Durch ein verändertes Kundenverhalten wird die so genannte „Darkside of the Customer Journey“ immer umfangreicher und das Unternehmen verliert die Hoheit über den Vertriebsprozess. Diese Entwicklung kann nur durch den gezielten Einsatz digitaler Tools sowie einem exzellenten Market-Intelligence- System rückgängig gemacht werden.

Fluch oder Segen? Welche Entwicklungen sich mit der Digitalisierung durchsetzen werden, ist schwer vorhersehbar. Aber die digitalen Transformationsprozesse werden vor der Sozialwirtschaft nicht haltmachen. Daher sollte sie die Chancen nutzen und Veränderungen aktiv gestalten.

Blockchain-Technologie kann nicht auf den Märkten für die dezentrale Transaktionsabwicklung genutzt werden. Auch der Rückgriff als Gestaltungselement im politischen System wird diskutiert. Damit verbunden ist aber auch eine Ideologisierung politischer Prozesse.

Diskussionen über Blockchain kreisen oft um deren „disruptives Potenzial“ im Bereich der Transaktionsabwicklung etwa bei Kryptowährungen wie Bitcoin oder bei Smart Contracts. Jenseits dieser ökonomischen Belange könnte die Technologie jedoch auch die politischen und gesellschaftlichen Gegebenheiten auf den Kopf stellen – im Wege einer „Politischen Disruption“.

We use an application scenario that collects, transports and stores sensor data in a database. The data is gathered with a high frequency of 1000 datasets per second. In the context of this scenario, we analyze the performance of multiple popular database systems. The benchmark results include the load on the system writing the data and the system running the database.

In our previous work, we proposed a system which makes complex production machines more user-friendly by giving the recommendations to the operator. So, we assist the user working with a complex production machine. The recommen- dations are presented like: ”In the last 10 occurrences of this event the operators performed the following keystrokes”. While working on the project, we had problems with retrieving the correct recommendations from our knowledge base. Meanwhile, we gathered more data from our project partners. Now, we dive deeper into this data in order to improve our solutions. This work describes methods to preprocess the data. This preprocessing should help us building up the knowledge base. To achieve this automatically, we do not want to know much about the machine and the production process itself.

Critical Infrastructures (CIs) use Supervisory Control And Data Acquisition (SCADA) systems for remote control and monitoring. Sophisticated security measures are needed to address malicious intrusions, which are steadily increasing in number and variety due to the massive spread of connectivity and standardisation of open SCADA protocols. Traditional Intrusion Detection Systems (IDSs) cannot detect attacks that are not already present in their databases. Therefore, in this paper, we assess Machine Learning (ML) for intrusion detection in SCADA systems using a real data set collected from a gas pipeline system and provided by the Mississippi State University (MSU). The contribution of this paper is two-fold: 1) The evaluation of four techniques for missing data estimation and two techniques for data normalization, 2) The performances of Support Vector Machine (SVM), and Random Forest (RF) are assessed in terms of accuracy, precision, recall and F 1 score for intrusion detection. Two cases are differentiated: binary and categorical classifications. Our experiments reveal that RF detect intrusions effectively, with an F 1 score of respectively > 99%.

Welcome to the Human Factors in Hypertext 2018 workshop (HUMAN'18) in Baltimore, Maryland, USA, the first workshop of a new series of workshops for the ACM Conference on Hypertext and Social Media. It has a strong focus on hypertext users and thus complements the machine analytics research that we experienced in previous conferences. The user-centric view on hypertext not only includes user interfaces and interaction, but also discussions about hypertext application domains. Furthermore, the workshop raises the question of how original hypertext ideas (e.g., Doug Engelbart's "augmenting human intellect" or Frank Halasz' "hypertext as a medium for thinking and communication") can improve today's hypertext systems. Historically, hypertext research is strongly connected to human factors. Hypertext pioneers, such as Doug Engelbart or Ted Nelson, focused on the usage of and interaction with hypertext. This workshop combines original hypertext research ideas with recent hypertext research trends. In addition, it consolidates different hypertext research areas from the viewpoint of human factors. Thus, HUMAN'18 fosters cross-cutting discussions and the development of new ideas.

The idea to associate information with so-called links was developed by hypertext pioneers in the 1960s. In the 1990s the Dexter Hypertext Reference Model was developed with the goal to provide a general model for node-link hypertext systems. In the 1990s and 2000s there were important steps made for hypertext infrastructures, which led to component-based open hypermedia systems (CB-OHS). In this paper we provide a detailed description of node-link structures. We argue that Dexter does not match the need of CB-OHS, as it supports a mix of multiple structure domains. Based on the implementation of link support in our system Mother we demonstrate how Dexter needs to be tailored accordingly. We further describe Mother's ability of node-link structures to interoperate with other available structure services and vice versa.