Open Data Initiatives Research Articles

Showcase of Active Learning and Teaching Practices in Spatial Data Infrastructure (SDI) Education

Abstract. 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.

Handling qualitative preferences in SPARQL over virtual ontology-based data access

With the increase of data volume in heterogeneous datasets that are being published following Open Data initiatives, new operators are necessary to help users to find the subset of data that best satisfies their preference criteria. Quantitative approaches such as top-k queries may not be the most appropriate approaches as they require the user to assign weights that may not be known beforehand to a scoring function. Unlike the quantitative approach, under the qualitative approach, which includes the well-known skyline, preference criteria are more intuitive in certain cases and can be expressed more naturally. In this paper, we address the problem of evaluating SPARQL qualitative preference queries over an Ontology-Based Data Access (OBDA) approach, which provides uniform access over multiple and heterogeneous data sources. Our main contribution is Morph-Skyline++, a framework for processing SPARQL qualitative preferences by directly querying relational databases. Our framework implements a technique that translates SPARQL qualitative preference queries directly into queries that can be evaluated by a relational database management system. We evaluate our approach over different scenarios, reporting the effects of data distribution, data size, and query complexity on the performance of our proposed technique in comparison with state-of-the-art techniques. Obtained results suggest that the execution time can be reduced by up to two orders of magnitude in comparison to current techniques scaling up to larger datasets while identifying precisely the result set.

Linked data for libraries: Creating a global knowledge space, a systematic literature review

The Semantic Web in general and the Linked Open Data Initiative, in particular, are a growing movement for organisations to make their existing data available in a machine-readable format. Thus, institutions are highly encouraged to publish, share and interlink their data publicly. The more data are opened on the Web (Open Data), the more integrated sets of data will be connected in the Semantic Web (Linked Open Data). Within this context, libraries can complement their data by linking it to other, external data sources. The purpose of this article is to identify papers that refer to linked data in libraries, emphasising the ways that linked data empower libraries to put their knowledge in the context of the open-world, thus enhancing semantic technology innovations. The study considered papers published between 2008 and 2019 in English and presents the collected literature by grouping it according to the topic each paper refers to. The results show that libraries are facing a period of continuing change which present several challenges and indicate that they are moving towards developing new practices, policies and services.

الفوائد المتوقعة من البيانات الحكومية المفتوحة في المملكة العربية السعودية

ملخص توفر مبادرات البيانات الحكومية المفتوحة عددًا من الفرص التي تسعى إلى تحقيق فوائد سياسية واجتماعية واقتصادية وتشغيلية وتقنية من خلال إتاحتها للاستخدام العام. ولتحقيق ذلك، تستثمر المملكة العربية السعودية قدرًا كبيرًا من الجهد والمال في دعم هذه المبادرات التي تتمثل في إنشاء بوابات البيانات المفتوحة لاستخدامها في توفير مجموعات بيانات يتم تجميعها إداريًا ويمكن قراءتها آليًا. تهدف الدراسة بشكل أساسي إلى دراسة الفوائد المتوقعة من مبادرات البيانات الحكومية المفتوحة في المملكة العربية السعودية، من أجل الحصول على فهم عميق للفائدة المتوقعة من البيانات الحكومية المفتوحة في المملكة العربية السعودية، تم إجراء (10) مقابلات شبه منظمة (semi-structured interviews) مع المسؤولين الذين ينفذون مبادرات البيانات الحكومية المفتوحة. تشير النتائج إلى عدد كبير من الفوائد المتوقعة للبيانات الحكومية المفتوحة التي تتمحور حول: (1) الفوائد السياسية والاجتماعية، (2) الفوائد الاقتصادية، (3) الفوائد التشغيلية والتقنية. وفي الختام أشار الباحث إلى الحاجة لمزيد من الدراسات التي قد تبحث في التحديات التي تحد من تحقيق الفوائد المتوقعة من مبادرات البيانات الحكومية المفتوحة ومدى إمكانية تحسين هذه الفوائد. يمكن إجراء مثل هذه التحسينات على المستويين المحلي والإقليمي من خلال الاستفادة من مبادرات البيانات المفتوحة في البلدان الأخرى، مع مراعاة السياق والقيم المجتمعية لكل بلد. Open government data initiatives provide a number of opportunities that seek political, social, economic, operational, and technical benefits by making them available for public use. To support these initiatives, the Kingdom of Saudi Arabia invests a great deal of effort and money to set up open data portals to be used in providing data sets. They are administratively bundled and machine-readable. This study aims to examine the anticipated benefits of open government data initiatives in the Kingdom of Saudi Arabia. In order to obtain a deep understanding of the anticipated benefits of open government data in Saudi Arabia, 10 semi-structured interviews were conducted with officials implementing open government data initiatives. The results indicate various anticipated benefits for open government data centred around (1) political and social benefits, (2) economic benefits, and (3) operational and technical benefits. In conclusion, the researcher points to the need for further studies that may investigate the challenges that limit the achievement of the anticipated benefits of open government data initiatives and the extent to which these benefits can be improved. Such improvements may be made at the local and regional levels by taking advantage of open data initiatives in other countries, taking into account the context and societal values of each country.

Survey of Open Data Concepts Within Fundamental Physics: An Initiative of the PUNCH4NFDI Consortium

PUNCH4NFDI (Particles, Universe, NuClei and Hadrons for the NFDI) aims at developing concepts and tools for the efficient management of digital research products in fundamental physics research. At the heart of the research products are scientific data sets that should be made interoperable and available to a broad scientific community and the public for a sustainable usage (“open data”). The first PUNCH4NFDI “Open Data Workshop” gave the opportunity for an initial survey of existing and planned open data initiatives within the PUNCH science field. The paper addresses the conceptual differences and commonalities of the participating communities presented in the workshop. Existing open data collections were presented and discussed. This is an inquiry into the community’s requirements for a better use of open data and in this context also of “Open Science”.

Eligibility and Prevalence of the American Heart Association Heart Check Certification Program in the US Packaged Food and Beverage Supply: A Cross-Sectional Study.

Objective: Consumers in the US make choices within a food supply dominated by processed packaged foods and beverage products. Front-of-package nutrition labels (FOPL) equip consumers to make healthier choices, but further evaluation and regulation regarding FOPL format, scope, and display have been recommended by the World Health Organization. As a leader in consumer FOPL guidance, the American Heart Association's (AHA) Heart Check programme certifies food companies seeking to add an AHA Heart Check logo as a FOPL for qualifying heart healthy products. A cross-sectional assessment of the AHA Heart Check Standard Certification was conducted within the US packaged food and beverage supply to assess the eligibility and prevalence of the programme as a FOPL. Methods: Data were derived from Label Insight's Open Data initiative, which is the largest publicly-available US branded food composition database. The proportions of products that were certified and eligible to be certified for the Standard Certification were reported by nutrient attributes, grocery aisles and food brands. Results: Among 153,453 products examined, fewer than 1% exhibited the Heart Check certification on their label. Among products that were not Heart Check certified,13.8% were eligible for Standard Certification. The most common reason for ineligibility was the saturated fat content (52%), followed by total fat content (47%) and sodium content (47%). Heart Check certification and eligibility differed substantially across grocery aisle categories. Conclusions: The abundance of unhealthy products in the US packaged food and beverage supply and absence of harmonized FOPL policies suggest the need for FOPL like the Heart Check label to promote adherence to healthy diets. There are opportunities for food manufacturers and the AHA to certify more heart healthy foods and beverages. However, more consistent criteria and transparent labelling could enhance Heart Check certification to facilitate consumers' ability to make more informed and healthful purchases.

The BMS-LM ontology for biomedical data reporting throughout the lifecycle of a research study: From data model to ontology

Biomedical research data reuse and sharing is essential for fostering research progress. To this aim, data producers need to master data management and reporting through standard and rich metadata, as encouraged by open data initiatives such as the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines. This helps data re-users to understand and reuse the shared data with confidence. Therefore, dedicated frameworks are required. The provenance reporting throughout a biomedical study lifecycle has been proposed as a way to increase confidence in data while reusing it. The Biomedical Study - Lifecycle Management (BMS-LM) data model has implemented provenance and lifecycle traceability for several multimodal-imaging techniques but this is not enough for data understanding while reusing it. Actually, in the large scope of biomedical research, a multitude of metadata sources, also called Knowledge Organization Systems (KOSs), are available for data annotation. In addition, data producers uses local terminologies or KOSs, containing vernacular terms for data reporting. The result is a set of heterogeneous KOSs (local and published) with different formats and levels of granularity. To manage the inherent heterogeneity, semantic interoperability is encouraged by the Research Data Management (RDM) community. Ontologies, and more specifically top ontologies such as BFO and DOLCE, make explicit the metadata semantics and enhance semantic interoperability. Based on the BMS-LM data model and the BFO top ontology, the BioMedical Study - Lifecycle Management (BMS-LM) core ontology is proposed together with an associated framework for semantic interoperability between heterogeneous KOSs. It is made of four ontological levels: top/core/domain/local and aims to build bridges between local and published KOSs. In this paper, the conversion of the BMS-LM data model to a core ontology is detailed. The implementation of its semantic interoperability in a specific domain context is explained and illustrated with examples from small animal preclinical research.

TheyBuyForYou platform and knowledge graph: Expanding horizons in public procurement with open linked data

Public procurement is a large market affecting almost every organisation and individual; therefore, governments need to ensure its efficiency, transparency, and accountability, while creating healthy, competitive, and vibrant economies. In this context, open data initiatives and integration of data from multiple sources across national borders could transform the procurement market by such as lowering the barriers of entry for smaller suppliers and encouraging healthier competition, in particular by enabling cross-border bids. Increasingly more open data is published in the public sector; however, these are created and maintained in siloes and are not straightforward to reuse or maintain because of technical heterogeneity, lack of quality, insufficient metadata, or missing links to related domains. To this end, we developed an open linked data platform, called TheyBuyForYou, consisting of a set of modular APIs and ontologies to publish, curate, integrate, analyse, and visualise an EU-wide, cross-border, and cross-lingual procurement knowledge graph. We developed advanced tools and services on top of the knowledge graph for anomaly detection, cross-lingual document search, and data storytelling. This article describes the TheyBuyForYou platform and knowledge graph, reports their adoption by different stakeholders and challenges and experiences we went through while creating them, and demonstrates the usefulness of Semantic Web and Linked Data technologies for enhancing public procurement.

Federated Data Science to Break Down Silos [Vision

Similar to Open Data initiatives, data science as a community has launched initiatives for sharing not only data but entire pipelines, derivatives, artifacts, etc. (Open Data Science). However, the few efforts that exist focus on the technical part on how to facilitate sharing, conversion, etc. This vision paper goes a step further and proposes KEK, an open federated data science platform that does not only allow for sharing data science pipelines and their (meta)data but also provides methods for efficient search and, in the ideal case, even allows for combining and defining pipelines across platforms in a federated manner. In doing so, KEK addresses the so far neglected challenge of actually finding artifacts that are semantically related and that can be combined to achieve a certain goal.

'Data dregs' and its implications for AI ethics: Revelations from the pandemic.

Technology giants today preside over vast troves of user data that are heavily mined for profit. The concentration of such valuable data in private hands to serve mainly commercial interests must be questioned. In this article, we argue that if data is the new oil, Big Tech companies possess extensive, encompassing and granular data that is tantamount to premium oil. In contrast, governments, universities and think tanks undertake data collection efforts that are comparatively modest in scale, scope, duration and resolution and must contend with ‘data dregs’. Viewed against the backdrop of the COVID-19 pandemic, this sharp data asymmetry is unfortunate because the data Big Tech monopolizes is invaluable for boosting epidemiological control, formulating government policies, enhancing social services, improving urban planning and refining public education. We explain why this state of extreme data inequity undermines societal benefit and subverts our quest for ethical AI. We also propose how it should be addressed through data sharing and Open Data initiatives.

Pharmacokinetics of chloroquine and primaquine in healthy volunteers

BackgroundVivax malaria is a neglected disease. There is an irrefutable need for better treatments with higher acceptability and efficacy. The treatment efficacy is influenced by many factors, including bioavailability. Hence, a straightforward strategy to improve vivax malaria treatment efficacy is the deployment of good quality formulations of primaquine and chloroquine. As these treatments were developed more than 70 years ago, many of the available data on blood levels of both drugs are based on obsolete analytical methodologies or pharmaceutical formulations, which are not available anymore. Herein, the results of three bioequivalence studies are presented, providing individual pharmacokinetic data on chloroquine and primaquine of more than a hundred healthy volunteers and using up-to-date analytical methods.MethodsThree trials were designed as a single centre, randomized, single dose, open label, fasting, crossover bioequivalence studies comparing a new coated chloroquine tablet to the uncoated tablet, and 5 and 15 mg primaquine formulations to either an international reference product or the currently distributed tablets. Plasma concentrations of chloroquine and primaquine were measured using a validated HPLC–MS/MS method in accordance with current international regulatory requirements for bio-analytical methods.ResultsIn total, a hundred eleven healthy volunteers of both genders were included in the three studies (n = 32; 30 and 56 respectively). No serious adverse events occurred. Drugs levels were measured in 5,520 blood samples. The estimated ratio of the geometric means of Cmax, AUC0-t and AUC0-inf of test and reference drugs and their 90% CI for chloroquine 150 mg, primaquine 15 mg and primaquine 5 mg were: 95.33% (89.18; 101.90), 86. 85% (82.61; 91.31), and 84.45% (76.95; 92.67); 93.28% (81.76; 106.41), 94.52% (86.13; 103.73) and 93.93% (85.83; 102.79); 97.44% (90.60; 104.78), 93.70% (87.04; 100.87) and 91.36% (85.27; 97.89), respectively. As Cmax and AUC0-t 90% CI were within the acceptance interval of 80–125% in all cases, the formulations tested were bioequivalent.ConclusionsIn conclusion, the three studies provided detailed chloroquine and primaquine pharmacokinetic data in accordance with current regulatory standards. Together with other open data initiatives, this individual data may increase the accuracy of pharmacokinetic models guiding best dose, new combinations, regimens and formulations to optimize the current chloroquine and primaquine treatments for vivax malaria. The data presented here may support the deployment of high-quality drugs and evidence-based public health policies.

Spy it before you try it: Intrinsic Cues and Open Data App Adoption

Access to open data from governments can benefit citizens by increasing transparency, accountability, and economic growth. While governments' open data initiatives are increasing, there is a lack of understanding of the factors influencing the adoption of open data mobile apps, which serve as an essential channel for open data use. Drawing from the signaling theory and IS success literature, this study investigates how information-related intrinsic cues available to potential users influence open data apps' adoption. Based on an analysis of open data apps in the Google Play store, we find that information cues such as whether an open data app provides complete and current information and is accessible in offline mode influence its adoption. Our findings contribute to the open data literature and provide implications for stakeholders in open data ecosystems such as governments, citizens, and organizations providing open data-related products and services.

Behavioral Taxation: Opportunities and Challenges

The field of behavioral taxation dates back at least to the 1950s. In this contribution I will explore the opportunities and challenges in the area, with a particular focus on tax compliance. I will focus on the data required to make further progress, discussing what can be improved when working with surveys and how the fie ld could benefit from open government data initiatives. I focus on collaborative efforts among scientists as well as with the government or the tax administration and examine many potenti al areas of exploration. The opportunities currently emerging due to digitalization provide not only interesting avenues for collaborations but also a natural method of using tools such as lab and field experiments. In addition, I will discuss potential dangers faced by the field of behavioral economics that also threaten the field of behavioral taxation.

Open Data Initiatives of Government Agencies as Data Brokers: Modeling and Hypothesis Validation with an Open Data Ecosystem

Open Data Initiatives of Government Agencies as Data Brokers: Modeling and Hypothesis Validation with an Open Data Ecosystem

Automated Annotations for AI Data and Model Transparency

The data and Artificial Intelligence revolution has had a massive impact on enterprises, governments, and society alike. It is fueled by two key factors. First, data have become increasingly abundant and are often available openly. Enterprises have more data than they can process. Governments are spearheading open data initiatives by setting up data portals such as data.gov and releasing large amounts of data to the public. Second, AI engineering development is becoming increasingly democratized. Open source frameworks have enabled even an individual developer to engineer sophisticated AI systems. But with such ease of use comes the potential for irresponsible use of data. Ensuring that AI systems adhere to a set of ethical principles is one of the major problems of our age. We believe that data and model transparency has a key role to play in mitigating the deleterious effects of AI systems. In this article, we describe a framework to synthesize ideas from various domains such as data transparency, data quality, data governance among others to tackle this problem. Specifically, we advocate an approach based on automated annotations (of both data and the AI model), which has a number of appealing properties. The annotations could be used by enterprises to get visibility of potential issues, prepare data transparency reports, create and ensure policy compliance, and evaluate the readiness of data for diverse downstream AI applications. We propose a model architecture and enumerate its key components that could achieve these requirements. Finally, we describe a number of interesting challenges and opportunities.

Social barriers to open (water) data

AbstractAlthough the proliferation of open water data platforms and initiatives in recent years is a laudable phenomenon, there is little empirical evidence indicating whether and to what extent these efforts are generating anticipated benefits of improved transparency, citizen participation, innovation, and water resource decision making. Relatedly, water resource researchers have devoted little attention to identifying and accounting for barriers that may be limiting open water data efforts from realizing their potential. The premise of this overview is that (a) open water data efforts could be improved with a better understanding of the non‐technical challenges and that (b) water researchers interested in open water data would benefit from delving into the emerging body of research in public policy, information science, and other disciplines on open data barriers more broadly. However, the research on open data barriers has neglected water sustainability issues. In light of this asymmetry, the aim of this overview is to foster interdisciplinary engagement on this topic by introducing the water resource community to this literature via a discussion of key social barriers to open data. Additionally, I hope to motivate water resource researchers to develop a two‐way interdisciplinary engagement by making original research contributions to this larger literature.This article is categorized under: Engineering Water Science of Water > Methods Human Water > Water Governance Human Water > Water as Imagined and Represented

Co-Designing the Future With Public Interest Technology

This special issue is dedicated to the theme of public interest technology (PIT) <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> . PIT acknowledges that technological potential can be harnessed to satisfy the needs of civil society. In other words, technology can be seen as a public good that can benefit all, through an open democratic system of governance, with open data initiatives, open technologies, and open systems/ecosystems designed for the collective good, as defined by respective communities that will be utilizing them. Just like in the established field of public interest law (PIL) <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> and public interest journalism (PIJ) <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> , we can consider potential fields around the idea of PIT <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref> , <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[6]</xref> , such as public interest co-design (PITco), even public interest engagement (PITengage) or public interest consulting (PIC). For decades, public interest engineers (PIEs) have volunteered their time to collaborate in meaningful participative engagements. These engineers have self-organized some impressive collectives including Engineers Without Borders, ASCE Disaster Assistance Volunteer Program, Appropriate Infrastructure Development Group, Architecture for Humanity, Bridges to Prosperity, Bridging the Gap Africa, Engineers for a Sustainable World, GISCorps, Habitat for Humanity, National Engineering Projects in Community Service, just to name a few. These collectives and initiatives call attention to the primary role of a PIT practitioner. That is, the importance of PIT practitioners serving as transdisciplinary intermediaries between the community and the STEM disciplines and technical teams, emphasizing the importance of justice, equity, and inclusion in the design and deployment of new technologies <xref ref-type="bibr" rid="ref7" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[7]</xref> that allow for positive social transformation and empowerment <xref ref-type="bibr" rid="ref8" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[8]</xref> .

Open science, the replication crisis, and environmental public health

ABSTRACT Concerns about a crisis of mass irreplicability across scientific fields (“the replication crisis”) have stimulated a movement for open science, encouraging or even requiring researchers to publish their raw data and analysis code. Recently, a rule at the US Environmental Protection Agency (US EPA) would have imposed a strong open data requirement. The rule prompted significant public discussion about whether open science practices are appropriate for fields of environmental public health. The aims of this paper are to assess (1) whether the replication crisis extends to fields of environmental public health; and (2) in general whether open science requirements can address the replication crisis. There is little empirical evidence for or against mass irreplicability in environmental public health specifically. Without such evidence, strong claims about whether the replication crisis extends to environmental public health – or not – seem premature. By distinguishing three concepts – reproducibility, replicability, and robustness – it is clear that open data initiatives can promote reproducibility and robustness but do little to promote replicability. I conclude by reviewing some of the other benefits of open science, and offer some suggestions for funding streams to mitigate the costs of adoption of open science practices in environmental public health.

Data through Movement: Designing Embodied Human-Data Interaction for Informal Learning

Abstract When you picture human-data interactions (HDI), what comes to mind? The datafication of modern life, along with open data initiatives advocating for transparency and access to current and ...

Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough?

Nowadays, governments launch open government data (OGD) portals that provide data that can be accessed and used by everyone for their own needs. Although the potential economic value of open (government) data is assessed in millions and billions, not all open data are reused. Moreover, the open (government) data initiative as well as users’ intent for open (government) data are changing continuously and today, in line with IoT and smart city trends, real-time data and sensor-generated data have higher interest for users. These “smarter” open (government) data are also considered to be one of the crucial drivers for the sustainable economy, and might have an impact on information and communication technology (ICT) innovation and become a creativity bridge in developing a new ecosystem in Industry 4.0 and Society 5.0. The paper inspects OGD portals of 60 countries in order to understand the correspondence of their content to the Society 5.0 expectations. The paper provides a report on how much countries provide these data, focusing on some open (government) data success facilitating factors for both the portal in general and data sets of interest in particular. The presence of “smarter” data, their level of accessibility, availability, currency and timeliness, as well as support for users, are analyzed. The list of most competitive countries by data category are provided. This makes it possible to understand which OGD portals react to users’ needs, Industry 4.0 and Society 5.0 request the opening and updating of data for their further potential reuse, which is essential in the digital data-driven world.