In Volunteered Geographic Information (VGI) projects, the tagging or annotation of objects is usually performed in a flexible and non-constrained manner. Contributors to a VGI project are normally free to choose whatever tags they feel are appropriate to annotate or describe a particular geographic object or place. In OpenStreetMap (OSM), the Map Features part of the OSM Wiki serves as the de-facto rulebook or ontology for the annotation of features in OSM. Within Map Features, suggestions and guidance on what combinations of tags to use for certain geographic objects are outlined. In this paper, we consider these suggestions and recommendations and analyse the OSM database for 40 cities around the world to ascertain if contributors to OSM in these urban areas are using this guidance in their tagging practices. Overall, we find that compliance with the suggestions and guidance in Map Features is generally average or poor. This leads us to conclude that contributors in these areas do not always tag features with the same level of annotation. Our paper also confirms anecdotal evidence that OSM Map Features is less influential in how OSM contributors tag objects.

E-government open data platforms use metadata to provide an adequate environment for the consumption of data released on these platforms. Metadata enable the machine processing of information in a structured manner. Given that it reveals details and context about data, metadata allow interpretation in unique way and offer semantics for open government data. This paper presents an overview and analysis of four metadata models used in contemporary e-government open data platforms. We illustrate the strengths and limitations of these models through aspects and principles of open data defined in the paper by proposing metadata quality assessment model. Moreover, we examine how metadata structure is oriented toward the provision of valuable information assets needed for the utilization of open government data. Finally, we give an overview of available API support on the selected open data platforms for the provision and reuse of open data. The research results indicate that more attention should be paid to metadata to uncover relationships between datasets.

Transparency evaluation in open government is a process of measuring the extent of transparency against a predefined set of indicators. In this paper, we address the existing initiatives regarding data and government transparency evaluation as two separate indicators and present the analysis of their advantages and drawbacks. Based on that analysis, we extend a part of the OpenGovB benchmark related to transparency in open government. What is unique about this benchmark is that it utilizes metadata of data published on the open government data portals to calculate the majority of indicators related to data transparency indicators. For the government transparency indicator evaluation, the benchmark utilizes some of the well-known transparency indicators. The article shows concrete results obtained from the application of the defined transparency evaluation model on 22 open data portals, thus demonstrating the possibilities of its application as well as the gains regarding generated results. The proposed model bridges the gap between available methodologies for evaluating transparency based on collaboration and participation and methodologies for evaluating transparency based on open data.

Big data analytics (BDA) in healthcare has made a positive difference in the integration of Artificial Intelligence (AI) in advancements of analytical capabilities, while lowering the costs of medical care. The aim of this study is to improve the existing healthcare eSystem by implementing a Big Data Analytics (BDA) platform and to meet the requirements of the Czech Republic National Health Service (Tender-Id. VZ0036628, No. Z2017-035520). In addition to providing analytical capabilities on Linux platforms supporting current and near-future AI with machine-learning and data-mining algorithms, there is the need for ethical considerations mandating new ways to preserve privacy, all of which are preconditioned by the growing body of regulations and expectations. The presented BDA platform, has met all requirements (N > 100), including the healthcare industry-standard Transaction Processing Performance Council (TPC-H) decision support benchmark in compliance with the European Union (EU) and the Czech Republic legislations. Currently, the presented Proof of Concept (PoC) that has been upgraded to a production environment has unified isolated parts of Czech Republic healthcare over the past seven months. The reported PoC BDA platform, artefacts, and concepts are transferrable to healthcare systems in other countries interested in developing or upgrading their own national healthcare infrastructure in a cost-effective, secure, scalable and high-performance manner.