To support the value assessment of technically feasible smart grid initiatives there exist several valuation methods. To determine whether those methods address all concerns relevant for smart grid valuation, we carry out a literature analysis aiming at (1) identifying existing valuation methods and the steps they propose, (2) identifying important valuation considerations, and (3) confronting these considerations with artifacts proposed by the existing valuation methods to identify open issues, requirements, and remaining challenges. Based on the conducted analysis we identify, among others, the following main deficiencies: (1) only a limited scope of concerns relevant to valuation is covered, particularly a systematic consideration of stakeholders goals, value exchange scenarios, and the IT infrastructure is lacking; and (2) a lack of instruments dedicated to fostering accessibility of valuation, in terms of establishing a shared understanding, communicating results, or actively involving different stakeholders in the process. Based on the findings, we suggest the application of conceptual modeling as an instrument to address the identified deficiencies. Therefore, we reflect on the role that current modeling approaches can play in smart grid valuation. This paper is a part of a larger project whose ultimate goal is to develop a model-based method for multi-perspective valuation of smart grid initiatives. The purpose of this paper is to establish a foundation for the realization of the envisioned method. The design of the model-based valuation method itself, its application and evaluation, are subjects of future work.

Digitalization of the energy grid, leading to a so-called smart grid, offers notable benefits to the electricity system itself, and creates economic, social, and environmental value for different parties. Nevertheless, there is still a lack of understanding the value proposition underlying a technically feasible smart grid initiative. In this paper we identify requirements towards an approach for understanding the value proposition of a smart grid initiative, and propose a first step towards such an approach in the form of a landscape of modeling languages complemented by a process model for valuation. We evaluate the proposed approach, among others, by applying it to a blockchain-based initiative in the energy sector.

Enterprises today face an increasing need to easily access and process knowledge they produce as well as automate their business processes. This need may be fulfilled by taking advantage of the Semantic Web and Semantic Web services technologies and implementing the concept of Semantic Business Process Management. In order to fulfil this vision, an enterprise and the specified part of the knowledge from the enterprisepsilas environment needs to be properly described. The main goal of this paper is to present Business Roles Ontology (BRO) and Business Functions Ontology (BFO) which are to provide description of business functions and corresponding business roles. Both ontologies may be used within automated business process management lifecycle and are the result of our research work.

The need for filtering of services results from the ever growing number of available Web services which offer similar functionalities. The filtering process is based not only on the functional aspects of services, but also on non-functional ones. One of the weaknesses of the filtering process is lack of high efficiency and its complexity as processing ontological descriptions and reasoning on them is extremely time-consuming. In order to speed-up the filtering process, clustering techniques that would narrow the set of potential services which meet user's preferences may be introduced. In this article the architecture for Semantic Web services filtering and clustering system is shortly discussed.