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Cooperative knowledge spaces create new potentials for the experimental fields in natural sciences and engineering because they enhance the accessibility of experimental setups through virtual laboratories and remote technology, opening them for collaborative and distributed usage. A concept for extending existing virtual knowledge spaces for the means of the technological disciplines (“ViCToR‐Spaces” ‐ Virtual Cooperation in Teaching and Research for Mathematics, Natural Sciences and Engineering) is presented. The integration of networked virtual laboratories and remote experiments (“NanoLab Approach”), as well as an approach to community‐driven content sharing and content development within virtual knowledge spaces (NanoWiki) are described.

Linking Open Data (LOD) provides a vast amount of well structured semantic information, but many inconsistencies may occur, especially if the data are generated with the help of automated methods. Data cleansing approaches enable detection of inconsistencies and overhauling of affected data sets, but they are difficult to apply automatically. The purpose of this paper is to present WhoKnows?, an online quiz that generates different kinds of questionnaires from DBpedia data sets.

Besides its playfulness, WhoKnows? has been developed for the evaluation of property relevance ranking heuristics on DBpedia data, with the convenient side effect of detecting inconsistencies and doubtful facts.

The original purpose for developing WhoKnows? was to evaluate heuristics to rank LOD properties and thus, obtain a semantic relatedness between entities according to the properties by which they are linked. The presented approach is an efficient method to detect popular properties within a limited amount of triples. Ongoing work continues in the development of sound property ranking heuristics for the purpose of detecting the most relevant characteristics of entities.

WhoKnows? uses the approach of “Games with a Purpose” to detect inconsistencies in Linked Data and score properties to rank them for sophisticated semantic search scenarios.

The purpose of this paper is to discuss researcher subjectivity in social entrepreneurship ethnographies. Previous research has highlighted a need for alternatives to the heroic representations of social entrepreneurship. Ethnographic methods have been mentioned as a relevant direction to create such emerging understandings.

This paper shows what followed from a decision of a researcher to do an ethnography of a co-working cooperative established for social innovation. Based on the notion of “working the hyphens” in previous research, further developed by other scholars as “working within hyphen-spaces”, the position of the researcher shifted during the research process between a distant outsider and an engaged insider. In addition, a new hyphen-space of hopefulness – hopelessness emerged based on fieldwork.

The shifting positions are manifested in the entanglement of stories of the researcher and the people met during the fieldwork in the hyphen-spaces of insiderness – outsiderness, engagement – distance and hopefulness – hopelessness. The stories reveal how for some the co-working space was a place for hope while for others it caused distress and even burnout.

The ethnographic understanding of social enterprises go beyond heroic representations, which affects how the phenomenon is represented in academic and public discussions.

This study concludes that despite its failure in the form of a bankruptcy, the co-working cooperative succeeded in enabling “social innovation” in the form of hope and personal development – also for the researcher.

This study contributes to the social entrepreneurship literature in showing how ethnographic fieldwork and acknowledging researcher subjectivity bring up alternative representations of social entrepreneurship. The entangled stories of participants and researchers can be a powerful way to reveal situated understandings.

This paper aims to study how activists involved in consumer-initiated cooperatives, in a specific context, challenge the practices of the neoliberal system and develop counter-practices that are ingrained with their values. It aims to access the transformative capacity and inclusiveness of consumer-initiated cooperatives and the role played by prefigurative practices in changing the status quo. Three practices – defetishization of agricultural commodities, surplus generation and distribution, prefiguration – that enable the inclusion of those groups who are marginalized in the food production and consumption nexus by neoliberal policies are identified.

The findings of this paper were developed from 23 unstructured interviews, participant observation and analysis of the social media accounts of five consumer-initiated cooperatives located in different districts of Istanbul and which are involved in a collective response to the neoliberal policies.

The study discusses that, in a specific context, political events and economic policies can be a catalyst for the initiation of alternative consumer-initiated cooperatives. The findings indicate that these organizations can develop and articulate prefigurative practices that are influential in transforming the prevailing capitalist food provisioning system to be more inclusive.

The findings offer an alternative view to the dominant capitalist logic and advance the concept of how the economic sphere can be re-politicized and how the persevering notion of financial performance is resolved by invoking values of inclusion, solidarity, responsibility and sharing. The findings are based on the study of five cases in a specific context during a specific period.

This paper focuses on cooperatives owned and governed by activist consumers and presents results concerning their underlying practices for creating a food provisioning system that is inclusive and aiming for social justice and equality. Similarly, it provides evidence of how local political and economic conditions influence the appropriation and development of these practices – commodity defetishization, surplus distribution and prefiguration.

Purpose: To examine the refugee women's empowerment and integration component of the pilot program of a Turkish social entrepreneurial organization (SEO) specialized in supporting disadvantaged women's empowerment. Methodology/Approach: The chapter utilizes a comparative qualitative case study approach to investigate the interplay between the dimensions of: business model, knowledge acquisition, and learning experiences, the achievement of goals, and scalability in determining social innovations. Findings: Despite the widespread belief that women's cooperative is an ideal business model for inclusivity, the chapter presents a variance in achieving this goal. The results propose that a strong business model, enhanced with knowledge acquisition and learning, and an inclusive approach to innovation, enable a women's cooperative to offer desirable solutions to community needs, improving its chances for higher impact. Research Limitations/Implications: The chapter adds to social entrepreneurship literature by offering multilevel analysis in examining social innovation, which has been often neglected as a research approach in the field. It asserts that an investigation into the community as a unit of analysis promises to be viable research in social innovation studies. Practical Implications: An inclusive approach that develops relations with the broader community and networking with other cooperatives and social actors is essential for women's cooperatives. Social Implications: The SEO's increasing local reach and impact have made it a strong actor in women's empowerment on the ground and force for institutional change. In the long term, SEOs' actions targeting multiple actors of influence will increase the chances of suggested framework changes accepted by policymakers.

On-orbit service technology is one of the key technologies of space manipulation activities such as spacecraft life extension, fault spacecraft capture, on-orbit debris removal and so on. It is known that the failure satellites, space debris and enemy spacecrafts in space are almost all non-cooperative targets. Relatively accurate pose estimation is critical to spatial operations, but also a recognized technical difficulty because of the undefined prior information of non-cooperative targets. With the rapid development of laser radar, the application of laser scanning equipment is increasing in the measurement of non-cooperative targets. It is necessary to research a new pose estimation method for non-cooperative targets based on 3D point cloud. The paper aims to discuss these issues.

In this paper, a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose (position and attitude) of the spatial non-cooperative target. First, we need to preprocess the obtained point cloud to reduce noise and improve the quality of data. Second, according to the features of the satellite, a recognition system used for non-cooperative measurement is designed. The components which are common in the configuration of satellite are chosen as the recognized object. Finally, based on the identified object, the ICP algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose estimation.

The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching points. The recognition of components on non-cooperative spacecraft directly contributes to the space docking, on-orbit capture and relative navigation.

Limited to the measurement distance of the laser radar, this paper considers the pose estimation for non-cooperative spacecraft in the close range.

The pose estimation method for non-cooperative spacecraft in this paper is mainly applied to close proximity space operations such as final rendezvous phase of spacecraft or ultra-close approaching phase of target capture. The system can recognize components needed to be capture and provide the relative pose of non-cooperative spacecraft. The method in this paper is more robust compared with the traditional single component recognition method and overall matching method when scanning of laser radar is not complete or the components are blocked.

This paper introduces a new pose estimation method for non-cooperative spacecraft based on point cloud. The experimental results show that the proposed method can effectively identify the features of non-cooperative targets and track their position and attitude. The method is robust to the noise and greatly improves the speed of pose estimation while guarantee the accuracy.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.