Keywords

Introduction

Many of the existing definitions of the collaborative economy refer to efficient access to underused goods and spaces making use of the internet and reputation systems (Sundarajan 2016). Schor (2014) speaks about recirculation of goods, increased utilisation of durable assets, exchange of services, sharing of productive assets and building of social connections. When attempting to apply such definitions to education, data and knowledge sharing, we are faced with difficulties. Benkler’s (2004) approach that refers extensively to community building, social relationships, altruism, sustainable lifestyles and non-monetary exchanges as the main drivers of sharing or collaborative economies constituted for us a more appropriate context. In their discussion of the Sharing Economy, Schor et al. (2016, p. 75) refer to open learning as a practice ‘that uses free or low-cost educational resources that are typically open access, peer-led, shareable, and digitally mediated’. The MOOCs (Massive Online Open Courses) discussed in this chapter, as well as a wide range of educational activities mediated by online platforms and open to large categories of the public, can be seen as open learning opportunities. Regarding both formal and nonformal education, there are a number of educational platforms widely used, such as Khan Academy, Udacity, Coursera, Skillshare, LinkedIn Learning, Udemy, Codecademy, and edX, that benefit students from all over the world. The attractivity of these platforms is enhanced by general accessibility and the quality of the user experience offered. Nevertheless, a problematic aspect is potential commercial, social, and political influences that could introduce a bias in educational content. Aspects related to incorporating case studies, data and other content belonging to former students in the new versions of a course raise questions regarding the intellectual ownership of this content. Also, data analytics are used to improve the sequence and automate further the delivery often without enough attention given to obtaining the students’ consent to participate in research, and their privacy, identity, and anonymity (Marshall 2014). These other priorities need to be clearly communicated to prospective students.

In this chapter, we prioritise the group of initiatives focusing on social innovation and striving for more sustainable economic and environmental models based on sharing access to goods and services, which have been the focus of our Sharing and Caring COST Action (Sharing and Caring 2021), while looking at how open education and knowledge sharing can be seen as part of the collaborative economy. These domains are not among the frequently discussed examples of collaborative economy initiatives; however, learning objects, knowledge, and skills are particularly important intangible assets in today’s digital economy and are at the basis of a whole range of evolving services. The following sections of this chapter are dedicated to collaborative developments in education, including examples of open education and shared resources in Europe, as well as knowledge and data sharing via open and inclusive approaches, providing examples of local European initiatives. We examined the Sharing and Caring COST Action collection of country reports (Klimczuk, Česnuitytė, and Avram 2021) and more than 130 short stories available on the Sharing and Caring website (Sharing and Caring 2021) and included a series of examples from the countries participating in the COST Action. Finally, the chapter offers a reflection on the particularities of these activities from the perspective of the sharing economy.

Collaborative Developments in Education

The use of open educational resources (OER)—that are freely licensed and remixable learning resources, has increased in the last decade, mainly due to the abundance of user-generated content and new types of content licensing such as Creative Commons. Open Educational Practices (OEP) are also evolving, supporting the opening and sharing of educational processes, and new collaborations between students and lecturers emerge, with the goal of improving access and empowering learners (Cronin and MacLaren 2018). New formats, such as open, connected courses (enabling students to connect with students and educators in other institutions and countries) and co-creation of open textbooks with students (Stagg and Partridge 2019), are also evolving. The learning theory promoted by George Siemens (2005) and Stephen Downes (2010) titled ‘connectivism’ looks at learning that takes place online across peer networks. Technologies such as web browsers, email, wiki, blogs, online forums, social networks, education games, platforms such as YouTube and Vimeo enable users to learn together and from each other and to share information with peers. A key feature of connectivism is that much learning can happen across peer networks that connect online. In line with the knowledge and skills gained through online learning and education, social learning and interaction are seen as important components of the educational framework. As Downes (2014) stated, applications and environments in social learning include: collaborative (wiki-style document authoring); cooperative (social sharing of bookmarks and resources); and competitive (games and contests) learning. Siemens and Downes were the creators of the first MOOC—Connectivism and Connected Knowledge, that was offered at the University of Manitoba in 2008 (Hollands and Devayani 2014). This type of MOOC is ‘based on the idea that learning happens within a network, where learners use digital platforms such as blogs, wikis, social media platforms to make connections with content, learning communities and other learners to create and construct knowledge’ (Siemens 2012).

A couple of years later (2011), several famous universities such as Harvard, MIT and Stanford started online courses based on a traditional classroom structure, including pre-recorded video lectures and assessments (quizzes, tests, projects). These are usually centred around a teaching team rather than around an open community of learners. The Stanford-style MOOCs were designed to scale education originally offered face-to-face. Also, research undertaken in parallel with running these courses focused on structuring and sequencing efficiently the transmission of knowledge. The initial idea behind this offering was creating a global service by bringing in people that were until then excluded from higher education and turning them into online learners at some of the world’s best universities (Reich and Ruipérez-Valiente 2019). But in the end, these courses attracted mainly learners from well-off countries and neighbourhoods, who were using these courses to complement their education. To help distinguish between the two educational approaches, the terms ‘cMOOC’ and ‘xMOOC’ were coined, ‘c’ denoting the focus on connectivism and ‘x’ denoting exponential, focusing on the massive enrolments, or extension (Hollands and Devayani 2014). The use of the term open in MOOC is often disputed, as the content of xMOOCs is seldom open reusable content licensed under Creative Commons. More often than not, the content is strictly copyrighted. Although in the beginning, participation in such courses was completely free, in time, platforms such as Coursera, edX, FutureLearn and Udemy have started charging for certificates. Another important set of aspects of xMOOCs that were addressed by researchers is related to ethical issues. Back in 2012, when Harvard first got involved in MOOCs by developing the MOOC platform edX, its president was quoted in a press release stating that the purpose for doing so was to extend its reach by conducting research into effective education (Marshall 2014). This way, he made clear that beyond the generous offer of elite university courses to anyone on the planet with good use of the English language and Internet access, the university’s strategic goal was to build a better understanding of e-learning.

In Europe, Goldie (2016) examined the role of MOOCs, emphasising the role played by the European Commission in advocating open education through the use of MOOCs. Following this, a group of European Universities partnered and launched the Openup Ed initiative in 2013. Openup Ed focuses on online courses for large numbers of participants, courses that can be accessed by anyone anywhere via the Internet, open to everyone and offering a full course experience for free. Although based in Europe, Openup Ed has an international scope. The courses offered are hosted on various platforms.

Eshach (2007) created a taxonomy of education/learning types that can prove relevant when examining open education. Eshach distinguished the following three types: formal education, taking place mainly through the national education system, and including both academic studies and full-time specialised professional training; any organised educational activity happening outside the established education system, initiated for specific target groups, and having concrete learning objectives is categorised as nonformal education. Finally, the lifelong process of acquiring knowledge, skills, attitudes, and values in one’s environment, without the express intention to learn, is termed as informal education. E-learning platforms offer both formal education (as in the cases of Coursera, edX, Udacity) and nonformal education/courses (the case of LinkedIn Learning, Instructables, Adobe, etc.). On the other side, informal learning happens daily and spontaneously when users check information on Wikipedia, consult YouTube or Vimeo user-generated content on a specific topic or ask questions on platforms such as Quora or Reddit. On the other hand, Reich (2020) considers three models of online learning: (1) MOOCs, where learning is guided by a human instructor (or team of instructors) following a set sequence; (2) Algorithm-led learning—where learners are assessed by software, and the sequence of lessons is reorganised automatically (Khan Academy) and (3) Peer-guided learning, or networked environments learning, where the learners guide each other or learn from each other, like in the case of Do-It-Yourself (DIY) forums, crafts circles or sports group enthusiasts.

In today’s world, the reach of e-learning platforms is going far beyond MOOCs. E-learning platforms are the mechanism that supports the sharing of diverse learning content with users, the gathering of learning analytics and the refinement of the content and sequence based on the users’ response in a wide range of organisations, such as universities, specialised training companies, communities and large companies looking to train their staff or customers. During the COVID-19 pandemic, not only university education but also primary and secondary school activities, as well as numerous nonformal courses, were forced to shift online. Those institutions that already had an effective digital platform for either complementing face-to-face learning activities or for providing blended or fully online tuition were advantaged, as they were able to pivot online quickly and efficiently. Table 9.1 presents a selection of the most popular educational platforms in use worldwide.

Table 9.1 Educational Platforms
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Another concept based on sharing resources and large-scale collaboration is that of Open Science, seen as a movement seeking to ‘leverage new practices and digital technologies to increase transparency and access in scholarly research’ (van der Zee and Reich 2018, p. 2). Based on Open Science, van der Zee and Reich propose a framework for Open Education Science, including Open Access to publications, Open Design of educational resources and pedagogy, Open Data for collecting data on the outcomes, and Open Analysis for analysing the results. The idea of collaborative teaching and learning as peer learning and peer production also appears in the Peeragogy Project, initiated by Howard Rheingold in 2012 (Corneli et al. 2016). All these developments in education are supported by digital platforms and are based on sharing resources such as content, practices, and analytics, with or without financial incentives. Besides these educational platforms and initiatives, the Sharing and Caring COST Action also revealed a series of examples of networks and platforms from the participating countries in Europe and beyond that assist people to share knowledge and skills with each other, many using a digital platform and some also centred around a physical meeting place that is presented below in Table 9.2.

Table 9.2 Examples of open education and shared resources in Europe
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Knowledge Sharing via Open and Inclusive Approaches

Besides education, there are other domains that benefitted heavily from the emergence of digital platforms and the opportunity of sharing information across the globe. Benkler (2004) introduced the term ‘shareable goods’ and illustrated his ‘commons-based peer production’ concept, seen as a large-scale cooperative effort in which what is shared among the participants is their creative effort, building on the example of Open-Source Software development communities. Benkler and Nissenbaum (2020, p. 70) stated that ‘socio-technical systems of commons-based peer production offer not only a remarkable medium of production for various kinds of information goods, but also serve as a context for positive character formation’. Inspired by the Open-Source Software movement, the Wikipedia project started in 2001 and demonstrated the potential of global collaboration in creating a free and open encyclopaedia that could be delivered ‘to every single person on the planet in their own language’ (Cohen 2008). Several other projects followed, such as OpenStreetMap (an open maps collaboration space), Quora (a questions and answers platform), Instructables (a space for sharing step-by-step instructions for DIY projects), Open Plaques (a crowdsourced collection of information on historical commemorative plaques), and WikiVoyage (a crowdsourced travel guide for travel destinations written by volunteers), to name but a few.

One of the domains that received a strong boost from the open global collaboration is innovation. As digital platforms offer a suitable environment for value creation and sharing, new open and distributed models of innovation emerged (Nambisan et al. 2018). Collaborative innovation has become a global trend, involving multiple stakeholders who engage in non-copyrighted innovation and create new solutions and technologies using open, collaborative platforms (Biasin and Kamenjasevic 2019), open to companies and individuals, creating new business models.

The open design movement focuses on developing physical products, machines, and systems by making use of publicly shared design information. Within this movement, one trend sees volunteers coming together and donating their time and skills working on projects for the common good—either because funding is lacking, or because there is not sufficient commercial interest, or for helping developing countries, promoting environmentally friendly or cheaper technologies (Pearce et al. 2010). A second trend is bringing together people and resources from different companies and countries for developing advanced projects and technologies that would be beyond the resources of any single company. Another trend involves the use of high-tech open-source solutions developed globally that is further adapted to respond to solving local challenges in a sustainable manner, sometimes labelled as ‘Design Globally, Manufacture Locally’. Schismenos et al. (2020) see this trend as being a new form of egalitarian and transnational collaborative networks (that they label as ‘cosmo-localism’), which could challenge the core values of capitalism and invite to further reflection going beyond its effects on production and distribution. These digital platforms provide the necessary infrastructure for individuals and organisations to share ideas online, work on joint projects and co-create products working together, supporting collaborative innovation that happens online (Biasin and Kamenjasevic 2019).

In order to illustrate the variety of digital platforms supporting online collaboration and co-creation worldwide, we include here a series of examples. For instance, AguaClara is an engineering group at Cornell University publishing an open-source design tool and CAD designs for water treatment plants (AguaClara 2021), while Open Source Ecology (OSE) is a network comprising of farmers, engineers, architects, and supporters. The main goal of OSE is manufacturing a so-called Global Village Construction Set (GVCS), an open technological platform that will allow the fabrication of 50 types of industrial machines that would be necessary for ‘building a small civilisation with modern comforts’ (Open Source Ecology 2021). In a different vein, Wikispeed is an automotive manufacturer that produces modular design cars. The project participants apply scrum development techniques borrowed from the software world. They use open-source tools and lean management methods to improve productivity (Wikispeed 2021). In addition, focusing on 3D printing technology, some knowledge sharing projects such as e-NABLE and Thingiverse allow the dissemination of creativity outcomes online. e-NABLE is a global network of volunteers who are using their 3D printers, design skills, and personal time to create free 3D printed prosthetic hands for those in need—with the goal of providing them to underserved populations around the world (e-NABLE 2021). With a more general scope, Thingiverse is a platform dedicated to the sharing of user-created digital design files that provides mainly free, open-source hardware designs licensed under the GNU General Public License or Creative Commons licenses. Each contributor can select a user license type for the designs that they share. The digital blueprints shared can be used for creating physical objects using 3D printers, laser cutters, milling machines and other technologies. The platform is widely used by DIY enthusiasts and communities as a repository for shared innovation and dissemination of source materials to the public (Thingiverse 2021).

Knowledge sharing between various stakeholders, as Biasin and Kamenjasevic (2020) pointed out, is the common denominator across these kinds of platforms. Users and communities are enabled to collaborate online by using the advantages of new digital technologies. Open knowledge sharing contributes to the spread of designs and project ideas worldwide. However, some of the Open-Source projects, especially the ones related to open hardware, could face a few legal challenges. These are related mainly to privacy and data protection, as data are being widely shared and manipulated, and to intellectual property rights, which can be complicated when participants reside in various countries and work for different organisations. Another complex issue is a liability—who will be responsible for the malfunctioning of an open-source car, water installation, or prosthetic? Table 9.3 presents a selection of open and inclusive sharing initiatives identified by the participants in the Sharing and Caring COST Action.

Table 9.3 Examples of open and inclusive sharing initiatives in Europe
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In this type of community, knowledge is offered freely for mutual benefit. It is also difficult to quantify individual contributions, making knowledge sharing a different type of transaction. This category sees the production of so-called ‘information goods’ (Benkler 2004) that are going into the design of both physical and digital products. Value is created from collaboration and synergy. Learning and community building are side effects of the collaboration, mirroring the ethos of the early days of Open-Source Software projects. Such collaboration projects supported by online platforms are enhancing resilience all around the globe, providing a solution to a wide range of problems. In difficult times—such as natural disasters, pandemics, conflict—this kind of project take off rapidly based on existing experience. One example is the Coronavirus Tech Handbook, initiated in the early weeks of the pandemic at Newspeak House, a London hackerspace, that received rapid contributions from thousands of volunteers (Maddyness 2020). The handbook is a library of tools, services and resources relating to the COVID-19 response that was crowdsourced. The site, launched in March 2020, is hosted as an interlinked collection of user-editable online documents allowing frequent updates.

Open and inclusive knowledge sharing initiatives facilitated by online platforms are stimulating innovation and allow individuals and communities with similar interests to find each other and work together. The role and importance of these activities have become even more prominent during the COVID-19 pandemic. Information, skills and competencies are shared locally and globally with notable results.

Platforms Facilitating Collaborative Information Production and Consumption

The European Commission sees data-driven innovation as a ‘key enabler of growth and jobs in Europe (European Commission 2018, p. 1). Data sharing is seen by the Commission as an economic activity. Richter and Slowinski (2019) point out the absence of a generally accepted definition when it comes to data sharing. The term ‘sharing’ involves a benign connotation and makes a connection to the ‘sharing economy’. Based on defining the sharing economy as ‘the more efficient use of resources – mostly products and services – as a consequence of a technically enabled reduction of transaction costs’ (Richter and Slowinski 2019, p. 8) and on considering ‘data sharing’ as virtually all sorts of data flows between companies, with customers and even within companies—the perspective of the EU Commission (2018), the focus is put on sharing platforms as (third-party) enablers for sharing data. Access to information stored in digital datasets plays a major role in both societal development and the well-being of citizens. The possibilities of data-driven innovation based on machine learning and other technologies are based on the availability of extensive datasets for training the algorithms (Richter and Slowinski 2019). Lately, several citizen initiatives have started to explore how citizens could harness the value of their personal data themselves. We focus here on peer-to-peer data sharing and data sharing initiatives that rely on crowdsourcing. While in a lot of such data initiatives, there are no financial incentives, there are specific examples where individuals come together to form cooperatives and harness the economic value of data for the benefit of members.

Patients LikeMe, a private venture, started as an initiative persuading patients with rare conditions to donate their data for the use of professional medical researchers to help research progress faster. New European initiatives such as MiData (van Velthoven et al. 2019) raise awareness on the value of personal health data and encourage individuals to join forces in a cooperative so that they can be the ones who decide how their data is being used. Salus, is a citizen data cooperative based in Spain and focused on legitimising the right of citizens to maintain control over their own data while being able to facilitate data sharing to accelerate research and innovation in the health sector.

Citizen science projects invite the public to contribute the data they collect following specific guidelines to large-scale projects (Riesch and Potter 2014). While science should respond to citizens’ concerns and needs, the citizens themselves must be able to produce reliable scientific knowledge. In this case, the peer-to-peer relationship is replaced with the centralisation of data for the general benefit of science. When the data collected is aggregated, analysed, and shared for the benefit of the public, a virtuous cycle is created, encouraging sustained participation. Reporting invasive species (Schade et al. 2019) is an activity that was made more attractive and accessible using smartphone applications that support both identification and geographic localisation of reports. An initiative that allowed citizens to map the noise levels data over a period in a specific area using a Smart Citizen kit was seen as useful for requesting a revision of legislation for bars and cafes (Balestrini et al. 2015). Another example of data crowdsourcing that benefits the wider community is citizen sensing and reporting projects that focus on air quality that complement the official sources of information (Wesseling et al. 2019). Many such projects are the result of grassroots initiatives, where contributors are sharing data with each other and also publicly. Table 9.4 presents a selection of data sharing initiatives revealed by participants in the Sharing and Caring COST Action.

Table 9.4 Examples of data sharing initiatives in Europe
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Data sharing is by no means a new activity. However, examining data sharing from the perspective of the sharing economy has the advantage of revealing the importance of data as a resource in both peer-to-peer exchanges and transactions involving third parties.

Summary

The activities included in this chapter: sharing education resources, knowledge and data, are seldom mentioned as being part of the sharing economy. Sharing intangible digital resources such as learning resources, domain knowledge and huge quantities of data—from personal data to analytics and sensor-generated data—have become the norm in today’s world. According to the definition of the digital sharing economy elaborated by Pouri and Hilty (2021, pp. 129–130), the resources we discussed in this chapter qualify as durable immaterial goods, including ‘durable information and competencies’—when examined from the shareable resources’ perspective. With regard to the sharing practices, there are a variety of models employed. Initially, access to MOOCs was free, in principle ‘without reciprocity or compensation’ (Pouri and Hilty 2021, p. 131). However, both the content of students’ assignments and learning analytics were used to improve successive versions of both the learning resources and pedagogic practices. In open knowledge sharing communities, participants contribute time, competencies and information without reciprocity or compensations. Where companies get involved in such communities, they usually support the digital infrastructure and offer premium access as a way to monetise content (as in the case of Instructables).

In all three domains presented in this chapter, open education, knowledge and data sharing, the role of online platforms is paramount. These types of sharing are made possible and facilitated by the platforms that set the terms of collaboration and support coordination in all these cases. Given the immaterial nature of the goods being shared, the inclusion of these exchanges in the sharing economy is disputed by many authors (see, for example, Frenken et al. 2015). Instead of dealing with idle capacity, these resources are highly shareable, and besides the direct creation of new services and products, they contribute to creating community, increasing social capital, and contributing to the common good. In all these cases, re-use, scaling, peer production, and consumption are made possible by the existence of digital platforms as a coordination mechanism.