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Government institutions have released a large number of datasets on their open data portals, which are in line with the data transparency and open government initiatives. With the purpose of making it more accessible and visible, these portals categorize datasets based on different criteria like publishers, categories, formats, and descriptions. However, some of this information is often missing, making it impossible to find datasets in all of these ways. As a result, with the number of datasets growing further on the portals, it is getting harder to obtain the desired information. This paper addresses this issue by introducing EODClassifier framework that suggests the best match for the category where a dataset should belong to. It relies on formal concept analysis as a means to generate a data structure that will reveal shared conceptualization originating from tags' usage and utilize it as a knowledge base to categorize uncategorized open datasets.

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.

This paper describes the enhanced LIRE (LInked RElations) architecture for creating relations between datasets available on open government portals. The architecture is improved to be applicable on different open government data platforms using minimal configuration at the Data processing layer. We evaluated the applicability of enhanced LIRE, its advantages and disadvantages, which resulted in necessary recommendations for the publication of dataset?s metadata to obtain better associations between datasets. Moreover, we introduced a LINDAT indicator that reflects the percentage of linked data in the total possible number of linked data on open government data portals.

Openness and transparency initiatives are not only milestones of science progress but have also influenced various fields of organization and industry. Under this influence, varieties of government institutions worldwide have published a large number of datasets through open data portals. Government data covers diverse subjects and the scale of available data is growing every year. Published data is expected to be both accessible and discoverable. For these purposes, portals take advantage of metadata accompanying datasets. However, a part of metadata is often missing which decreases users’ ability to obtain the desired information. As the scale of published datasets grows, this problem increases. An approach we describe in this paper is focused towards decreasing this problem by implementing knowledge structures and algorithms capable of proposing the best match for the category where an uncategorized dataset should belong to. By doing so, our aim is twofold: enrich datasets metadata by suggesting an appropriate category and increase its visibility and discoverability. Our approach relies on information regarding open datasets provided by users — dataset description contained within dataset tags. Since dataset tags express low consistency due to their origin, in this paper we will present a method of optimizing their usage through means of semantic similarity measures based on natural language processing mechanisms. Optimization is performed in terms of reducing the number of distinct tag values used for dataset description. Once optimized, dataset tags are used to reveal shared conceptualization originating from their usage by means of Formal Concept Analysis. We will demonstrate the advantage of our proposal by comparing concept lattices generated using Formal Concept Analysis before and after the optimization process and use generated structure as a knowledge base to categorize uncategorized open datasets. Finally, we will present a categorization mechanism based on the generated knowledge base that takes advantage of semantic similarity measures to propose a category suitable for an uncategorized dataset.

This paper focuses on real-time monitoring of open data in the Western Balkan countries and assessment of dataset quality using five star methodology introduced by Berners-Lee. We have designed a framework and an application prototype that uses existing Application Programming Interfaces (API) of open data portals to collect information in real-time and conduct assessment on dataset quality for the Balkan countries. The obtained data has been evaluated and assessment results are visualized and presented in a dashboard. The results show that Balkan countries have 2.5/5 level on data quality on average.

Under influence of data transparency initiatives, a variety of institutions have published a significant number of datasets. In most cases, data publishers take advantage of open data portals (ODPs) for making their datasets publicly available. To improve the datasets' discoverability, open data portals (ODPs) group open datasets into categories using various criteria like publishers, institutions, formats, and descriptions. For these purposes, portals take advantage of metadata accompanying datasets. However, a part of metadata may be missing, or may be incomplete or redundant. Each of these situations makes it difficult for users to find appropriate datasets and obtain the desired information. As the number of available datasets grows, this problem becomes easy to notice. This paper is focused on the first step towards decreasing this problem by implementing knowledge structures to be used in situations where a part of datasets' metadata is missing. In particular, we focus on developing knowledge structures capable of suggesting the best match for the category where an uncategorized dataset should belong to. Our approach relies on dataset descriptions provided by users within dataset tags. We take advantage of a formal concept analysis to reveal the shared conceptualization originating from the tags' usage by developing a concept lattice per each category of open datasets. Since tags represent free text metadata entered by users, in this paper we will present a method of optimizing their usage through means of semantic similarity measures based on natural language processing mechanisms. Finally, we will demonstrate the advantage of our proposal by comparing concept lattices generated using formal the concept analysis before and after the optimization process. The main experimental research results will show that our approach is capable of reducing the number of nodes within a lattice more than 40%.

Connecting data that government releases in diverse domains, such as economy, statistics, environment, transportation, and medicine, as open data available on the web by using semantic web technologies, leads to linked open government data (LOGD). LOGD supports development of innovative, intelligent applications that improve openness and transparency and deliver a smart environment for smart living. With LOGD, any stakeholder can browse a data source and subsequently navigate to related data sources. In this paper, we present an overview of applied Semantic Web technologies in the open government data domain that increase openness and transparency of government, provide for effective data use and deliver smart services to everyone needing information. We will explain how Semantic Web technologies can contribute to a smart collaborative environment that promotes government data use and helps citizens obtain information they need.

This paper presents a benchmark proposal for the Open Government and its application from the open data perspective using data available on the U.S. government's open data portal (data.gov). The benchmark is developed over the adopted Open Government conceptual model, which describes Open Government through data openness, transparency, participation and collaboration. Resulting in two measures, that is, one known as the e-government openness index (eGovOI) and the other Maturity, the benchmark indicates the progress of government over time, the efficiency of recognizing and implementing new concepts and the willingness of the government to recognize and embrace innovative ideas.

Along teaching scientific research is second most important task for every university and faculty member. Research results are commonly published as journal papers, book chapters or as conference proceedings with the purpose to communicate the findings in academic circles, serve as promotion, or be used for tenure or reapplication. Maintaining the list of scientific references, can be a time consuming and tedious activity. To help along the process we have created a Web application named References that makes the process of editing and formatting the references partially automated and less time consuming. In this paper we present the architecture of the application, its functionalities and newly added feature that enables importing references both from structured and unstructured data.

This paper deals with representation of scientific references’ data and visual analysis of this data using web based scientific reference management software. The Reference application, is a web based reference management software, that enables easy administration and management of authors and scientific references. Similar web based reference management systems additionally support advanced tools for data visualization and exploration but the downside of this solutions is that they require installation of additional plugins due to the fact that visualization within the web browsers requires advanced graphics capabilities thus limiting the usability of these applications. The Reference application on the other hand introduces a solution for data visualization and exploration that relies on extensive usage of the latest HTML5 web standard featuring support for rich graphic intensive web applications hence forcing maximum usability and compatibility with the modern web browsers. This paper describes the visualization tool within Reference application, its implementation and functionalities.

This paper tracks the development of e-government towards the e-government 2.0 concept under the influence of WWW innovations and provides insight in how strategic goals of e-government 2.0 can be achieved in the Web 2.0 era. Although Western countries progress rapidly in achieving more open, participatory and transparent relations with users, by adoption of Web 2.0 technologies, less developed countries are slower to progress. This paper examines government websites in the developing countries of the Balkans for the presence of Web 2.0 applications and evaluates the results in comparison with more developed countries. It concludes with suggestions on how countries with e-government models prior to 2.0 can catch up and create an environment for citizen engagement and empowerment.

Linking open data in government domain, can lead to creation of new services and information as well as discovery of new ways to perform queries and get results in accessible, machine processable and structured manner. To reach the full potential of open government data more relations between data should be discovered. The interconnection of open government data and semantic description of their relations can bring new aspect of producing and consuming the data. In this paper we investigate issues for producing and utilizing open government data with special focus on dataset relations. We have proposed the Linked Relations (LIRE) architecture for relations creation between datasets and a basic RDF model of relation between two datasets. The architecture contains different modules that perform analysis of datasets attributes and suggest the type of relation between the datasets. It can be utilized by open data portals for creating relations between datasets belonging to different public agencies and government sectors. An idea presented in this paper is made available as CKAN plugin.

Nowadays web applications contain graphical elements which are often connected in a way that reflects relationship between them. Connections have different structure depending on needs of application. A common type of structure used to describe relationship between elements consists of four members, two of which are elements and two lines represent relationship between them. This paper presents an approach to eliminate commutative pairs in array of elements with mutually exclusive connections. The ECOMPAIR (Elimination of COMmutative PAIRs) algorithm allows using one line with associated descriptions to link two elements. Experimental results obtained from applying the ECOMPAIR algorithm on jsPlumb library for visualization show significant reduction on number of elements necessary for visualization.

Growing open data initiatives are offering different solutions for opening governmental data to the public. Open data platform solutions provide simple tools for enriching governmental portals with a data dimension. The new data-oriented shape of government inevitably imposes the need for the evaluation of government efficiency in light of open data. Regardless of the numerous initiatives, there is still no globally accepted open government evaluation framework. The purpose of the research presented in this chapter is to present and apply a model for assessing data openness, which relies on eight open data principles established by the Open Government Working Group. The model represents a new approach to the evaluation of open data with real-world application capabilities and is fully described throughout the chapter. As a confirmation of this model’s capabilities, we illustrate the results of its application on seven data portals along with analyses, comparisons, and conclusions regarding the results.

Attaining highly efficient e-Government in developing countries is a true challenge. These countries are struggling with many internal issues that are preventing them from providing budgetary resources for investing in ICT infrastructure, staff education, developing strategies, and enacting laws and policies. However, realizing the benefits that e-Government can bring, both to citizens and administration, these countries are working hard towards implementing e-Government and are achieving great results. As one of the developing countries, Serbia has been struggling for years with e-Government ideas. It started with humble implementations nearly ten years ago by publishing only a few informational services, but quickly made significant progress. The efforts made are worthy of recognition while experience gained is of considerable importance not only for Serbia’s further advances in this area but also for all other developing countries as an example and guidance to solving similar problems. This chapter provides an overview of the current state and history of e-Government development in Serbia and presents important issues and challenges influencing Serbian adoption of e-Government, which can be recognized in other developing countries as well. The chapter also addresses other issues and challenges that are now facing developed Governments, but which are on the way to developing nations as well. Even though these countries are not currently setting their focus on them, they should not be ignored nor neglected—indeed these should be included in developmental plans and strategies in order to successfully overcome them when the time comes.

Data mining in e-government is the process of translating data from government web site in useful knowledge that can provide various types of support in decision making. Data mining can be applied to any type of data, but we have chosen to use this technique on open government data. Open data is a new concept in the development of e-government. It stands for a public sector information which is available for distribution and usage without any restrictions. In this paper we will give an overview of a framework for open data mining and present an example of usage of this framework for data mining on government open data portals.

This paper presents extended GinisSense architecture applied for the prediction of electric power supply system behaviour. The original GinisSense architecture is a Sensor Web based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. This architecture was extended in order to process data from various IT systems present in power supply companies and sensors attached on power supply network elements. This allowed us to manage a large amount of data, both archived and real time, extract valuable information from raw data and perform rules based reasoning for the prediction of power supply system behaviour. The behaviour prediction process consists of four steps, defined according to Omnibus data fusion model. These steps lead to generation of events, where each event represents the possible future state of the power supply system indicating vulnerability of individual power supply network elements. By means of specialized Web GIS application, user is presented with the geographical area containing power supply network elements with the potential for the hazardous events. Within this paper, we demonstrate the architecture with a scenario generated in a laboratory conditions. For demonstration purposes, the necessary subset of data was transferred from the power supply company database to the laboratory conditions and the electrical values were collected from the local data warehouse during the simulation of hazardous events.

E-government, as a product of information technology, enables more efficient delivery of government services and contributes to better transparency and accountability of the government administration. One of the main tasks of government is to introduce a platform with high efficiency and good performance that will provide access to information of public interest. This paper presents the general architecture of the open government data platform with an overview of commonly used platforms in state and local governments around the world.

University and faculty members spend much of their time on scientific discovery and research. Scientific papers, as product of their extensive work, are used not only for their acknowledgement in academic circles, but also as a term of their promotion, tenure or reapplication. Most of the time, composing the list of references on published work turns into a long-lasting activity. Instead of manually editing and formatting the list, this process should be automated and less time consuming. In this paper we present a Web application for researchers and academics designed to help them manage and maintain references on published work.