they are an important aspect of process engines. Blockchain-based process execution approaches are no exception to this, but are severely limited by the inherent properties of the platform: The isolated environment prevents direct access to external entities and data, and the non-continual runtime based entirely on atomic transactions impedes the monitoring and detection of events. In this paper we provide an in-depth examination of the semantics of deferred choice, and transfer them to environments such as the blockchain. We introduce and compare several oracle architectures able to satisfy certain requirements, and show that they can be implemented using state-of-the-art blockchain technology.
Which event happened first?
(2021)
First come, first served: Critical choices between alternative actions are often made based on events external to an organization, and reacting promptly to their occurrence can be a major advantage over the competition. In Business Process Management (BPM), such deferred choices can be expressed in process models, and they are an important aspect of process engines. Blockchain-based process execution approaches are no exception to this, but are severely limited by the inherent properties of the platform: The isolated environment prevents direct access to external entities and data, and the non-continual runtime based entirely on atomic transactions impedes the monitoring and detection of events. In this paper we provide an in-depth examination of the semantics of deferred choice, and transfer them to environments such as the blockchain. We introduce and compare several oracle architectures able to satisfy certain requirements, and show that they can be implemented using state-of-the-art blockchain technology.
A survey has been carried out in the Computer Science (CS) department at the University of Baghdad to investigate the attitudes of CS students in a female dominant environment, showing the differences between male and female students in different academic years. We also compare the attitudes of the freshman students of two different cultures (University of Baghdad, Iraq, and the University of Potsdam).
The term Linked Data refers to connected information sources comprising structured data about a wide range of topics and for a multitude of applications. In recent years, the conceptional and technical foundations of Linked Data have been formalized and refined. To this end, well-known technologies have been established, such as the Resource Description Framework (RDF) as a Linked Data model or the SPARQL Protocol and RDF Query Language (SPARQL) for retrieving this information. Whereas most research has been conducted in the area of generating and publishing Linked Data, this thesis presents novel approaches for improved management. In particular, we illustrate new methods for analyzing and processing SPARQL queries. Here, we present two algorithms suitable for identifying structural relationships between these queries. Both algorithms are applied to a large number of real-world requests to evaluate the performance of the approaches and the quality of their results. Based on this, we introduce different strategies enabling optimized access of Linked Data sources. We demonstrate how the presented approach facilitates effective utilization of SPARQL endpoints by prefetching results relevant for multiple subsequent requests. Furthermore, we contribute a set of metrics for determining technical characteristics of such knowledge bases. To this end, we devise practical heuristics and validate them through thorough analysis of real-world data sources. We discuss the findings and evaluate their impact on utilizing the endpoints. Moreover, we detail the adoption of a scalable infrastructure for improving Linked Data discovery and consumption. As we outline in an exemplary use case, this platform is eligible both for processing and provisioning the corresponding information.