<p>This thesis explores the concepts of crowdsourcing and the ability of diversity, applied to optical mine detection. The idea is to use the human eye and wide and diverse workforce available on the Internet to detect mines, in addition to computer algorithms.</p><p>The theory of diversity in problem solving is discussed, especially the Diversity Trumps Ability Theorem and the Diversity Prediction Theorem, and how they should be carried out for possible applications such as contrast interpretation and area reduction respectively.</p><p>A simple contrast interpretation experiment is carried out comparing the results of a laymen crowd and one of experts, having the crowds examine extracts from hyperspectral images, classifying the amount of objects or mines and the type of terrain. Due to poor participation rate of the expert group, and an erroneous experiment introduction, the experiment does not yield any statistically significant results. Therefore, no conclusion is made.</p><p>Experiment improvements are proposed as well as possible future applications.</p> / <p>Denna rapport går igenom tanken bakom <em>crowdsourcing</em> och mångfaldens styrka tillämpad på optisk mindetektering. Tanken är att använda det mänskliga ögat och Internets skiftande och varierande arbetsstyrka som ett tillägg för att upptäcka minor tillsammans med dataalgoritmer.</p><p>Mångfaldsteorin i problemlösande diskuteras och speciellt ''Diversity Trumps Ability''-satsen och ''Diversity Prediction''-satsen och hur de ska genomföras för tillämpningar som kontrastigenkänning respektive ytreduktion.</p><p>Ett enkelt kontrastigenkänningsexperiment har genomförts för att jämföra resultaten mellan en lekmannagrupp och en expertgrupp. Grupperna tittar på delar av data från hyperspektrala bilder och klassifierar andel objekt eller minor och terrängtyp. På grund av lågt deltagande från expertgruppen och en felaktig experimentintroduktion ger inte experimentet några statistiskt signifikanta resultat, varför ingen slutsats dras.</p><p>Experimentförbättringar och framtida tillämpningar föreslås.</p> / Multi Optical Mine Detection System

This thesis explores the concepts of crowdsourcing and the ability of diversity, applied to optical mine detection. The idea is to use the human eye and wide and diverse workforce available on the Internet to detect mines, in addition to computer algorithms. The theory of diversity in problem solving is discussed, especially the Diversity Trumps Ability Theorem and the Diversity Prediction Theorem, and how they should be carried out for possible applications such as contrast interpretation and area reduction respectively. A simple contrast interpretation experiment is carried out comparing the results of a laymen crowd and one of experts, having the crowds examine extracts from hyperspectral images, classifying the amount of objects or mines and the type of terrain. Due to poor participation rate of the expert group, and an erroneous experiment introduction, the experiment does not yield any statistically significant results. Therefore, no conclusion is made. Experiment improvements are proposed as well as possible future applications. / Denna rapport går igenom tanken bakom crowdsourcing och mångfaldens styrka tillämpad på optisk mindetektering. Tanken är att använda det mänskliga ögat och Internets skiftande och varierande arbetsstyrka som ett tillägg för att upptäcka minor tillsammans med dataalgoritmer. Mångfaldsteorin i problemlösande diskuteras och speciellt ''Diversity Trumps Ability''-satsen och ''Diversity Prediction''-satsen och hur de ska genomföras för tillämpningar som kontrastigenkänning respektive ytreduktion. Ett enkelt kontrastigenkänningsexperiment har genomförts för att jämföra resultaten mellan en lekmannagrupp och en expertgrupp. Grupperna tittar på delar av data från hyperspektrala bilder och klassifierar andel objekt eller minor och terrängtyp. På grund av lågt deltagande från expertgruppen och en felaktig experimentintroduktion ger inte experimentet några statistiskt signifikanta resultat, varför ingen slutsats dras. Experimentförbättringar och framtida tillämpningar föreslås. / Multi Optical Mine Detection System

Introduction: From the start-up, the Internet has allowed easier, cheaper and more widespread communication between different parties. New ways in conducting business have emerged thanks to the Internet, such as Crowdsourcing. Crowdsourcing makes an open call to a group of peers, where the peers contribute to a final product. However, motivating these peers could be troublesome. Thus, there is a question in how to engage a crowd to participate in Crowdsourcing in order to create some sort of exchange to strive for a mutually beneficial relationship that makes the crowd willing to participate in Crowdsourcing. Purpose: The purpose of this study is to find how different motivating factors affect Participation in explicit Crowdsourcing. Methods: The design of the research conducted in this thesis was a quantitative survey that investigated motivating factors for the members of the company Company X. The survey was sent out threw Company X own site to their members and there were 82 complete answers collected. However, only 73 questionnaires were analyzable due to previous participation. The results gathered from the survey were analyzed with the help of seven hypotheses. Results: Monetary Awards, the Challenge of Problem Solving, and Peer Pressure were found to have a positive effect on Participation. Attention, Recognition, and the Ability of completing a Problem Solving process indicated that there are tendencies of a positive relationship with Participation, but it was not possible to draw any conclusions from these concepts. The results also indicated that having a Competition, or competitive environment could have a negative effect on Participation. Conclusion: The results show that there are some major differences between the results from studies dealing with implicit Crowdsourcing and innovation contests. The general nature of an explicit Crowdsourcing community is speculated to be more friendly and helpful than an implicit Crowdsourcing platform due to the necessary collaboration of explicit Crowdsourcing. Monetary incentives might be what draws the eye of a member in the beginning - although this is not tested -, and this is also one factor that might be motivating people the most in an explicit Crowdsourcing community. Nevertheless, the factors that could have effects on Participation in explicit Crowdsourcing were Monetary Awards, Ability, Competition, and Peer Pressure.

With the Culture Survey 2009, the Cultural policy in Sweden has got a new direction. The new direction emphasises the importance of broadening the non-public funding for the cultural sector. The new direction opens up new phenomenon to establish themselves in Sweden. Crowdfunding is such a phenomenon. Crowdfunding is an online-method "by which the individual becomes financiers of projects and activities they have passion for" (Jakten på medborgarfinansiering, 11). The essay has resulted in a comprehensive presentation of the phenomenon crowdfunding and a deepening of the platform Crowdculture. Crowdculture is an online-platform for funding cultural projects through a combination of crowdfunding and public support. Societal trends digitization, stronger donation culture, economization of culture and cultural policies that seek broader financing is considered to be the foundation for Crowdcultures existence. The method crowdfunding contribute to a participatory and an audience perspective, witch is not previously been used frequently in the cultural sector. The platform Crowdculture suits a particular type of cultural project, and should not replace the existing funding. Within the cultural sector Crowdculture has the potential to make an impact but the potential has not yet fully spread. Cultural projects that fit within crowdfunding is usually owned and produced by civil society, as these projects have been difficult to get public funding. The method Corwdfunding is not only about getting funding but also with opportunity for early marketing. / Kulturutredningen 2009 har gett kulturpolitiken i Sverige en ny inriktning. Den nya inriktningen betonar vikten av att bredda den icke offentliga finansieringen av kultursektorn. Inriktningen öppnar upp för nya fenomen att etablera sig i Sverige. Crowdfunding är ett sådant fenomen. Crowdfunding är en online-metod ”genom vilken individen blir finansiärer av projekt och verksamhet de känner engagemang för” (Jakten på medborgarfinansiering, 11). Uppsatsen har resulterat i en övergripande presentation av fenomenet crowdfunding och en fördjupning av plattformen Crowdculture. Crowdculture är en online-plattform för att finansiera kulturprojekt genom en kombination av crowdfunding och offentligt bidrag. Samhällstrenderna digitalisering, starkare donationskultur, kulturens ekonomisering och kulturpolitiken som eftersträvar breddad finansiering anses vara grunden till Crowdcultures existens. Metoden crowdfunding bidrar till en deltagarkultur och ett publikperspektiv som tidigare inte använts flitigt inom kultursektorn. Plattformen Crowdculture passar en viss typ av kulturprojekt och bör inte ersätta redan befintligt finansieringssystem. Crowdculture har potential att få genomslag inom kultursektorn men är inte riktigt där ännu. Kulturprojekt som ryms inom crowdfunding är oftast ägda och producerade av civilsamhället då dessa projekt har svårt att få offentlig finansiering. Crowdfunding handlar inte endast om att finansiera projekt utan belyser också ett nytt sätt av marknadsföring.

Enterprise crowdsourcing transforms the way in which traditional business tasks can be processed by harnessing the collective intelligence and workforce of a large and often diver-sified group of people. At the present time, data and information residing within enterprise crowdsourcing systems and other business applications are insufficiently interlinked and are rarely made publicly available in an open and semantically structured manner – neither to the corporate intranet nor to the World Wide Web (WWW). However, the semantic annotation of enterprise crowdsourcing activities is a promising research and application domain. The Semantic Web and its related technologies, methods and principles for publishing structured data offer an extension of the traditional layout-oriented Web to provide more intelligent and complex services. This technical report describes the efforts toward a universal and lightweight yet powerful Semantic Web vocabulary for the domain of enterprise crowdsourcing. As a methodology for developing the vocabulary, the approach of ontology engineering is applied. To illustrate the purpose and to limit the scope of the ontology, several informal competency questions as well as functional and non-functional requirements are presented. The subsequent con-ceptualization of the ontology applies different sources of knowledge and considers various perspectives. A set of semantic entities is derived from a review of existing crowdsourcing applications and a review of recent crowdsourcing literature. During the domain capture, all partial results of the review are integrated into a consistent data dictionary and structured as a UML data schema. The designed ontology includes 24 classes, 22 object properties and 30 datatype properties to describe the key aspects of a crowdsourcing model (CSM). To demonstrate the technical feasibility, the ontology is implemented using the Web Ontology Language (OWL). Finally, the ontology is evaluated by means of transforming informal to formal competency questions, comparing it to existing semantic vocabularies, and calculat-ing ontology metrics. Evidence is shown that the CSM ontology covers the key representa-tional needs of the enterprise crowdsourcing domain. At the end of the technical report, cur-rent limitations are illustrated and directions for future research are proposed.

De plus en plus de contenus 3D interactifs sont disponibles sur la toile. Visualiser et manipuler ces contenus 3D en temps réel, de façon naturelle et intuitive, devient donc une nécessité. Les applications visées sont nombreuses : le e-commerce, l'éducation et la formation en ligne, la conception, ou l'architecture dans le contexte par exemple de musées virtuels ou de communautés virtuelles. L'utilisation de contenus 3D en ligne ne propose pas de remplacer les contenus traditionnels, tels que les textes, les images ou les vidéos, mais plutôt d'utiliser la 3D en complément, pour enrichir ces contenus. La toile est désormais une plate-forme où les contenus hypertexte, hypermédia, et 3D sont simultanément disponibles pour les utilisateurs. Cette utilisation des contenus 3D pose cependant deux questions principales. Tout d'abord, les interactions 3D sont souvent lourdes puisqu'elles comprennent de nombreux degrés de liberté; la navigation dans les contenus 3D peut s'en trouver inefficace et lente. Nous abordons ce problème en proposant un nouveau paradigme basé sur l'analyse des interactions (crowdsourcing). En analysant les interactions d'utilisateurs 3D, nous identifions des régions d'intérêt (ROI), et générons des recommandations pour les utilisateurs suivants. Ces recommandations permettent à la fois de réduire le temps d'interaction pour identifier une ROI d'un objet 3D et également de simplifier les interactions 3D nécessaires. De plus, les scènes ou objets 3D contiennent une information visuelle riche. Les sites Web traditionnels contiennent, eux, principalement des informations descriptives (textuelles) ainsi que des hyperliens pour permettre la navigation. Des sites contenants d'une part de l'information textuelle, et d'autre part de l'information 3D peuvent s'avérer difficile à appréhender pour les utilisateurs. Pour permettre une navigation cohérente entre les informations 3D et textuelles, nous proposons d'utiliser le crowdsourcing pour la construction d'associations sémantiques entre le texte et la visualisation en 3D. Les liens produits sont proposés aux utilisateurs suivants pour naviguer facilement vers un point de vue d'un objet 3D associé à un contenu textuel. Nous évaluons ces deux méthodes par des études expérimentales. Les évaluations montrent que les recommandations réduisent le temps d'interaction 3D. En outre, les utilisateurs apprécient l'association sémantique proposée, c'est-à-dire, une majorité d'utilisateurs indique que les recommandations ont été utiles pour eux, et préfèrent la navigation en 3D proposée qui consiste à utiliser les liens sémantiques ainsi que la souris par rapport à des interactions utilisant seulement la souris. / Recent years have seen the development of interactive 3D graphics on the Web. The ability to visualize and manipulate 3D content in real time seems to be the next evolution of the Web for a wide number of application areas such as e-commerce, education and training, architecture design, virtual museums and virtual communities. The use of online 3D graphics in these application domains does not mean to substitute traditional web content of texts, images and videos, but rather acts as a complement for it. The Web is now a platform where hypertext, hypermedia, and 3D graphics are simultaneously available to users. This use of online 3D graphics, however, poses two main issues. First, since 3D interactions are cumbersome as they provide numerous degrees of freedom, 3D browsing may be inefficient. We tackle this problem by proposing a new paradigm based on crowdsourcing to ease online 3D interactions, that consists of analyzing 3D user interactions to identify Regions of Interest (ROIs), and generating recommendations to subsequent users. The recommendations both reduce 3D browsing time and simplify 3D interactions. Second, 3D graphics contain purely rich visual information of the concepts. On the other hand, traditional websites mainly contain descriptive information (text) with hyperlinks as navigation means. The problem is that viewing and interacting with the websites that use two very different mediums (hypertext and 3D graphics) may be complicated for users. To address this issue, we propose to use crowdsourcing for building semantic associations between texts and 3D visualizations. The produced links are suggested to upcoming users so that they can readily locate 3D visualization associated with a textual content. We evaluate the proposed methods with experimental user studies. The evaluations show that the recommendations reduce 3D interaction time. Moreover, the results from the user study showed that our proposed semantic association is appreciated by users, that is, a majority of users assess that recommendations were helpful for them, and browsing 3D objects using both mouse interactions and the proposed links is preferred compared to having only mouse interactions.

Les plateformes de co-innovation sont des dispositifs en ligne que les entreprises ont commencé à développer au milieu de la décennie 2000, dans le sillage du Web 2.0, afin d’intégrer les consommateurs au processus d’innovation. Présentées comme de nouveaux espaces ouverts et collaboratifs, entièrement dédiés à la coopération avec les internautes, ces démarches participatives suscitent l’engouement des gestionnaires et des cabinets de conseil spécialisés dans l’innovation. Pourtant, rares sont les études portant sur la co-innovation qui aient consacré une enquête de terrain aux dispositifs mis en place et aux formes de collaborations qu’ils accueillent. La sociologie, en particulier, s’est notablement désintéressée — au profit des sciences de gestion — des initiatives de co-innovation impliquant de grandes entreprises et a fait porter l’essentiel de ses analyses sur des cas d’innovation ascendante, sur le mouvement du logiciel libre ou sur de petites structures de nature entrepreneuriale. Cette thèse, en prenant pour objet six plateformes mises en place par des très grandes entreprises françaises et étasunienne dans les secteurs des télécommunications, du transport de voyageurs et du matériel informatique, vise à combler ce manque.Au-delà de cette ambition qui tente de restituer la légitimité d’un objet de recherche au sein d’un champ disciplinaire, cette thèse tisse une réflexion autour de trois problèmes fondamentaux : pourquoi et comment les entreprises associent-elles les usagers à leur processus d’innovation ? Pourquoi et comment les usagers collaborent-ils, le plus souvent de façon bénévole ? De quelles nouvelles formes de collaboration, voire de relation, entre l’individu et l’entreprise ces dispositifs sociotechniques sont-ils porteurs ?Nous apportons des réponses à ces questions en mobilisant les outils combinés de la théorie du cadre de référence de Flichy, de la théorie des régimes d’engagement développée par Thévenot et poursuivie par Auray, et enfin des concepts standards de l’analyse de réseaux. Sur le plan empirique, cette thèse s’appuie sur une enquête de terrain menée depuis 2010 auprès des acteurs de ces plateformes, au cours de laquelle nous avons adopté une méthode quali-quantitative articulant 44 entretiens semi-directifs auprès des acteurs des plateformes (usagers mais aussi responsables de plateformes, chefs de produits, community managers), observations en ligne et analyse de réseaux des collaborations qui se nouent autour des dispositifs. / Innovation platforms are online disposistifs that companies have started to develop in the middle of the 2000s, in the wake of the Web 2.0, in order to incorporate customers to the innovation process. Presented as new open and collaborative spaces, entirely dedicated to the cooperation with Internet users, these participative processes arouse the enthusiasm of managers and consulting firms specialized in innovation. Yet, there are only few studies dealing with co-innovation that have dedicated a field survey to the dispositifs that have been set up and to the collaborations they host. Sociology, in particular, has had little interest — in favour of management sciences — in co-innovation processes involving big companies, and has focussed the most of its analyzes on cases of bottom-up innovation, free software movement and start-up economy.This thesis, by choosing as field survey six platforms built by very large companies from several business sectors (telecommunications, passenger transport and computer equipment), aims to fill this gap.Beyond this ambition that tries to restore the legitimacy of a research topic within a research area, this thesis weaves a reflection on three fundamental problems : why and how do companies associate users to their innovation process ? Why and how do users collaborate with them, most of the time on a volunteer basis ? What new forms of collaboration, nay of relationships, between the individual and the company this sociotechnical dispositifs do carry ?We provide answers to these questions by mobilizing the combined tools of Flichy’s theory of reference frame, Thevenot’s theory —continued by Auray — of engagement regimes, and finally the standard concepts of social network analysis (SNA). Empirically, this thesis is based on a field survey conducted since 2010 among the actors of these platforms, in which we have adopted a quali-quantitative method hinging 44 semi-structured interviews with platforms actors (users but also platforms managers, product managers, community managers, etc), online observations and online collaborations network analysis.

The last couple of years have seen a fascinating evolution. While the early Web predominantly focused on human consumption of Web content, the widespread dissemination of social software and Web 2.0 technologies enabled new forms of collaborative content creation and problem solving. These new forms often utilize the principles of collective intelligence, a phenomenon that emerges from a group of people who either cooperate or compete with each other to create a result that is better or more intelligent than any individual result (Leimeister, 2010; Malone, Laubacher, & Dellarocas, 2010). Crowdsourcing has recently gained attention as one of the mechanisms that taps into the power of web-enabled collective intelligence (Howe, 2008). Brabham (2013) defines it as “an online, distributed problem-solving and production model that leverages the collective intelligence of online communities to serve specific organizational goals” (p. xix). Well-known examples of crowdsourcing platforms are Wikipedia, Amazon Mechanical Turk, or InnoCentive. Since the emergence of the term crowdsourcing in 2006, one popular misconception is that crowdsourcing relies largely on an amateur crowd rather than a pool of professional skilled workers (Brabham, 2013). As this might be true for low cognitive tasks, such as tagging a picture or rating a product, it is often not true for complex problem-solving and creative tasks, such as developing a new computer algorithm or creating an impressive product design. This raises the question of how to efficiently allocate an enterprise crowdsourcing task to appropriate members of the crowd. The sheer number of crowdsourcing tasks available at crowdsourcing intermediaries makes it especially challenging for workers to identify a task that matches their skills, experiences, and knowledge (Schall, 2012, p. 2). An explanation why the identification of appropriate expert knowledge plays a major role in crowdsourcing is partly given in Condorcet’s jury theorem (Sunstein, 2008, p. 25). The theorem states that if the average participant in a binary decision process is more likely to be correct than incorrect, then as the number of participants increases, the higher the probability is that the aggregate arrives at the right answer. When assuming that a suitable participant for a task is more likely to give a correct answer or solution than an improper one, efficient task recommendation becomes crucial to improve the aggregated results in crowdsourcing processes. Although some assumptions of the theorem, such as independent votes, binary decisions, and homogenous groups, are often unrealistic in practice, it illustrates the importance of an optimized task allocation and group formation that consider the task requirements and workers’ characteristics. Ontologies are widely applied to support semantic search and recommendation mechanisms (Middleton, De Roure, & Shadbolt, 2009). However, little research has investigated the potentials and the design of an ontology for the domain of enterprise crowdsourcing. The author of this thesis argues in favor of enhancing the automation and interoperability of an enterprise crowdsourcing environment with the introduction of a semantic vocabulary in form of an expressive but easy-to-use ontology. The deployment of a semantic vocabulary for enterprise crowdsourcing is likely to provide several technical and economic benefits for an enterprise. These benefits were the main drivers in efforts made during the research project of this thesis: 1. Task allocation: With the utilization of the semantics, requesters are able to form smaller task-specific crowds that perform tasks at lower costs and in less time than larger crowds. A standardized and controlled vocabulary allows requesters to communicate specific details about a crowdsourcing activity within a web page along with other existing displayed information. This has advantages for both contributors and requesters. On the one hand, contributors can easily and precisely search for tasks that correspond to their interests, experiences, skills, knowledge, and availability. On the other hand, crowdsourcing systems and intermediaries can proactively recommend crowdsourcing tasks to potential contributors (e.g., based on their social network profiles). 2. Quality control: Capturing and storing crowdsourcing data increases the overall transparency of the entire crowdsourcing activity and thus allows for a more sophisticated quality control. Requesters are able to check the consistency and receive appropriate support to verify and validate crowdsourcing data according to defined data types and value ranges. Before involving potential workers in a crowdsourcing task, requesters can also judge their trustworthiness based on previous accomplished tasks and hence improve the recruitment process. 3. Task definition: A standardized set of semantic entities supports the configuration of a crowdsourcing task. Requesters can evaluate historical crowdsourcing data to get suggestions for equal or similar crowdsourcing tasks, for example, which incentive or evaluation mechanism to use. They may also decrease their time to configure a crowdsourcing task by reusing well-established task specifications of a particular type. 4. Data integration and exchange: Applying a semantic vocabulary as a standard format for describing enterprise crowdsourcing activities allows not only crowdsourcing systems inside but also crowdsourcing intermediaries outside the company to extract crowdsourcing data from other business applications, such as project management, enterprise resource planning, or social software, and use it for further processing without retyping and copying the data. Additionally, enterprise or web search engines may exploit the structured data and provide enhanced search, browsing, and navigation capabilities, for example, clustering similar crowdsourcing tasks according to the required qualifications or the offered incentives.

This Master's Thesis prepares Evaluation Set for Problems of Recognition and Disambiguation of Named Entities. Evaluation Set is created using Automatization and Crowdsourcing. Evaluation Set can be used in testing Edge Cases in Recognition and Disambiguation of Named Entities.

Les projets en humanités numériques utilisent de plus en plus des méthodes de collaboration axées sur le public, telles que le crowdsourcing pour atteindre les objectifs de recherche, de conservation et d’édition scientifique en sciences humaines et sociales. Par exemple, le crowdsourcing représente une opportunité pour accélérer les projets de transcription pour des communautés de chercheurs qui travaillent traditionnellement dans des circuits-fermés. Certaines questions importantes soulevée par les chercheurs et les érudits concernent notamment l’intérêt de la méthode, et en particulier la qualité des résultats obtenus avec cette méthode. En outre, l’efficacité du crowdsourcing pour les humanités numériques n’est pas documenté dans la littérature. Se pose ainsi la question de savoir si le public peut produire du matériel pouvant être par la suite utilisé pour des éditions scientifiques, auxquels cas, pour quel type de projet et combien de post-traitement ou corrections seront nécessaires.Cette thèse de doctorat examinera le potentiel apport du crowdsourcing des transcriptions pour les projets d’édition scientifique en humanités numériques. Pour cela, nous allons premièrement explorer les technologies et les techniques disponibles pour produire les transcriptions sous format XML en ligne. Deuxièmement, ayant développé et testé une plateforme internet de transcription que nous présenterons, nous pourrons examiner les besoins des utilisateurs vis-à-vis des environnements de travail collaboratifs fondées sur les retours des utilisateurs et les environments de crowdsourcing industriels existants. Troisièmement, les données récoltées seront soumises à une analyse numérique qui permettra de comparer les productions des experts et celle des non-experts en s’appuyant sur les mesures de distances entre documents. Les résultats obtenus permettront de déterminer le potentiel apport du crowdsourcing pour les projets d’édition numérique scientifique. Enfin, le travail se terminera avec une discussion sur les implications des travaux actuels et présentera des opportunités pour des recherches futures sur le terrain. / Projects in digital humanities increasingly employ public-oriented collaboration methods such as crowdsourcing to achieve objectives that include research, conservation and scholarly editing in the humanities and social sciences. For example, crowdsourcing presents an opportunity to quicken the pace of progress for transcription projects for research communities that have traditionally operated within closed circuits. Some important questions raised by researchers and scholars concern the benefits of using this method and in particular the quality of results that can be obtained. Meanwhile, literature that evaluates the efficacy of crowdsourcing for digital humanities projects is insufficient. Questions as to whether the public can produce material that can be used for scholarly editions, in which cases, for which types of projects, and how much post-processing or corrections will be required, continue to occupy discussions on the matter.This doctoral thesis will examine the potential benefits of crowdsourced transcription for scholarly editing projects in the digital humanities. Firstly, by exploring the technologies and techniques available to render online transcription in XML possible. Secondly, by developing and testing an online transcription platform, which will allow to examine user needs for collaborative work environments based on user responses and existing industrial crowdsourcing environments. Thirdly, the data collected will be subjected to digital analysis to compare the productions of non-expert transcribers to those of expert transcribers on the basis of document distance measurements. The results will be interpreted to determine the potential benefits of crowdsourcing for digital scholarly editing projects. Finally, the work will conclude by discussing the implications of current work and presenting opportunities for future research in the field.