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From beginning to today, pHealth has been a data driven service that collects and uses personal health information (PHI) for personal health services and personalized healthcare. As a result, pHealth services use intensively ICT technology, sensors, computers and mathematical algorithms. In past, pHealth applications were focused to certain health or sickness related problem, but in today they use mobile devices, wireless networks, Web-technology and Cloud platforms. In future, pHealth uses information systems that are highly distributed, dynamic, increasingly autonomous, multi-stakeholder data driven eco-system having ability to monitor anywhere person's regular life, movements and health related behaviours. Because privacy and trust are pre-requirements for successful pHealth, this development raises huge privacy and trust challenges to be solved. Researchers have shown that current privacy approaches and solutions used in pHealth do not offer acceptable level of privacy, and trust is only an illusion. This indicates, that today's privacy models and technology shall not be moved to the future pHealth. The authors have analysed interesting new privacy and trust ideas published in journals, and found that they seem to be effective but offer only a partial solution. To solve this weakness, the authors used a holistic system view to aspects impacting privacy and trust in pHealth, and created a template that can be used in planning and development future pHealth services. The authors also propose a tentative solution for future trustworthy pHealth. It combines privacy as personal property and trust as legal binding fiducial duty approaches, and uses a Blockchain-based smart contract solution to store person's privacy and trust requirements and service providers' promises. publishedVersion

Public sector organizations are moving from digitalization toward digital transformation. However, this fast-paced and fundamental transformation can be difficult to manage with traditional approaches. One solution is the application of agile methods and adaptive governance. Currently, it is not clear whether the agile mindset can be successfully adopted by public sector organizations, which value stability over agility. To provide a much-needed example of how the agile approach can be introduced in the context of the public sector, this paper presents the findings of a single case study of a municipal IT department. The case shows how the IT department adopted an agile IT management approach in response to the growing demand for digital services and the effects of the digital transformation inside the IT department and throughout the municipality. The findings reveal that introducing agile IT management in public sector IT departments can help improve operational flexibility, collaboration, and customer service despite barriers, such as traditional operational structures, and resistance to change. Consequently, bottom-up agile experiments can drive large-scale agile transformations, especially if such transformations are also accepted at the organizational level. acceptedVersion

The WHO Health Emergencies Programme combined online tools with adult learning techniques to develop an innovative online leadership course. A combination of self-paced learning and online classes were used to deliver skills-based leadership training tailored to public health staff working in emergency response roles. Although using an online approach was considered a temporary solution to counter travel restrictions during the pandemic, the advantages have challenged preconceptions that effective learning, networking and peer exchange for leadership can only be achieved through face-to-face learning.

openaire: EC/H2020/101004825/EU//InTaVia 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.

In pursuit of equitable access to emergency-related knowledge, the World Health Organization (WHO) translates COVID-19 and other infectious disease courses into multiple languages on its open-access online learning platform OpenWHO.org. Languages spoken by vulnerable or underserved populations in low- and middle-income countries and in outbreak-prone and affected areas are prioritized. Accessing learning in preferred languages enhances uptake and comprehension. In this study, we assess and compare the initial enrollment levels and global reach of these multilingual courses. On average, OpenWHO's 38 COVID-19 courses have each been translated into 4.8 languages. The platform hosts courses in 55 different languages with 10.4 million words translated. The findings identify which available languages were most utilized for COVID-19 learning to inform course production and outreach strategies. Languages were used differently across geographic regions, calling for localized learning offerings. A streamlined multilingual publishing scheme, ensuring quick and effective delivery of diverse languages, is critical to achieving greater equity of access to knowledge. publishedVersion

INTRODUCTION: OpenWHO provides open-access, online, free and real-time learning responses to health emergencies, which includes capacitating healthcare providers, first liners, medical students and even the general public. During the pandemic and to date, an additional 40 courses for COVID-19 response have led to a massive increase in the number of learners and a change in user's trends. This paper presents initial findings on enrollment trends, use and completion rates of health emergency courses offered on OpenWHO. METHODS: The enrolment data statistics were drawn from OpenWHO's built-in reporting system, which tracks learners' enrolments, completion rates, demographics and other key course-related data, This information was collected from the beginning of the OpenWHO launch in 2017 up until October 2021. RESULTS: Average course completion rate on OpenWHO including all courses and languages was equal to 45.9%. Nearly half (46.4%) of all OpenWHO learners have enrolled in at least 2 courses and 71 000 superusers have completed at least 10 courses on the platform. CONCLUSION: WHO's learning platform during the pandemic registered record high completion rates and repeat learners enrollment. This highlights the massive impact of the OpenWHO online learning platform for health emergencies and the tangible knowledge transfer and access to health literacy. publishedVersion

Computers were originally developed for executing complex calculations fast and effectively. The intelligence of computer was based on arithmetic capabilities. This has been the mainstream in the development of computers until now. In the middle of 1950s a new application area, Artificial Intelligence (AI), was introduced by researchers. They had interest to use computers to solve problems in the way intelligent beings do. The architecture, which supported calculations, were conquered to perform tasks associated with intelligence beings, to execute inference operations and to simulate human sense. Artificial intelligence has had several reincarnation cycles; it has reappeared in different manifestations since this research area became interesting for the researchers. All the time a lot of discussion about intelligence of these systems has been going on - are the AI based systems and robots intelligent, what is the difference of human and machine intelligence, etc. Abilities related to intelligence cover ability to acquire and apply knowledge and skills, as well as ability to learn. AI provides different manifestations to the term 'intelligence': the human intelligence is a wide variety of different types of intelligence, as well as the meaning of artificial intelligence has varied over time. In our paper we will look to this term, especially to provide means for comparing human and artificial intelligence and have a look to the learning capability related to it. publishedVersion

The ability of assessing any type of linguistic complexity of any given contents could potentially improve knowledge reproduction, especially tacit knowledge which can be expensive during a pandemic. In this paper, we develop a simple and crosslinguistic model of complexity which considers formal accounts on the study of linguistic systems, but can be easily implemented by non-linguists' groups, e.g., communication experts and policymakers. To test our model, we conduct a study on a corpus extracted from the World Health Organization (WHO)'s emergency learning platform in 6 languages. Data extracted from open-access encyclopaedic entries act as control groups. The results show that the measurements adopted signal a trend for a minimization of complexity and can be exploited as features for (automatic) text classification. publishedVersion

This paper presents a new software framework, SAMPO-UI, for developing user interfaces for semantic portals. The goal is to provide the end-user with multiple application perspectives to Linked Data knowledge graphs, and a two-step usage cycle based on faceted search combined with ready-to-use tooling for data analysis. For the software developer, the SAMPO-UI framework makes it possible to create highly customizable, user-friendly, and responsive user interfaces using current state-of-the-art JavaScript libraries and data from SPARQL endpoints, while saving substantial coding effort. SAMPO-UI is published on GitHub under the open MIT License and has been utilized in several internal and external projects. The framework has been used thus far in creating six published and five forth-coming portals, mostly related to the Cultural Heritage domain, that have had tens of thousands of end-users on the Web.

OpenWHO provides open access, online, free and real time learning responses to health emergencies. Before the pandemic, courses on 18 diseases were provided. The increase to 38 courses in response to COVID-19 have led to a massive increase in the number of new learners. As a result, the COVID-19 pandemic affected learners' trends. This paper presents initial findings of changes perceived in the use and user groups' attendance to the World Health Organization's (WHO) health emergency learning platform OpenWHO. Enrolment statistics were based on data collected in December 2019 and March 2021. A descriptive analysis was conducted to explore changes in the usage pattern of the platform. Several user characteristics shifted between before and during the pandemic. More women, younger and older learners joined the learning during the pandemic. Public health education leaned toward a more equitable reach including previously underrepresented groups. publishedVersion Non

pHealth is a data (personal health information) driven approach that use communication networks and platforms as technical base. Often it' services take place in distributed multi-stakeholder environment. Typical pHealth services for the user are personalized information and recommendations how to manage specific health problems and how to behave healthy (prevention). The rapid development of micro- and nano-sensor technology and signal processing makes it possible for pHealth service provider to collect wide spectrum of personal health related information from vital signs to emotions and health behaviors. This development raises big privacy and trust challenges especially because in pHealth similarly to eCommerce and Internet shopping it is commonly expected that the user automatically trust in service provider and used information systems. Unfortunately, this is a wrong assumption because in pHealth's digital environment it almost impossible for the service user to know to whom to trust, and what the actual level of information privacy is. Therefore, the service user needs tools to evaluate privacy and trust of the service provider and information system used. In this paper, the authors propose a solution for privacy and trust as results of their antecedents, and for the use of computational privacy and trust. To answer the question, which antecedents to use, two literature reviews are performed and 27 privacy and 58 trust attributes suitable for pHealth are found. A proposal how to select a subset of antecedents for real life use is also provided. publishedVersion

Reproduction of knowledge, especially tacit knowledge can be expensive during a pandemic. One of the most common causes is the reduced information accessibility during the translation process. Having the ability to assess the linguistic complexity of any given contents could potentially improve knowledge reproduction. Authors conduct two cross-linguistic studies on the World Health Organization (WHO)'s emergency learning platform to assess the linguistic complexity of two online courses in 10 languages. Morpho-syntactically annotated treebanks, unannotated materials from Wikipedia and language-specific corpora are set as control groups. Preliminary findings reveal a clear reduced complexity of learning contents in the most candidate languages while retaining the maximum amount of information. Creating a baseline study on low-resourced languages on the learning genre could be potentially useful for measuring impact of normative products at country and local level. publishedVersion

Accessibility, multilingualism and real-time knowledge transfer are the tenets of the OpenWHO learning platform. A descriptive analysis was conducted using anonymised statistical datasets retrieved from the OpenWHO reporting system to understand global use trends. When examining OpenWHO use in the areas with the highest burden of COVID-19 cases, a strong correlation was identified between the burden of COVID-19 and OpenWHO user activity. Further, health professionals are the top users of COVID-19 materials. The massive demand for OpenWHO courses confirms the need for real-time learning materials in accessible, multilingual formats during a pandemic. Learning is a global public good and is an essential component of the response to health emergencies. publishedVersion Non

The paper examines the Third Mission of universities from the point of view of company collaboration in the prototype development process. The paper presents an implementation of university-enterprise collaboration in prototype development described by means of process modeling notation. In this article, the focus is on modeling the software prototyping process in a research context. This research paper introduces prototype development in a university environment. The prototypes are made in collaboration with companies, which offered real-world use cases. The prototype development process is introduced by a modeling procedure with four example prototype cases. The research method used is an eight-step process modeling approach. The goal was to find instances of activity, artifact, resource, and role. The results of modeling are presented using textual and graphical notation. This paper describes the data elicitation, where the process knowledge is collected using stickers-on-the-wall technique, and the creation of the model is described. Finally, the shortcomings found in our existing practices and possibilities for improving our prototype development processes and practices are discussed. publishedVersion

Contrary to the prevailing view that robots cannot be full-blown members of the larger human moral community, I argue not only that they can but that they would be ideal moral agents in the way that currently counts. While it is true that robots fail to meet a number of criteria which some human agents meet or which all human agents could in theory meet, they earn a perfect score as far as the behavioristic conception of moral agency at work in our moral responsibility practices goes.

Data (conceptual, data, information, knowledge) modelling is still the work of an artisan, i.e. an art in the best case, made by humans, because of the need for human intelligence. Data modelling is an essential part of Information System (IS) design, specifying how data is implemented as part of an IS. The principles of data modelling follow the evolution of IS development paradigms, and these in turn follow the progress of technological changes in computing. Although technology has changed a lot during the decades of commercial use of computers – since the early 1950s to now, close to 70 years – data modelling is still based on the same basic principles as decades ago. Or is it really so? Finding the answer to this question was the main motivation to start writing this paper. Since the future is more interesting than the past, we set our research problem to be “What are the challenges for data modelling in the future?”. The reason for this is that we see some significant changes in the future in the data modelling sector which we wanted to examine. However, the future is a continuum of the past. The future cannot be fully understood without understanding the past. Humans also tend to forget the details of the past. Even the most remarkable innovations from the past have become part of the new normal. Consequently, at the beginning of our paper we look shortly at the progress of data modelling during the era of commercial computing. Our focus is on the recent past and we look at the technological changes that have been of key importance in data modelling in the role of triggers and enablers. To find the answer to our research question, we retrieved some recent studies handling the future of data modelling and analyse the challenges found in these sources. The paper is concluded by some future paradigms. In general, the big changes seem to be the growing importance of Artificial Intelligence (AI) and machine learning (ML) as its fuel. AI not only conducts algorithmic rule-based routines, it has learning capability, which makes it more intelligent and adaptable, and able to compete with human intelligence, even in data management tasks. publishedVersion

As social robots project socially interactive skills including speech and gestures, they are in a position to project normative practices that humans ordinarily rely upon in their everyday interactions with each other. Social robots enable experiences that are reducible to interaction as a normative practice, such as a sense of moral obligation to respond to a robot's greeting. This may have consequences both for the user experience and the design of social robots that are currently overlooked. We propose that theoretical-methodological tools from ethnomethodology should be applied to evaluate and investigate the experiences related to social interaction with social robots. acceptedVersion

In this article the focus is on software evolution, which is an important part of software engineering. In practice, software development does not stop when a system is delivered but continues throughout the lifetime of the system. After the system has been deployed, external pressure for change can generate new requirements for the existing software. This change aspect, which is a characteristic of software engineering, should be taken into consideration when developing and modeling new software systems. In this paper the theme was studied using experience gained from the piloting of a reference system developed in an earlier research project carried out by T ampere University of Technology. Software evaluation is examined from the point of view of system developers, administrators (maintenance), and end users based on a concrete long-term piloting period. submittedVersion

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Engaging youth in civic participation is essential for sustainable societies. Social robots, as embodied and interactive entities, may be feasible tools to spark youth’s interest. To start designing persuasive interactions for this purpose, we conducted a study addressing the question, what do youth consider as appropriate behaviour for a civic robot? We developed three scenarios describing social robots as persuaders for youth’s civic participation. The scenarios were evaluated in three workshops with 51 fifteen-year-old participants. The credibility of the robot emerged as a central theme: a civic robot should emphasize its purpose and avoid any pretence, also when expressing emotions. acceptedVersion

Today's digital information systems and applications collect every day a huge amount of personal health information (PHI) from sensor and surveillance systems, and every time we use personal computers or mobile phones. Collected data is processed in clouds, platforms and ecosystems by digital algorithms and machine learning. Pervasive technology, insufficient and ineffective privacy legislation, strong ICT industry and low political will to protect data subject's privacy have together made it almost impossible for a user to know what PHI is collected, how it is used and to whom it is disclosed. Service providers' and organizations' privacy policy documents are cumbersome and they do not guarantee that PHI is not misused. Instead, service users are expected to blindly trust in privacy promises made. In spite of that, majority of individuals are concerned of their privacy, and governments' assurance that they meet the responsibility to protect citizens in real life privacy is actually dead. Because PHI is probably the most sensitive data we have, and the authors claim it cannot be a commodity or public good, they have studied novel privacy approaches to find a way out from the current unsatisfactory situation. Based on findings got, the authors have developed a promising solution for privacy-enabled use of PHI. It is a combination of the concept of information fiduciary duty, Privacy as Trust approach, and privacy by smart contract. This approach shifts the onus of privacy protection onto data collectors and service providers. A specific information fiduciary duty law is needed to harmonize privacy requirements and force the acceptance of proposed solutions. Furthermore, the authors have studied strengths and weaknesses of existing or emerging solutions. publishedVersion

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Humankind faces a most crucial mission; we must endeavour, on a global scale, to restore and improve our natural and social environments. This is a big challenge for global information systems development and for their modelling. In this paper, we discuss on different aspects of conceptual modelling in global environmental context. The paper is the summary of the panel session “The Future of Conceptual Modelling” in the 29th International Conference on Information Modelling and Knowledge Bases. peerReviewed

Governments publish legislation and case law widely in print and on the Web. Such legal information is provided for human consumption, but the information is usually not available as data for algorithmic analysis and applications to use. However, this would be beneficial in many use cases, such as building more intelligent juridical online services and conducting research into legislation and legal practice. To address these needs, this Chapter presents Semantic Finlex, a national in-use data resource and service for publishing Finnish legislation and related case law as Linked Open Data for legal applications to use. The system transforms and interlinks on a regular basis data from the legacy legal database Finlex of the Ministry of Justice into Linked Open Data, based on the European standards ECLI and ELI. The published data is hosted on the '7-star' Linked Data Finland service and SPARQL endpoint with a variety of related services available that ease data re-use. Rich Internet Applications using SPARQL for data access are presented as application demonstrators of the data service. In addition, this Chapter presents methods and tools under development to automatically annotate legal texts and to anonymize case law documents prior to their publication on the Web. Anonymization is necessary due to issues of data protection and privacy, and annotation is needed for semantic search and interlinking the documents. The automated approaches could significantly speed up the process and minimize costs of publishing legal documents as Linked Open Data.

Patient experience (PX) is an important evaluation criterion for quality in healthcare. Compared to patient satisfaction, however less research has focused on the development of instruments to measure experiences of patients and their families. In the article, we describe the process of developing a PX questionnaire for the parents of pediatric patients in the context of children's hospital and illustrate the questionnaire items for measuring PX. The phases of the development process included retrospective interviews, description of the themes influencing PX and the metrics for measuring PX, as well as iterative development of three versions of questionnaires including data gathering and factor analysis. The final versions of the surveys suggested for implementation at the hospitals include eight PX statements for the outpatient clinic and five statements for the ward. Compared to satisfaction surveys, the developed surveys emphasize the aspects of parent's attitude towards the illness, support for families, and daily arrangements with a child patient.

As information systems are producing vast amounts of data with ever increasing speed and diversity, the management of data is becoming an important part of gaining the information that we need. With this as the motivation, this paper proposes a Manageable Data Sources framework for the systematic management of data sources. The framework is derived from a new conceptual model of data processing: The Faucet-Sink-Drain model. The framework achieves two aims: The unification of data processing, and secondly, the componentization and decoupling of data processing related tasks. The framework is described and a reference architecture is laid out for the creation of a proof-of-concept implementation to solve the given use case. acceptedVersion

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.

Modelling is an essential part of information systems development. Models are used for communication between interest groups and inside development teams. Models are also used for transferring baseline artefacts between development phases. Models are mainly developed by humans, which represent certain cultures - national, enterprise, professional, team, project etc. Because of that we claim that models, as well as many other information systems related artefacts are culture dependent. The models are born in certain context and these must be also interpreted by taking the original context into account. In our earlier studies we have analysed the effect of culture in information systems development: culture related aspects in general level, in information search and interaction and in web information systems. We focus now on modelling. Because of that we shortly answer to the question “How cultures differ from each other”. This reviews and synthesis generally accepted frameworks for cultural analysis. In addition we shortly open the results of our earlier studies. Because modelling is a human activity, as well as information systems are used by humans, we integrate the use context into information systems development. The findings of culture analysis are transferred to modelling practices via our framework that defines model as an instrument transferring elements of its development context to the models – we discuss the roles of normal models, deep models and modelling matrix. Finally we will concentrate on the problems of cross-cultural modelling using selected national cultures as an example. acceptedVersion

A clean environment is often taken for granted, but when a river or a lake becomes polluted, it might be hard for the general public to verify the condition. A simple visualization tool for checking the condition of water could help to inform the public and help to increase environmental awareness. With the emergence of Open Data and other openly available data sources, it is possible to create new and innovative applications. In this paper we present a web-based tool for reviewing the quality of water by applying the River Heavy Metal Evaluation Index (rHMEI) method together with open data on water quality in Finland. publishedVersion

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Proceeding volume: 285