Abstract
The main goal of the conference is to promote the interest in the current digital culture and its intersection with art and technology as an important research field, and also to create a common space for discussion and exchange of new experiences. It seeks to foster greater understanding about digital arts and culture across a wide spectrum of cultural, disciplinary, and professional practices. To this end, many scholars, teachers, researchers, artists, comput-er professionals, and others who are working within the broadly defined areas of digital arts, culture and education across the world, submitted their innovative work to the conference. © 2019 ACM.

Abstract
In the Mediterranean region, water scarcity has already prompted concern in the wine sector due to the strong impact it has on vineyard productivity and wine quality. Water footprint is an indicator that takes account of all the water involved in the creation of a product and may help producers to identify hotspots, and reduce water consumption and the corresponding production costs. In recent years several studies have been reported on wine water footprint determination, but mostly focused on the viticulture phase or assuming no grey water footprint at the winery since it has a treatment system. In the framework of the WineWaterFootprint project a medium-size winery was monitored, with direct measurements, regarding determination of the blue and grey components of water footprint. The determined winery water footprint ranged from 9.6 to 12.7 L of water per wine bottle of 0.75 L, the wastewater produced being responsible for about 98%, which means that the grey component cannot be disregarded. The developed scenarios show that a potential reduction of 87% in winery water footprint can be obtained with almost no investment. The challenge of reducing the grey footprint is not in technology development, but rather in the proper maintenance and monitoring of treatment systems.

Abstract
Disruptive requirements that currently drive the so-called Industry 4.0 (I4.0) are increasingly present in today's industries, where factories are forced to innovate in search of improvement in the quality of manufacturing of products aligned with the reductions of: manufacturing time, environmental and cost impacts with the manufacturing process. For this, an Information Systems (IS) architecture is proposed to reduce the negative impacts on an industrial operation caused by manual configuration failures in manufacturing systems, machines that are worn out in the production process and unstable integrations between industrial subsystems. The suggested SI model uses the Viable Systems Model adapted to Maintenance 4.0 technologies (Cyber-physical Systems (CPS), Manufacturing Execution Systems (MES), Data Mining and Digital Manufacturing concepts/technologies) with the goal to create an automatic purchase flow to replace parts by mitigating impending failures in industrial equipment through data mining and predictive analysis.

Abstract
In face of the continuously growing process of the fourth industrial revolution, the industries are forced to innovate their industrial manufacturing process to remain competitive and active in the market, perfecting the manufacturing process through new interconnected and autonomous technologies. Since time reduction, quality enhancement and cost reduction for manufacturing of industrial products are the major catalysts of a successful company for the current Era called Maintenance 4.0, this paper proposes to illustrate an Information Systems Architecture where, using the Viable Systems Model, it is possible to perform automatic adjustments in the subsystems related to Cyber-Physical Systems and Manufacturing Execution Systems (MES) within the Digital Manufacturing model and, in addition, to mitigate machine failures through predictive analyzes of massive volumes of data using algorithms with intelligent functions and Data Mining (DM) in order to automatically stabilize the entire system chain quickly and efficiently. © 2019 IEEE.

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