Open Data Services Research Articles

Are We Back to Normal? A Bike Sharing Systems Mobility Analysis in the Post-COVID-19 Era

In recent years, numerous cities around the world have adopted bike sharing systems (BSSs). The increasing popularity of these transportation means is directly related to their eco-friendly and health advantages. Several factors affect how citizens make use of BSS, for instance, the size and configuration of a city, where docking stations are located, the associated prices, and others. Moreover, these systems have different usage patterns that vary according to the month, day, or hour but remain constant when compared yearly. However, the onset of the COVID-19 pandemic modified mobility behaviors as various governments around the world implemented mobility restrictions to avoid the spread of the virus. The objective of this investigation is to determine if the usage patterns of BSSs have changed permanently or if we have recovered pre-pandemic levels and usage patterns. Given the special characteristics of each BSS, this study focuses on Barcelona’s BSS, called Bicing. To understand the impact of other BSSs, the further analysis of each system’s unique characteristics is necessary. The study employs bike usage information from the public open data service maintained by Barcelona City Hall, namely, the Open Data BCN website, from January 2019 to December 2023, and it covers mechanical and electrical bikes with more than 4 million records per month. The results show that usage patterns were similar before and after the pandemic; the usage increased in 2021 and 2022 and stabilized in 2023, registering a rise of 17.5% in Bicing usage from 2021 to 2023. However, bike type preferences have changed for reasons unrelated to the pandemic restrictions. The main limitation of this investigation is the lack of continuity in the data due to a change in the company that provides the service in Barcelona. For future research, data from other transportation means can be used to analyze all communication behavior in this city. Additionally, if data are available, a study by gender and age can be performed and used to improve the system for certain groups.

Predictive Analyses of Traffic Level in the City of Barcelona: From ARIMA to eXtreme Gradient Boosting

This study delves into the intricate dynamics of urban mobility, a pivotal aspect for policymakers, businesses, and communities alike. By deciphering patterns of movement within a city, stakeholders can craft targeted interventions to mitigate traffic congestion peaks, optimizing both resource allocation and individual travel routes. Focused on Barcelona, Spain, this paper draws on data sourced from the city council’s open data service. Through a blend of exploratory analysis, visualization techniques, and modeling methodologies—including time series analysis and the eXtreme Gradient Boosting (XGBoost) algorithm—the research endeavors to forecast traffic conditions. Additionally, a study of variable importance is carried out, and Shapley Additive Explanations are applied to enhance the interpretability of model outputs. Findings underscore the limitations of traditional forecasting methods in capturing the nuanced spatial and temporal dependencies present in traffic flows, particularly over medium- to long-term horizons. However, the XGBoost model demonstrates robust performance, with the area under ROC curves consistently exceeding 80%, indicating its efficacy in handling non-linear traffic data variables.

Semantic Solutions for Democratizing Archaeological and Numismatic Data Analysis

Museums, heritage agencies and other institutions responsible for managing archaeological cultural heritage across Europe are engaged in developing digital platforms to better open their collections to the public as a common resource for the purposes of discovering, learning about, and sharing our common past. This paper explores the potential of new semantic computing technologies in democratizing not only public access to digital cultural heritage records, but also to computational and Linked Open Data -assisted data analysis and knowledge discovery. As a case study, we consider archaeological and numismatic Open Data services in Finland, and discuss the research results obtained during the ongoing development work for the CoinSampo framework for opening Finnish and international numismatic data. Existing digital cultural heritage services are often built with the needs of professional collections management in mind. The presentation of the records is typically structured after the familiar format established for the printed catalogues of yesteryear, with few analytical tools that would take advantage of the potential of digital data to probe and visualize internal relationships and patterns within the full body of the opened material. CoinSampo, however, will provide scientific tools to new audiences among the non-professional public who have not enjoyed such a level of access to numismatic data. The broad range of target audiences we envisage includes collections managers, who will benefit from enhanced access to their own data for updating records and for error detection and correction, as well as academic researchers interested in using the material in scientific analysis. Importantly, it also includes non-professional groups such as coin collectors, educators, local historians, and the archaeological hobby metal-detectorists who produce most of the new coin finds entering the national collections in Finland and in other European countries where detecting is legal. By adopting a citizen science and participatory heritage approach in the development of Open Data services, we aim to promote a technological model for cultural heritage dissemination that addresses the needs of a wide spectrum of different user audiences inside and outside the professional sphere.

OCR Pipeline for Transforming Parliamentary Debates into Linked Data: Case ParliamentSampo - Parliament of Finland on the Semantic Web


 
 
 This paper presents the OCR pipeline created for ParliamentSampo - Parliament of Finland on the Semantic Web, a Linked Open Data (LOD) service, data infrastructure, and semantic portal for studying Finnish political culture, language, and networks of the Members of Parliament (MP). A knowledge graph of linked data has been created based on ca. 967 000 speeches in all plenary sessions of the Parliament of Finland in 1907—2022; the data is also available in XML format, utilizing the new international Parla- CLARIN format. A central part of the historical debates 1907-1999 was available only as PDF documents of fairly low OCR quality and had to be OCRed first; this paper reports lessons learned from this process.
 
 

OpenMindat: Open and FAIR mineralogy data from the Mindat database

AbstractThe open data movement has brought revolutionary changes to the field of mineralogy. With a growing number of datasets made available through community efforts, researchers are now able to explore new scientific topics such as mineral ecology, mineral evolution and new classification systems. The recent results have shown that the necessary open data coupled with data science skills and expertise in mineralogy will lead to impressive new scientific discoveries. Yet, feedback from researchers also reflects the needs for better FAIRness of open data, that is, findable, accessible, interoperable and reusable for both humans and machines. In this paper, we present our recent work on building the open data service of Mindat, one of the largest mineral databases in the world. In the past years, Mindat has supported numerous scientific studies but a machine interface for data access has never been established. Through the OpenMindat project we have achieved solid progress on two activities: (1) cleanse data and improve data quality, and (2) build a data sharing platform and establish a machine interface for data query and access. We hope OpenMindat will help address the increasing data needs from researchers in mineralogy for an internationally recognized authoritative database that is fully compliant with the FAIR guiding principles and helps accelerate scientific discoveries.

Analyzing biography collections historiographically as Linked Data: Case National Biography of Finland

Biographical collections are available on the Web for close reading. However, the underlying texts can also be used for data analysis and distant reading, if the documents are available as data. Such data is usable for creating intelligent user interfaces to biographical data, including Digital Humanities tooling for visualizations, data analysis, and knowledge discovery in biographical and prosopographical research. In this paper, we re-use biographical collection data from a historiographical perspective for analyzing the underlying collection. For example: What kind of people have been included in the collection? Does the language used for describing female biographees differ from that for men? As a case study, the Finnish National Biography, available as part of the Linked Open Data service and semantic portal BiographySampo – Finnish Biographies on the Semantic Web is used. The analyses show interesting results related to, e.g., how specific prosopographical groups, such as women or professional groups are represented and portrayed. Various novel statistics and network analyses of the biographees are presented. Our analyses give new insights to the editors of the National Biography as well as to researchers in biography, prosopography, and historiography. The presented approach can be applied also to similar biography collections in other countries.

Constellations of Correspondence

This paper presents the vision of aggregating, harmonizing, and publishing letter catalog metadata (information e.g. of senders, receivers and datings of letters) from cultural heritage (CH) institutions in Finland as a single reconciled Linked Open Data (LOD) service and a semantic portal providing data analytical tools for researchers. The research is conducted as part of the consortium research project Constellations of Correspondence (CoCo). The target of the project is to study – for the first time – scattered, heterogeneous epistolary metadata regarding the period of the Grand Duchy of Finland (1809–1917) as one, integrated dataset and make it interoperable and available. This will enable scholars to ask ambitious research questions in the field of computer science and to conduct empirical, bottom-up case studies e.g. on epistolary culture, communicative networks, and heritagization processes. This paper discusses one of the first datasets acquired by the project, the letter collection of the Board of the Finnish Art Society (1846–1901), provided by the Finnish National Gallery, which contains details of c. 1150 letters sent or received by c. 400 actors.

Evaluating a Business Ecosystem of Open Data Services Using the Fuzzy DEMATEL-AHP Approach

The government has formulated and implemented an open data policy to promote administrative transparency and economic development in recent years. Therefore, most previous studies on open data have focused on e-government. Consequently, an open data service industry committed to providing innovative value-added data application services has emerged in Taiwan, with small- and medium-sized enterprises being the driving force. However, in a complex industrial environment, enterprises need to promote efficient data services development by developing a cross-disciplinary business ecosystem cooperatively. Nevertheless, few studies have discussed the open data service industry from the perspective of business ecosystems, making it impossible for enterprises to evaluate the business ecosystem of open data services built by them. In this study, we used the fuzzy analytic hierarchy process and fuzzy decision-making and trial evaluation laboratory methods to construct five evaluation dimensions and thirty-one evaluation criteria. We organized them into an evaluation scale to measure the business ecosystem’s performance of open data services built by enterprises. Then, using the case analysis method, we tested the applicability of the evaluation scale. This study examined the assessment scale of ecosystem construction in the open data industry, from the perspective of a business ecosystem, and analyzed the importance of each key criterion.

Finnish Parliament on the Semantic Web

This paper introduces the system ParliamentSampo – Parliament of Finland on the Semantic Web, a Linked Open Data (LOD) service, data infrastructure, and semantic portal for studying Finnish political culture, language, and networks of the Members of Parliament (MP). The article presents the vision behind the system, the LOD service, and explores the possibilities to utilize it in research and application development. A knowledge graph of linked data has been created based on ca. 962 000 speeches in all plenary sessions of the Parliament of Finland in 1907—2021; the data is also available in XML format, utilizing the new international Parla-CLARIN format. For the first time, the entire time series of the Finnish parliamentary speeches has been converted into data and a data service in a unified format. In addition, the speeches have been interlinked with another knowledge graph created from the database of the MPs and enriched from other data sources into a broader ontology-based data service. The paper shows how the LOD service SPARQL endpoint can be used to research parliamentary culture, the use of political language, and networks of politicians through data analysis. The service endpoint can also be used to develop applications for different user groups without programming skills, such as the ParliamentSampo semantic portal introduced in the paper, too. This application aims to make political decision making more transparent to the general public, media, politicians, and other end users.

АНАЛІЗ ЦИФРОВИХ ТЕХНОЛОГІЙ ФОНДОВОЇ БІРЖОВОЇ ТОРГІВЛІ В УКРАЇНІ

Activation of investment activity for the recovery of the economy after the corona crisis requires the development of stock exchange trading as part of trading in state securities, municipal securities, corporate securities, etc. Institutional, organizational and technical conditions have not been created for the development of stock exchange trading in Ukraine. The purpose of the article is to study the current state of digital technologies of stock exchange trading in Ukraine. An analysis of stock exchange trading in Ukraine was carried out based on the analysis of general activity on the stock market, analysis of stock market segments and activities of operators of organized markets. In 2014–2017, the stock market of Ukraine was in a state of stagnation due to a decrease in trading volumes. The recovery of the activity of stock market participants took place in 2018–2021. Activity on the stock market of Ukraine is ensured mainly in the secondary segment. The share of the secondary market in the stock market of Ukraine in 2014–2021 was more than 97%. The digital technologies of the stock exchange "Perspektiva" (Electronic trading system, BIT eTrade Mail, BIT eTrade, BIT eTrade Future, BIT eTrade IPO, BIT ePayment, BIT eReport, etc.) are characterized. Further restoration of stock exchange trading in Ukraine and use of the potential of the stock market for the needs of economic recovery is possible only under certain conditions. There are an increase in the number of issuers of debt securities and equity securities, publicity of information about the stock market and stock market participants, protection of stock market participants, improvement of financial literacy of the population, improvement of digital technologies of stock exchange trading. It is possible to improve digital technologies and activate the digitization of stock exchange trading in Ukraine through the development of software products and mobile applications for all stock trading participants, the use of artificial intelligence, Big Data for the formation and organization of information on the stock market, the integration of digital technologies of stock exchange trading with state registers and open data services.

Systematic and ontology-based approach to interoperable cross-domain open government data services

PurposeOpen government data (OGD) has emerged as a radical paradigm shift and endeavor among government administrations across the world mainly due to its promises of transparency, accountability, public-private collaboration, civic participation, social innovation and data-driven value creation. Complexity, cross-cutting nature, diversity of data sets, interoperability and quality issues usually hamper unlocking the full potential value of data. To tackle these challenges, this paper aims to provide a novel solution using a top-down approach.Design/methodology/approachIn this paper, the authors propose a systematic ontology-based approach combined with a novel architecture and its corresponding processes enabling organizations to carry out all the steps in the OGD value chain. In addition, an OGD Platform including a portal (www.iranopendata.ir) and a data management system (www.ogdms.iranopendata.ir) are developed to showcase the proposed solution.FindingsThe efficiency and the applicability of the solution are evaluated by a real-life use case on energy consumption of the buildings of the city of Tehran, Iran. Finally, a comparison was made with existing solutions, and the results show the proposed approach is able to address the existing gaps in the literature.Originality/valueThe results imply that modeling and designing the data model, as well as exploiting an ontology-based approach are critical pillars to create rich, relevant and well-described OGD data sets. Moreover, clarity on processes, roles and responsibilities are the key factors influencing the quality of the published data services. Thus, to the best of the knowledge, this is the first study that exploits and considers an ontology-based approach in a top-down manner to create OGD data sets.

Name and Subject Heading Reconciliation to Linked Open Data Authorities using Virtual International Authority File and Library of Congress Linked Data Service APIs: A Case Study featuring Emblematica Online

Libraries are actively exploring ways to use Linked Open Data (LOD) services to enhance discovery and facilitate the use of collections. Emblematica Online, which provides integrated discovery of digitized emblem books, incorporates LOD in its design. As an implementation prerequisite, the Virtual International Authority File (VIAF) and Library of Congress (LC) Linked Data Service APIs were used to reconcile name and subject strings from legacy catalog records with global authoritative links from LOD resources. This case study reports on the automated reconciliation process used and examines the efficacy of the APIs in reconciling name and subject heading entities. While a majority of strings were successfully reconciled, analysis suggests that data cleanup, rigorously consistent formatting of metadata strings, and addressing challenges in existing LOD resources and services could improve results for this corpus.

Citizen science archaeological finds on the Semantic Web: the FindSampo framework

FindSampo fosters collecting, sharing, publishing and studying archaeological finds discovered by the public. The framework includes the following: a mobile find-reporting system; a semantic portal for researchers, the public and collection managers to use; and a Linked Open Data service for creating custom data analyses and for application developers.

An open web‐based module developed to advance data‐driven hydrologic process learning

AbstractThe era of ‘big data’ promises to provide new hydrologic insights, and open web‐based platforms are being developed and adopted by the hydrologic science community to harness these datasets and data services. This shift accompanies advances in hydrology education and the growth of web‐based hydrology learning modules, but their capacity to utilize emerging open platforms and data services to enhance student learning through data‐driven activities remains largely untapped. Given that generic equations may not easily translate into local or regional solutions, teaching students to explore how well models or equations work in particular settings or to answer specific problems using real data is essential. This article introduces an open web‐based module developed to advance data‐driven hydrologic process learning, targeting upper level undergraduate and early graduate students in hydrology and engineering. The module was developed and deployed on the HydroLearn open educational platform, which provides a formal pedagogical structure for developing effective problem‐based learning activities. We found that data‐driven learning activities utilizing collaborative open web platforms like CUAHSI HydroShare and JupyterHub to store and run computational notebooks allowed students to access and work with datasets for systems of personal interest and promoted critical evaluation of results and assumptions. Initial student feedback was generally positive, but also highlighted challenges including trouble‐shooting and future‐proofing difficulties and some resistance to programming and new software. Opportunities to further enhance hydrology learning include better articulating the benefits of coding and open web platforms upfront, incorporating additional user‐support tools, and focusing methods and questions on implementing and adapting notebooks to explore fundamental processes rather than tools and syntax. The profound shift in the field of hydrology toward big data, open data services and reproducible research practices requires hydrology instructors to rethink traditional content delivery and focus instruction on harnessing these datasets and practices in the preparation of future hydrologists and engineers.

Akatemiasampo-portaali ja -datapalvelu henkilöiden ja henkilöryhmien historialliseen tutkimukseen

AcademySampo – Academic people in Finland 1640–1899 is a portal and a Linked Open Data service on the Semantic Web. AcademySampo contains richly interlinked open data about all people that have got academic education in Finland in 1640–1899. The system is targeted to researchers and the general public for biographical and prosopographical research. This review gives an overview on how AcademySampo can be utilized in practise with its novel digital humanities tools included in the portal and by using the data service via APIs.

Harmonizing and publishing heterogeneous premodern manuscript metadata as Linked Open Data

AbstractManuscripts are a crucial form of evidence for research into all aspects of premodern European history and culture, and there are numerous databases devoted to describing them in detail. This descriptive information, however, is typically available only in separate data silos based on incompatible data models and user interfaces. As a result, it has been difficult to study manuscripts comprehensively across these various platforms. To address this challenge, a team of manuscript scholars and computer scientists worked to create “Mapping Manuscript Migrations” (MMM), a semantic portal, and a Linked Open Data service. MMM stands as a successful proof of concept for integrating distinct manuscript datasets into a shared platform for research and discovery with the potential for future expansion. This paper will discuss the major products of the MMM project: a unified data model, a repeatable data transformation pipeline, a Linked Open Data knowledge graph, and a Semantic Web portal. It will also examine the crucial importance of an iterative process of multidisciplinary collaboration embedded throughout the project, enabling humanities researchers to shape the development of a digital platform and tools, while also enabling the same researchers to ask more sophisticated and comprehensive research questions of the aggregated data.

Promoting Open Data services to decision-makers: Providing interactive data through Web Maps and Web Applications for Oradea city and Bihor county

Maps are known since antiquity, the oldest examples are from the 6th to 5th centuries BC. From the Babylonian world map, known as the Imago Mundi, maps evolved continuously. In the present day, maps allow us to visualize data in new and informative ways and to present it in an interactive manner. In recent years, web mapping technology has become a necessity for urban planning, and not only, by helping the population to take better and informed decisions. When communicating with decision-makers or only to take the best decision we need first to assess the answers to all the following questions “What and Why and When and How and Where and Who” and what better way to do this than by using Open Data? The governmental and administrative institutions have data in the form of historical maps, topographic maps, digital terrain models, statistical analysis, and other types of data. Our goal was to make these data available for the public in an easy and interactive way, by creating web maps, applications, and a website that gathers all these data.

Improving Opportunities for New Value of Open Data: Assessing and Certifying Research Data Repositories

Investments in research that produce scientific and scholarly data can be leveraged by enabling the resulting research data products and services to be used by broader communities and for new purposes, extending reuse beyond the initial users and purposes for which the data were originally collected. Submitting research data to a data repository offers opportunities for the data to be used in the future, providing ways for new benefits to be realized from data reuse. Improvements to data repositories that facilitate new uses of data increase the potential for data reuse and for gains in the value of open data products and services that are associated with such reuse. Assessing and certifying the capabilities and services offered by data repositories provides opportunities for improving the repositories and for realizing the value to be attained from new uses of data. The evolution of data repository certification instruments is described and discussed in terms of the implications for the curation and continuing use of research data.

Управление на основе больших данных в сфере образования

The article discusses a new technology in the field of administration – a method of data-based management. In the field of education, analytics is the necessary manager’s competence to fulfill his work duties. The author identified the problem of transforming legal norms when working with open data, which did not affect the change in institutional and cultural norms of “data- based management” in managerial decision-making practice. The article provides a comparative analysis of the professional standards’ requirements and educational programs for the managerial personnel’s professional development in the field of education. The author analyzed two aspects of the development of a data-based management system: personnel – the development of educational programs for training managerial specialists who can use such technology, and infrastructure – the development of digital open data services and digital data processing services for making managerial decisions. The tasks of developing education through the analysis of data for assessing its quality are reflected in the Decree of the President of the Russian Federation “On national goals and strategic objectives for the development of the Russian Federation for the period up to 2024” and can be implemented based on the professional capital of managers using tools for analyzing such data. It is necessary to improve the interaction of electronic information exchange services for more effective information interaction and the construction of analytical reporting. This will allow for the efficient integration of data from different information systems and electronic resources and obtain the necessary data of the information of interest.

Working hours and traffic accident injuries: Case study in Barcelona

Working hours in Spain is generally last for 8 hours per day with a maximum of 40 hours per week. Working hours, therefore, can impact the traffic flow and characteristics due to the intensity of road usage by different road users. On the other side, traffic accidents can also be impacted by several temporal factors that may lead to a higher number of traffic accidents or may increase the level of injury alongside other risk factors. In this study, these timings are examined to comprehend the influence of the temporal factors represented by the working hours scheme on traffic accident injuries in Barcelona. Another temporal factor which is the season of the year is included to provide a wider and clearer image for the conducted results and the current situation. The data is collected from the open data service provided by the City Hall of Barcelona. Data preparation and segregation to include the categories of working hours that may lead to a different level of injury resulted from a traffic accident is, firstly, carried. Then, a machine learning model is applied to classify the correlations for both the temporal factors and traffic accidents. Eventually, a Tree Augmented Naïve Bayes model is applied. The results showed that both working hours timing and summer season have higher probabilities of having traffic accidents slight injuries with different medical care assistance provided compared to other timings.