Open data portals are web services that serve as a central access point for all government-published open data and can exist at local, regional, national, and international levels. They are an important element of most open data initiatives that have enabled a large amount of government data to be widely available. However, data quantity and quality are not the only aspects that should be considered when publishing data. To improve the reusability of data and to achieve greater impact and benefits from open data, it is important to consider user-oriented aspects of the portal management, discovery, and use of data (e.g., organizing the portal in a user-centric way, providing accurate metadata, using a standardized and open data format, etc.). In this paper, we adopted the metrics proposed by the European Commission to assess compliance of the Croatian Open Data Portal with 10 user-oriented principles that open data portals should implement in terms of sustainability and added value. While the results show the government’s efforts in publishing data, some aspects such as better collaboration with data providers and other data portals, offering different visualization tools, etc. need to be improved to achieve active use and impact.@en

The 2019 European Open Data Directive identifies geospatial data as data that could have a major impact on human activities (high-value data, HVD) and advocates its provision as open data (OD), i.e., without barriers to access and re-use. Although Croatia has implemented OD policies to support the provision of open data, many geospatial data are still not available, or if available, their level of openness ranks Croatia lower than Slovenia and Serbia on some ranking lists. Benchmarking tools have proven to be a powerful tool in identifying barriers in OD. This paper, therefore, benchmarks the level of openness and provision of geospatial HVD in Croatia, Slovenia and Serbia, using the extended and modified Global Open Data Index methodology (GODI Plus). It is expected that this will provide an answer to the status of OD policies and government engagement in OD in Croatia and identify good OD practices among the three countries analyzed. Furthermore, the results will be a baseline benchmark for future HVD analyses. The results reveal low data openness for Croatia and Serbia, high data openness for Slovenia, and a low level of government engagement in all three proposed countries.

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As part of the Twinning Open Data Operational (TODO) Project, a series of virtual and physical site visits were organized in 2021 and 2022 as part of the Capacity Building Work Package. The goal of the site visits was to increase the knowledge of the TODO Consortium partners and to expand their understanding of the real-life implementation of open data policies, technologies, and initiatives in different domains. The institutions that participated in the site visits are considered to be among open data best practices in Europe. These organizations included public organizations at different administrative levels (EU, national, regional, local), businesses, research institutions and non-profit organizations. The aim of the site visits was to gain insight in policies and day-to -day practices of open data organizations and in the main challenges they are facing. This paper describes the outcomes of these site visits, and which open data developments, challenges and opportunities are currently going on for open data organisations. @en

The new concept of Open Spatial Data Infrastructures (Open SDIs) has emerged from an increased interest in open data initiatives together with national and international directives, such as the EU Open Data Directive (Directive (EU) 2019/1024), and the large investment of European public authorities in developing SDIs for sharing spatial data within public authorities. Open SDIs have the potential to boost reaching SDIs’ general aims and goals of facilitating the exchange and sharing of spatial data to support planning and decision-making by including public participation and increased openness in all aspects of SDIs, including Open SDI Education. The open SPatial data Infrastructure eDucation nEtwoRk (SPIDER) project aims to address Open SDI Education by particular emphasis on studying Active Learning and Teaching (ALT) methods for SDI education. This article provides a theoretical basis of ALT for SDI methodologies. We show in which way ALT practices were already implemented in SDI education at the Partner universities before the COVID-19 pandemic. We also describe how the pandemic functioned as a catalyst for implementing ALT practices to an online environment, and how students evaluated these practices. The outcomes of our research can serve as an inspiration for SDI education in other countries.@en

Dogs and dog owners are increasingly present in modern urban spaces, and the construction and maintenance of urban infrastructure that includes places for them has become standard in most major cities. We wanted to investigate the extent to which the City of Zagreb is adhering to open data principles when it comes to dog-related data it makes available to citizens.The openness and quality of dog-related data was analysed in three steps. First, dog-related data was searched on various official websites and portals of the city and the data formats were ranked according to the five-star system for open data. In the second step, based on the available data, a field survey was conducted in 2020 to verify the found datasets and geocode them using a GPS device. In addition, the locations obtained from the local community of dog owners through social media were reviewed. Finally, data obtained from the survey was cross-checked with the government data to assess their quality. Government data on the locations of 300 dog waste bins and 72 green areas where dogs can be walked off-leash were available in Croatian from one or more government sources. All data sets found received the lowest score in terms of open data formats. Field survey revealed differences between the data and reality. The location of 40 dog waste bins could not be confirmed, and additional 53 bins were found that were not mentioned in the data. As for green areas, there were reportedly 10 dog parks in the city of Zagreb. The survey confirmed all locations and discovered 12 more, five of which were mentioned in the data but not designated as dog parks. The results suggest that the municipality needs to update the already open datasets more frequently. Improved implementation of these datasets into existing city data portals or the creation of a separate hub for dog owners would greatly improve the availability and reuse of this data by citizens.@en

There is an increasing need for spatial data to be used for informed decision-making and as a resource for developing innovative products and services. A Spatial Data Infrastructure (SDI) facilitates access to and sharing of spatial data by providing a framework in which technical and non-technical aspects are established. Traditionally, SDIs are developed by and for government organisations to share spatial information within government. Non-government parties may also use SDIs to access government spatial data, either as open data or as fee-based data. There are also non-government SDIs, such as company SDIs used to share spatial information within a private sector organisation. OpenStreetMap is another example of a non-government SDI, whereby citizens have created a worldwide map based on crowd-sourced information and contributions from private and public sector organisations. The concept of Open SDIs has emerged from an increased interest in open data initiatives steered by national and international directives, such as the EU Open Data Directive (Directive (EU) 2019/1024), as well as the large investment of European public authorities in developing SDIs. Open SDIs are SDIs in which citizens, research institutions, private organizations and other businesses and non-governmental actors are recognized as key stakeholders of the infrastructure (Vancauwenberghe and van Loenen, 2018; Vancauwenberghe et al., 2018). The concept of Open SDIs is about openness to new stakeholders in the open data ecosystem, in which stakeholders can be both producers and users of spatial data. Open SDIs are also linked to developments and trends in other domains, such as open government, open data, open science, and open software. This new paradigm regarding Open SDIs means that new particular skills are required, which currently are not offered by traditional SDI education@en

As we advance technologically, spatial data gains importance with its ability to be used in various fields. Traditionally, most spatial data are collected by government organisations. To facilitate sharing and reuse of spatial data, Spatial Data Infrastructures (SDIs) have been developed in the last decades. More recently with the growing maturity of open data, the notion emerged that not only government organisations should be involved in SDIs but also companies and citizens should be included to upload and share their data in an Open SDI. One of the Open SDI challenges is how to engage and continuously motivate non-governmental parties to participate as an open data community. This research used OpenStreetMap (OSM) as a case study to explore the factors that foster user participation in an Open SDI community, as we consider OSM to be a non-governmental Open SDI ecosystem. Using a qualitative and a quantitative approach, we found that participants that were mostly heavy contributors are highly motivated to participate mostly because they believe in the main goal of OSM, they value the community and the development of the OSM platform and trust the system and its users. Moreover, they also participate for fun, instrumentality, altruism, meeting own needs, and for learning. Although OSM participants perceive OSM as an Open Data Ecosystem, there are dividing opinions of the perception of Open Spatial Data Infrastructures. The participants’ concerns and recommendations for future development of OSM can be used by government organisations in the development of Open SDIs.@en

Over the last decade, open data has become a hot topic that researchers and governments all over the world are eager to explore. The term first appeared in a 1995 document from an American scientific agency (Chignard, 2013), but its popularity increased when the U.S. president, Barrack Obama, signed the 2009 Memorandum on Transparency and Open Government, pledging to achieve an unprecedented level of openness in government (Obama, 2009). This memorandum emphasized the importance of creating a system of transparency, public participation, and collaboration through openness.@en

This research aims to assess available spatial open data related to access to hospitals in the three largest Croatian cities (Zagreb, Split, Rijeka), with a future aim to create digital services as an ecosystem that will be used in everyday situations, as part of the concept of “digital society”. Data analysis is performed for the following datasets: hospitals, hospital specialization, public transport (tram, bus), bike routes, car routes, parking and parking for people with disabilities. The future aim is to create a new mobile, multilingual and voice-based application that would enable quick access to information on hospital access, relying on the principles of the open data ecosystem, which would improve over time. There are four specific aims: (1) to identify and analyze portals and open datasets of the selected categories for the three largest Croatian cities; (2) to analyze existing open data assessment frameworks and detect gaps; (3) to create a conceptual open data assessment framework as an open data ecosystem that integrates new end-user perspectives; and (4) to analyze existing open datasets for the three largest cities in Croatia, based on supply and demand by researcher/developer categories, using the newly developed framework. The results show that existing open datasets related to hospital access in the three largest Croatian cities are scattered across different portals. Analyzed frameworks existing on the supply side of open data are more focused on the status of the components, lacking evaluation scales and not including end-user-driven aspects, which would be crucial for the open data ecosystem. As a result, the new “Hospital Access Framework” is created as a conceptual ecosystem, including five categories: supply, demand by researcher/developer, demand by end-user, legal aspect and impact. Analysis of existing open data for the three Croatian cities is performed for two categories (supply and demand by researcher/developer), for which KPIs, indicators and evaluation scales are developed. The other three categories are not analyzed, since the application cannot be developed from existing data, which are insufficient for the creation of a smart application. Results show that existing open data related to hospital access are incomplete or do not exist at all (hospital specialization, parking for people with disabilities, data on multilingualism and voice enabling). Average scores of the supply category are higher than those for demand by researcher/developer, although they are below the average grade, showing a lack of available data that could be used for further development. The new conceptual “Hospital Access Framework” open data ecosystem would benefit from end-user interaction, therefore, improving over time with end-users through interaction.@en

High quality data of botanical records, spatially and otherwise, can provide valuable information to researchers and government stakeholders in decision-making processes regarding species and habitat protection and sustainable use. Two plant databases were used as a source of records for assessment of spatial quality: Flora Croatica database (FCD) and Croatian Plant Genetic Resources Database (CPGRD). As the most extensive botanical database in Croatia, FCD comprises of herbarium collections, literature, and fieldwork observations aimed at nature protection, science, and educational use. CPGRD provides data on collection for conservation of national plant genetic resources in agricultural plant production and use. Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.) as an endemic and protected species with cultivation potential is an example of overlap in these two open databases. Records of Dalmatian pyrethrum were scored based on three categories of indicators: completeness, logical consistency, and positional accuracy. In total, 1042 records were identified (FCD: 901, CPGRD: 141) with 47 records found in both databases. Preliminary results indicate a high quality of Dalmatian pyrethrum spatial records scoring high on all three categories (completeness: 95.59%, logical consistency: 93.38% and positional accuracy: 95.78%). These findings open a possibility for linking the data from two different sectors while promoting constant quality improvements. @en

The assessment of the performance of open data ecosystems has gained significant interest of researchers worldwide (see Welle Donker & Van Loenen, 2016; Dodds and Newman, 2015; Capgemini Consulting, 2015; Public Sector Information (PSI) Scoreboard; Independent Reporting Mechanism (IRM), 2015; World Wide Web Foundation, 2015; Open Knowledge International (OKI), 2014). These existing assessment methods focus on the status of the components of an ecosystem (is there an open data policy, does the data comply with open standards, is it available free of charge, etc). By applying an application/ user needs driven approach, this project implements a different assessment approach: open data as a means to assess (physical) access to hospital buildings. The extent to which such a simple but important societal question can be answered is regarded as a measure for the maturity of the open data ecosystem of a jurisdiction. We used the basic indicators for assessing the performance of an open data ecosystem, and complemented these with the result of the assessment of hospital accessibility. The results will provide insight in how the open data ecosystem is able to answer such a simple question and which steps have to be taken to improve the ecosystem. Adding such an user question driven approach to the portfolio of open data ecosystem assessment framework would be extremely beneficial for decision makers in specific domains to set priorities for releasing data as open data. The focus of the research is to detect available data sets in order to assess access to hospitals in three Croatian towns (Zagreb, Rijeka, Split). The research is based on existing open data, found on web portals, containing information on hospitals, emergency service, coronavirus screening clinics, public transport and stations (bus lines, tramways, bike routes), roads and car parking. Research method includes qualitative research on publicly available datasets. Methodology includes identification of portals, search for datasets, acquisition, data inspection, qualitative and quantitative analysis based on created model and reporting. The created framework entitled “Hospital Access Framework” consists of five domains: Supply side, Demand side (open data user skills), Demand side (end-user capabilities), Legal aspects and privacy, Impact. For each domain, several KPIs (Key Performance Indicators) are suggested, using SMART (Specific Measurable Achievable Relevant Time-bound) criteria. Qualitative analysis is performed on suggest eco-system framework, created for this research, while quantitative analysis includes Yes/Partly/No answers of suggested KPIs. Existing data sets are incomplete, missing, not in formats available for download, or generally, not of the sufficient quality and quantity. The aim was to interrelate data for several Croatian towns in order to assess access to hospitals by public and private transport and parking places. Although the suggested framework “Hospital Access Framework” is created as an ecosystem framework, it is not fully implemented. The framework is used at this stage only for assessment of (non)existence of available datasets needed to assess access to hospitals. The future challenge would be to create an online app as an eco-system, which would be updated through adding new data from interaction with users and by improving data quality and data quantity and to apply the framework “Hospital Access Framework” in its full potential.@en

This report looks at different methods of active teaching and learning and the application of these methods at the partner universities of the SPIDER project. Different methods of on-campus and online teaching are presented and reports on experiences in their application at the partner universities are discussed. In combination with the results from Intellectual Output (IO) 4, this results in best practices for Open SDI Education. @en

This report presents showcases of active teaching and learning in spatial data infrastructure education in the SPIDER partner universities. It includes detailed descriptions of the practices that have been implemented, as well as the results of the evaluation of the practices from an active teaching learning perspective.@en

In this 2 hour workshop the experiences of the geographic data domain will be shared with the open data research & education community to promote and strengthen active innovative learning and teaching in both worlds. The domain of geographic data can be considered as one of the front running in open data. Over the past two decades, many geographic datasets in Europe became available as open data through the open [spatial] data infrastructure. Several of the high value dataset categories in the EU Directive on Open data and reuse of Public Sector Information have a geographic component. Teachers in this domain are struggling with the concepts of data ecosystems and data infrastructures presented in the academic literature. A very current Vancauwenberghe et al. 2018), in which also nongovernment data and nongovernment actors should be considered as key to the performance of the infrastructure and/or ecosystem. Moreover, teaching methods are still limited to traditional teaching in the classroom. As a consequence, there is barely an international exchange of educational material and approaches on open SDI among universities. In this workshop an overview and detailed analysis of the concepts of open data ecosystems and infrastructures are presented and discussed and existing open data education highlighting good practices of learning, teaching and training in open [spatial] data infrastructures or ecosystems explored.@en

Open data initiatives have resulted in greater availability of data, thereby realising ambitions such as improved efficiency and effectiveness of public services, increased transparency, accountability and citizen participation, and economic and social value creation. Open data research is a crucial component in creating and accelerating sustainable and innovative open data ecosystems. However, not all countries equally progress with regard to implementing open data policies and some countries are falling behind. The project Twinning Open Data Operational (TODO) examines which strategy can boost the open data ecosystem of countries that are just beginning to develop open data policies. We are developing and implementing an interdisciplinary multi-domain open data research approach to increase the maturity of the concept and impact of the open data ecosystem in Croatia and beyond. This paper lays down the strategy to arrive at a sustainable open data research ecosystem in open data beginners countries.@en

Het Ministerie van Binnenlandse Zaken en Koninkrijksrelaties (BZK) investeert veel in het verbeteren van de ontsluiting van open data. Met de NL DIGITAAL Data Agenda Overheid laat het ministerie van BZK ook zien dat er een duidelijke ambitie is om de burgers en ondernemers centraal te stellen en te komen tot gebruiker gedreven overheidsdata. Een van de actiepunten uit NL DIGITAAL is het bevorderen van hergebruik van open overheidsdata. Om daar stappen in te kunnen zetten, is het van belang om beter inzicht te krijgen in de vraag wie de hergebruikers van open data zijn, en wat hun behoeften zijn. Dat inzicht ontbreekt het Ministerie van BZK op dit moment. Er zijn voldoende aanwijzingen dat open data gebruikt worden, zeker als men kijkt naar het aantal bezoekers van open data portalen. Echter aantallen bezoekers zeggen op zich niet zoveel over het hergebruik zelf. Bekijken de bezoekers alleen naar een dataset, wordt de dataset gedownload dan wel via een Application Programming Interface (API) aangeroepen? Komen gebruikers uit het bedrijfsleven of uit de publieke sector en waarvoor gebruiken zij welke open data en via welke wegen? En wat zijn hun behoeften dan wel problemen waar zij tegen aan lopen? In dit geven wij antwoord op de volgende vier vragen: 1. Wie zijn open data hergebruikers? 2. Op welke manier(en) gebruiken hergebruikers open data? 3. Waar lopen hergebruikers tegenaan bij het gebruiken van open data? 4. Wat zijn de behoeften van de hergebruikers? Voor dit onderzoek is gebruik gemaakt van verschillende onderzoeksmethoden. Een kwantitatieve analyse is uitgevoerd op basis van de IP-Adressen in de logfile gegevens voor het open data portaal van CBS (statistische data), PDOK (geodata), en data.overheid.nl. Deze kwalitatieve analyse geeft antwoord op de vraag welke typen hergebruikers open data gebruiken en in welke categorieën zij kunnen worden onderverdeeld; welke datasets het meest worden gebruikt en welke kruisverbanden kunnen worden gelegd; op welke manier hergebruikers zich toegang tot de data verschaffen, en via welke weg (centraal dataplatform of individuele organisaties). Ook hebben wij technieken ingezet om inzicht te geven in welke websites melding gemaakt wordt van het gebruik van open data. Ten slotte hebben wij een kwantitatieve analyse gemaakt van Twitterberichten tussen 2010 en 2018 met betrekking tot open data. Daarnaast is er een kwalitatieve analyse uitgevoerd op basis van een online enquête, een workshop met wetenschappelijke medewerkers, diepte-interviews met open data hergebruikers en een online prioritering van de grootste belemmeringen en behoeften door de geïnterviewde hergebruikers. Deze kwalitatieve analyse verifieert de kwantitatieve analyse en geeft inzicht in voor welke doelen open data worden gebruikt, eventuele knelpunten en behoeften van de verschillende categorieën hergebruiker. En vooral welke aanbevelingen zij hebben voor het Ministerie van BZK om het aanbod van open data te verbeteren.@en

Het doel van de verkenning is het uitbouwen en verspreiding van kennis over het gebruik van ‘sociale’ locatiegegevens door de overheid. Tijdens de verkenning wordt inzicht gegeven in de rol die locatiedata van sociale media en aan sociale media gerelateerde applicaties spelen bij de wederzijdse communicatie tussen de overheid en de burger. Door middel van interviews met veertien organisaties is een indruk verkregen van de stand van social media (locatie) gegevens gebruik bij de overheid. Sociale media data worden op veel plekken in meer of mindere mate gebruikt door overheden maar het gebruik is de projectfase nog niet ontgroeid: het gebruik beperkt zich tot reactieve communicatie en eenvoudige omgevingsanalyses, en maakt geen onderdeel uit van een algemene data strategie van de betrokken overheden. In algemene zin kunnen sociale media (locatie)gegevens snel inzicht geven in wat er op een bepaald moment op een bepaalde plaats aan de hand kan zijn. Dit is voor veel overheden een belangrijke aanvulling op traditionele informatievergaring. @en

Onderzoek AMS E-GOS Local Governance modellen van open data bij gemeenten en de performatie van open data. In 2017 is het Kenniscentrum Open Data begonnen met het project ‘Effective Governance of Open Spatial data’ (E-GOS) Local. Het E-GOS Local onderzoeksproject was een uitbreiding op het E-GOS-project uitgevoerd door Dr. Glenn Vancauwenberghe. Waar het E-GOS project zich richtte op de ver-gelijking van governance modellen voor open data beleid tussen landen, richtte het E-GOS Local zich op de vergelijking van governance modellen voor open geodata beleid tussen gemeenten. In dit on-derzoek is de link tussen de ingezette governance instrumenten voor open data beleid bij gemeenten met de performantie van dat open data beleid in kaart gebracht. Het governance model van het open data beleid van de gemeente Amsterdam is geanalyseerd. Aspecten die hierbij in beschouwing zijn genomen, zijn of aan alle governance componenten voor open data beleid voldaan wordt, welke in-strumenten worden toegepast en wat de impact is van het beleid op de performantie van open (geo)data. Daarnaast is een vergelijkend onderzoek uitgevoerd in Den Haag, Eindhoven, Rotterdam en Utrecht om een beeld te krijgen welke governance modellen voor open data beleid in andere ge-meenten gehanteerd worden, en welke effecten die op de performantie van open data hebben.@en

Much research has emphasised the benefits of open government data, and especially high-value data. The G8 Open Data Charter defines high-value data as data that improve democracy and encourage the innovative reuse of the particular data. Thus, governments worldwide invest resources to identify potential high-value datasets and to publish these data as open data. However, while the benefits of open data are well researched, the costs of publishing data as open data are less researched. This research examines the relationship between the costs of making data suitable for publication as (linked) open data and the societal benefits thereof. A case study of five high-value datasets was carried out in the Netherlands to provide a societal cost-benefit analysis of open high-value data. Different options were investigated, ranging from not publishing the dataset at all to publishing the dataset as linked open data. In general, it can be concluded that the societal benefits of (linked) open data are higher than the costs. The case studies show that there are differences between the datasets. In many cases, costs for open data are an integral part of general data management costs and hardly lead to additional costs. In certain cases, however, the costs to anonymize /aggregate the data are high compared to the potential value of an open data version of the dataset. Although, for these datasets, this leads to a less favourable relationship between costs and benefits, the societal benefits would still be higher than without an open data version.@en