To an increasing degree, data is a driving force for digitization, and hence also a key asset for numerous companies. In many businesses, various sources of data exist, which are isolated from one another in different domains, across a heterogeneous application landscape. Well-known centralized solution technologies, such as data warehouses and data lakes, exist to integrate data into one system, but they do not always scale well. Therefore, robust and decentralized ways to manage data can provide the companies with better value give companies a competitive edge over a single central repository. In this paper, we address why and when a monolithic data storage should be decentralized for improved scalability, and how to perform the decentralization. The paper is based on industrial experiences and the findings show empirically the potential of a distributed system as well as pinpoint the core pieces that are needed for its central management.

Situational awareness of maritime vessels in ice conditions is important for the operation of supply chains. In the artic sea areas, the ice conditions pose a major challenge for maritime vessels getting stuck in the ice and being significantly delayed in arrival to harbor. Data science and open data provide new opportunities to overcome these challenges. This paper introduces available open data sources and data visualizations that can be used to develop applications, for example, for detecting maritime vessel collision, predicting estimated time of arrival to harbor, as well as maritime vessel route optimization in ice conditions. The paper begins by introducing available open data sources and existing computational studies on maritime vessels in ice conditions, then presents the developed data science solution and visualizations of the open data along with the open source software code, and finally concludes with a discussion on the potential application areas and opportunities for further research.

Increasingly common open data and open application programming interfaces (APIs) together with the progress of data science -such as artificial intelligence (AI) and especially machine learning (ML) -create opportunities to build novel services by combining data from different sources. In this experience report, we describe our firsthand experiences on open data and in the domain of marine traffic in Finland and Sweden and identified technological opportunities for novel services. We enumerate five challenges that we have encountered with the application of open data: relevant data, historical data, licensing, runtime quality, and API evolution. These challenges affect both business model and technical implementation. We discuss how these challenges could be alleviated by better governance practices for provided open APIs and data.

Application Programming Interfaces (APIs) have become prevalent in today's software systems and services. APIs are basically a technical means to realize the co-operation between software systems or services. While there are several guidelines for API development, the actually applied practices and challenges are less clear. To better understand the state of the practice of API development and management in the industry, we conducted a descriptive case study in four Finnish software companies: two consultancy companies developing software for their customers, and two companies developing their software products. As a result, we identified five different usage scenarios for APIs and emphasize that diversity of usage should be taken into account more explicitly especially in research. API development and technical management are well supported by the existing tools and technologies especially available from the cloud technology. This leaves as the main challenge the selection of the right technology from the existing technology stack. Documentation and usability are practical issues to be considered and often less rigorously addressed. However, understanding what kind of API management model to apply for the business context appears as the major challenge. We also suggest considering APIs more clearly a separate concern in the product management with specific practices, such as API roadmapping.