A Hybrid Framework for Automated and Adaptive E-Business Platforms

The automation of business transactions between corporations has been dominated by proprietary and inflexible EDI solutions for a long time. During the last years, novel XML-based standards emerged which have a wider scope than EDI but strongly differ with regard to granularity and industry-focus. Due to the abundance of many complex standards with limited diffusion among users and industries, especially small-and medium-sized enterprises (SMEs) have not yet managed to automate the execution of business transactions and to seamlessly interconnect their respective IT applications. In this work, we propose a novel approach which builds on a composite of existing standards and combines them towards a hybrid architecture facilitating electronic business transactions. The Web Service stack represents the technical foundation of this approach, while parts of the ebXML standard are leveraged to ensure a common understanding of business information and processes between trading partners. A central server acts as repository of formal agreements, common data and process modeling artifacts and allows for intermittent connectivity of the users. Decentral adapter components enable connecting heterogeneous legacy applications of the users to the central server. The resulting approach can thus be considered as hybrid regarding the degree of centralism involved and with respect to the combination of the Web services stack and the ebXML standard as an infrastructural foundation

Productivity gains of DevOps adoption: a case study

The main purpose of this research is to assess the productivity gains from the merge of two traditional IT teams: Development and Operations into a single DevOps team implementing 6 DevOps capabilities This research was conducted using the Case Study methodology, the author goes through the existing DevOps literature to better frame this research and the reader. To answer the formulated research question the author analyzed the team capacity planning divided by tasks type before and after a DevOps transition and interviewed 5 senior team members to collect their opinion about this transition. Observation was also part of this research and it was done by the author. The main objective is to analyze if there were productivity gains of that team after making the transition to a DevOps approach. The main contribution of this research is to analyze and extract results of the application of the DevOps capabilities in a real-world scenario where two teams are merged into a single DevOps team. As an example, we can observe that the operational work of the team decrease from 50% to 20%O objectivo principal desta pesquisa é aferir os ganhos de produtividade ao efetuar a fusão de duas equipas tradicionais de IT: Desenvolvimento e Operações numa única equipa DevOps implementando as 6 capacidades de DevOps. Esta pesquisa foi efetuada utilizado o método Caso de Estudo, o autor efetua uma revisão da literatura para melhor enquadrar esta pesquisa e o leitor. Para responder a pergunta enunciada nesta pesquisa o autor analisou o planeamento da capacidade da equipa dividido por tipo de tarefas antes e depois da fusão para DevOps, foram também efetuadas 5 entrevistas a membros seniores da equipa para recolher a sua opinião acerca desta transiçao para um modelo DevOps. E foi efetuada também a observação no terreno pelo autor do estudo. A maior contribuição desta pesquisa reside na extração dos resultados da aplicação das capacidades de DevOps num cenário real onde duas equipas foram fundidas numa só equipa DevOps. Como exemplo podemos observar a diminuição das tarefas operacionais das equipas decresceram de 50% para 20%

Data platforms for open life sciences-A systematic analysis of management instruments

Open data platforms are interfaces between data demand of and supply from their users. Yet, data platform providers frequently struggle to aggregate data to suit their users' needs and to establish a high intensity of data exchange in a collaborative environment. Here, using open life science data platforms as an example for a diverse data structure, we systematically categorize these platforms based on their technology intermediation and the range of domains they cover to derive general and specific success factors for their management instruments. Our qualitative content analysis is based on 39 in-depth interviews with experts employed by data platforms and external stakeholders. We thus complement peer initiatives which focus solely on data quality, by additionally highlighting the data platforms' role to enable data utilization for innovative output. Based on our analysis, we propose a clearly structured and detailed guideline for seven management instruments. This guideline helps to establish and operationalize data platforms and to best exploit the data provided. Our findings support further exploitation of the open innovation potential in the life sciences and beyond

Industrial Data Homogenization and Monitoring Scheme with Blockchain Oracles

Research efforts on Distributed Ledger Technologies (DLTs) for industrial applications have constantly been increasing over the last years. The use of DLTs in the Industry 4.0 paradigm provides traceability, integrity, and immutability of the generated industrial data. However, Industry 4.0 ecosystems are typically composed of multiple smart factory clusters belonging to several companies, which are immersed in constant interaction with other business partners, clients, or suppliers. In such complex ecosystems, multiple DLTs are necessarily employed to maintain the integrity of the data throughout the whole process, from when the data is generated until it is processed at higher levels. Moreover, industrial data is commonly heterogeneous, which causes compatibility issues, along with security and efficiency issues in the homogenization process. Thus, the data needs to be pre-processed and homogenized in a secure manner before being exploited. Consequently, in this work, we address the issues mentioned above by providing an industrial raw data pre-processing and homogenization process according to a standard data model. We employ decentralized blockchain oracles to guarantee the integrity of the external data during the homogenization process. Hereafter, we design an interoperable plant blockchain for trustworthy storage and processing of the resulting homogenized data across several industrial plants. We also present a prototype implementation of the aforementioned scheme and discuss its effectiveness. Finally, we design a monitoring scheme to overview the usage the performance of the architecture processes and identify possible performance and security issues.This work has been financed by the European Commission through the Horizon Europe program under the IDUNN project (grant agreement number 101021911). It was also partially supported by the Ayudas Cervera para Centros Tecnológicos grant of the Spanish Centre for the Development of Industrial Technology (CDTI) under the project EGIDA (CER-20191012), and by the Basque Country Government under the ELKARTEK program, project ELKARTEK program, project REMEDY - REal tiME control and embeddeD securitY (KK-2021/00091)

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history