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What is Wisdom in this kind of society? And what things are helping or hindering us from having both wisdom and a good quality of life in ICT societies? Taking the reader through a quick Global Youth in Digital Trajectories explores the most recent developments regarding youth and media in a global perspective. Representing an innovative contribution to virtual research methods, this book presents research carried out in areas as diverse as Greece, the Netherlands, Germany, Brazil, Grounded in qualitative empirical research about social media users' attitudes towards privacy and surveillance issues, this book contributes to a critical theory of information capitalism by exploring the commodification of privacy and personal data, providing a critical framing of the ongoing Bringing together empirical cultural and media studies of religion and critical social theory, Technologies of Religion: Spheres of the sacred in a post-secular modernity investigates powerful entanglement of religion and new media technologies taking place today, taking stock of the repercussions This book is the first general social analysis that seriously considers the daily experience of information disruption and software failure within contemporary Western society.

Through an investigation of informationalism, defined as a contemporary form of capitalism, it describes the social Daniel Trottier, Christian Fuchs January 27, This book is the essential guide for understanding how state power and politics are contested and exercised on social media. It brings together contributions by social media scholars who explore the connection of social media with revolutions, uprising, protests, power and counter-power, hacktivism How is global togetherness possible?

How does the availability of the Internet alter migrants' everyday lives and senses of belonging? This book introduces an 'alien people' inhabiting a specific common virtual space in the World Wide Web, while the members of this space - most of them ethnic Alistair S. Duff September 20, There is a clear need for a systematic, integrative, and rigorous normative theory of the information society. In this book, Duff offers a prescriptive theory to help to guide the academic and policy communities as they debate the future shape of emerging post-industrial, information-based Migrants and diaspora communities are shaped by their use of information and communication technologies.

This book explores the multifaceted role played by new media in the re-location of these groups of people, assisting them in their efforts to defeat nostalgia, construct new communities, and Fengshu Liu situates the lives of Chinese youth and the growth of the Internet against the backdrop of rapid and profound social transformation in China. In , the total of Internet users in China had reached million in comparison with Yet, despite rapid growth, the Stay on CRCPress.

Social networking is generally expected to improve information accuracy, foster peer-based learning and co-creation where participants are able to both generate and evaluate content, develop new knowledge, and refine existing skills, all of which can lead to higher quality UGC Lukyanenko ; Silvertown ; Tan et al.

Contributors remain aware of the social context in which observations are being made: the study by Nov et al. As the same time, overreliance on social media in the context of citizen science may impose scientific limitations and negative impacts on quality. High user interactivity may lead to group think or hypothesis guessing. As scientists frequently conduct online experiments in the context of citizen science e. Social media also brings additional challenges of managing a less structured user engagement, which can be fraught with cyberbullying, trolling or other malignant user behavior prevalent on social media platforms Kapoor et al.

As social networking has only recently been incorporated into corporate information production Andriole , there is scarce work on IQ implications of these platforms, and findings from citizen science may offer useful insights to social networking-related IQ research in corporate settings. Consider malfeasance, a persistent concern in open online settings Law et al. Research has also considered features of systems that make them more robust to malfeasance Wiggins and He , as anecdotal evidence has suggested extremely low levels of malicious behavior in citizen science.

These lessons may be applicable in more traditional settings to detect data sabotage by disgruntled employees. Research on social factors in citizen science can also contribute to the emerging area of online digital experimentation conducted for marketing or product development purposes in commercial contexts e. Citizen science sheds new light on and invites reconsideration of several long-standing assumptions of IS research.

Some researchers argue that novel challenges of understanding and improving quality in citizen science warrant extending prevailing definitions of IQ and suggest rethinking traditional methods of improvement Lukyanenko and Parsons b. The organizational IQ paradigm focused on the data consumers and has defined quality as fitness of data to their needs Madnick et al. This view remains central to much of citizen science, as scientists routinely approach citizen science the same way they approach scientific research: they formulate predefined hypotheses, set goals for the projects, and then use the data provided by the volunteers to corroborate their predictions and assumptions Lukyanenko and Parsons ; Wiersma This strategy is also sound as it reduces noise and variation in the data and makes the resulting data much easier to interpret and analyze.

Notwithstanding the value of approaching citizen science from the traditional fitness for use perspective, it may have limitations for some projects. Thus, holding data contributors to data consumer standards may curtail their ability to provide high quality content as defined by data consumers, or suggest a need to refine instructions, procedures, or expectations. Guided by this definition, a series of laboratory and fields experiments demonstrated that accuracy and completeness of citizen science data can indeed be improved by relaxing the requirements to comply with data consumer needs Lukyanenko et al.

Further, for projects focusing on new, emerging phenomena, it may be challenging to anticipate the optimal structure of citizen science data due to the different needs of diverse data consumers, so traditional solutions for storage premised on a priori structures e. The new definition, however, remains controversial: the original definition was clearly useful for project leaders, and the data resulting from putting the views of data contributors first may be sparse and difficult to work with or even intractable for scientific requirements.

Nonetheless, the advantages for some contexts suggest that the traditional fitness for use view may not fully capture the diverse and changing IQ landscape. These findings further provide a novel connection between conceptual modeling grammars i. The citizen science context revealed an exciting new possibility for combining research strands within IS.

Another controversial idea born out of citizen science is the notion that expertise may be harmful to IQ Ogunseye and Parsons Contrary to the prevailing common sense assumption, Ogunseye and Parsons argue that it is the essence of expertise to be focused, and potentially ignore what is deemed irrelevant based on prior knowledge. Citizen science is a setting where discoveries are possible, and thus, it is important to have an open mind Lukyanenko et al. Crowdsourcing strategies where added value is premised on diverse contributions, e.

An active stream of research has studied design antecedents of quality in citizen science: many novel IS design solutions are rapidly tested with information quality being the most common outcome variable evaluated. It can also offer a setting for research on participatory design Bowser et al. Growing evidence demonstrates benefits of gamification for data quantity and discovery. For example, Foldit is a highly successful project that turns a complex and esoteric task of designing proteins into an interactive game resulting in important discoveries in healthcare and biology Belden et al.

Defying the notoriously mysterious nature of quantum theory, the Quantum Game Jam project scienceathome. As gamification is quite novel in IS e. The quality challenges in citizen science also fuel the search for innovative design solutions, such as applying artificial intelligence techniques like machine learning.

Artificial intelligence appears fruitful where knowledge and abilities of volunteers are deemed limited Bonney et al. Typically, however, machine learning is applied post hoc — after data is captured — to detect trends or label items based on data provided Hochachka et al. Citizen science is one of the pioneers of artificial intelligence used to augment and improve quality at the point of data creation. For example, the Merlin App aids people with bird species identification based on uploaded photographs and other basic information, using data from eBird contributors to predict likely species matches.

The decision is made in real time and allows people to confirm or reject the automatic recommendation; the machine learning results can also be used to dynamically generate more effective data collection forms. The same project uses post hoc data mining to sift through millions of bird sightings to identify outliers, automatically flag erroneous species identifications, and detect potential vandalism.

The substantial progress in the application of artificial intelligence and high-performance computing as well as growing evidence of effective adaptation of successful project designs led to recent Nature Show and Science Bonney et al. Such a conclusion, of course, is based on limited indicators of quality based on accuracy of identification e. At the same time, such signals from the leaders in the citizen science community are quite telling of the significant progress the field made in a very short period of time, which also stands ready to advance the broader field of IS.

Finally, a notable contribution of the citizen science context is investigating IQ in real settings. As visitors of websites can be easily converted into research subjects by assigning them to different control and treatment conditions Lukyanenko and Parsons , many citizen science experiments can be conducted in field settings Delaney et al. Despite challenges in controlling for confounds, field experiments offer several advantages over laboratory experiments or surveys.

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Using a real setting allows tracking real user behavior as opposed to behavioral intentions. It also allows for research with the population of interest rather than surrogates e. Conducting research in a real setting also increases external validity compared to similar studies conducted in laboratory environments. As field experimentation is generally scarce in IS Siau and Rossi ; Zhang and Li , citizen science field experimental evidence can be used to corroborate and compare findings from more prevalent surveys and laboratory data e.

The examples of research in citizen science provided above are not meant to be comprehensive and exhaustive. Instead, they illustrate the potential of this research domain for advancing knowledge and practice in IS related to IQ. As discussed earlier, citizen science information quality research actively investigates traditional aspects of information quality, novel concepts, methods for conducting research, and approaches to IS development and IQ management. Currently rooted in specific scientific disciplines, citizen science studies have much to offer to the traditional information quality work in IS.

At the same time, as information quality is one of the core subject areas for the information systems research, citizen science promises unique opportunities for cross-pollination of theories and methods, and for exporting foundational knowledge from IS to sciences where practitioners actively seek collaborators but may be unaware of IS research community.

In the next section, we further consider the role citizen science information quality research may play in connecting IS scholars with the broader scientific community. Citizen science is becoming a prolific area of research in sciences credited with an increasing number of scientific breakthroughs and discoveries, and indeed, its own journal - Citizen Science: Theory and Practice Bonney et al.

At the same time, citizen science presents a wicked theoretical and design challenge Hevner et al. Extensive evidence has emerged to support the effectiveness of enlisting ordinary people in this endeavor, so these wicked challenges are part of what makes citizen science such a promising venue for information quality research. One can hardly find another example of the convergence of so many different disciplinary perspectives and ideas focused on ensuring high-quality data. This paper demonstrates the strong potential of citizen science to advance IQ and offer unique insights to the information systems community, identifying ways that IS researchers can contribute to this socially-important movement.

Citizen science is being actively pursued by scientists from different disciplines, who are rarely familiar with IS;. Many of the disciplines engaged in citizen science view IQ issues from their own perspectives, using their own vocabularies, with limited incentive to contribute beyond their own areas of research e. Much of the research on citizen science is published in non-IS and non-IQ journals, making it likely to be overlooked by IQ scholars.

These observations suggest that citizen science can be an important area of focus for future research that increases contact and collaboration between researchers in IS and other scientific disciplines. Below, we identify several directions in information quality in citizen science to support the assimilation of citizen science research conducted in sciences into IS.

Survey of the state of the art in citizen science. As shown in this paper, there is a wealth of theoretical and practical knowledge that is being continuously generated in non-IS domains. Much of knowledge on IQ in citizen science comes from the broader scientific community, including biology, physics, geography, anthropology, heath care, and engineering. Their interdisciplinary approaches can provide inspiration for new IQ work in IS. We suggest IS researchers should continuously monitor citizen science literature currently almost entirely outside IS to find relevant results and solutions.

We call on the due diligence of both researchers in IS and the reviewers of such work, as a literature review on citizen science is fundamentally incomplete if it includes IS publications alone. To guide such surveys of the state of the art, researchers in IS can take advantage of the many reviews of citizen science and IQ published in domain journals in sciences and humanities.

Indeed, such reviews have already commenced, but thus far they focus on the citizen science itself e. Publications such as Kosmala et al. More work is needed that surveys the ongoing research in the sciences from the perspective of the information quality tradition in IS, with the aim of assimilating these ideas and findings for the benefit of IS. Which themes are emerging in IQ citizen science research in other disciplines? What are key trends and findings? Which IQ solutions are most actively pursued in other disciplines?

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Which of these are most promising for broader applications? Which require more analysis and investigations? What research areas are becoming saturated and what gaps are emerging? What conceptual areas have the most potential to result in significant insights for theory of IQ? Which findings hold the most practical relevance and impact? Which are most clearly translatable to other contexts? Integration of research in citizen science with broader information quality research.

Following from the previous research direction, once relevant studies have been identified and surveyed, their cumulative knowledge needs to be integrated with theories and methods in IS. This paper has attempted to begin demonstrating how citizen science research relates to existing knowledge in IS, including identification of what is novel and what is a new application of prior knowledge. But a more systematic effort is needed and this work is likely to be a challenging one.

Given its inherent disciplinary roots, many studies in citizen science utilize language, concepts and pursue objectives very different from that of the IQ tradition in IS. Yet, as argued earlier, this diversity makes this research area quite a productive source of original ideas. What basic assumptions of IS IQ research does citizen science violate? Are these assumptions due for critical re-evaluation? How does this compare to other instances of data production and use in IS studies?

Find analogs of research problems studied in IS that also occur in citizen science. Once found, consider triangulating studies in IS context e. This will not only strengthen the generalizability of specific studies but also move the field of IS and citizen science closer. Conducting systematic literature reviews of citizen science from IS perspective, including focused reviews on relevant sub-topics to improve the utility and depth of the analysis.

This would include translation of disciplinary concepts into IS vocabulary via a nomological network. As citizen science is a rapidly moving field, such reviews should be repeated frequently. Here, a promising strategy is utilizing the novel machine-learning approaches for automatic literature review and knowledge integration currently under active development in IS Endicott et al.

Investigating and developing novel information quality approaches in citizen science. The IS community is increasingly engaging in design science research with the aim to produce innovative artifacts such as principles, models, methods, and instantiations Goes ; Gregor and Hevner ; Rai With this paper we hope to increase awareness and recognition of citizen science by the broader IS community as a fertile area for design work.

Citizen science presents many novel challenges exaggerated beyond their usual extent in traditional domains, creating opportunity for innovation. These and other advances are the tip of the proverbial iceberg for design work in this area. How can citizen science platforms be designed to allow maximally open citizen participation and to motivate contributions while delivering highest quality data to scientists?

How can designs encourage freedom of expression, promoting novel perspectives and discoveries while ensuring that the data remains consistent and usable for science? How can designs mitigate participation and reporting biases e. How can citizen science be augmented with AI and hybrid intelligence to make it more effective?

Considering citizen science implications of research findings. Assimilation of citizen science in IS should not be unidirectional. We call on researchers working on problems that are similar to citizen science to proactively consider implications of their studies for citizen science. While citizen science has unique characteristics, many of its features e. This naturally includes areas conceptually adjacent to citizen science such as other types of crowdsourcing, social media, distributed virtual teams, and social networks where similar information quality challenges persist.

While this environment differs from citizen science, with an explicit payment for work involving small tasks that are stripped of organizational context, the data production aspects of crowdsourcing share similarities with citizen science. So far, this line of work has been conducted in relative isolation Lukyanenko and Parsons a and holds strong potential to advance citizen science research. In the process of developing citizen science projects, researchers routinely investigate, test, and implement novel approaches for effective engagement with ordinary people.

Among other extensions, lessons from citizen science can be potentially applicable for corporate research and development initiatives which seek direct customer input. Companies are increasingly exploring these opportunities, such as Fortune companies investing in digital platforms to monitor what potential customers are saying, understand customer reactions to products and services, use consumer feedback to design better products, and monitor market changes Barwise and Meehan ; Brynjolfsson and McAfee ; Delort et al.

Indeed, some studies already demonstrate the potential of citizen science as a source of insight for data production in commercial settings. Ogunseye et al. These findings support our contention that citizen science can be a fruitful source of insights for information quality issues in corporate and other settings.

Broadly, citizen science also presents an opportunity for IS to share foundational concepts, principles, and design knowledge that can support excellence and advancement in a broad range of scientific disciplines. This would have a variety of benefits for IS, including amplifying its relevance to practice. As citizen science grapples with particularly daunting IQ challenges, it pioneers theoretical and practical approaches that can improve IQ in other domains.

For example, in an analogy to citizen science, the role of telemedicine health IS is connecting patients domain non-experts, familiar with own conditions and medical professionals domain experts Hailey et al. At the same time, since most of citizen science IQ research occurs in sciences, these researchers may be unfamiliar with the IS community, creating opportunity for IS research to bridge this gap by leveraging the knowledge of IQ to benefit other domains. Conduct cross-disciplinary literature reviews which identify common trends related to IQ e.

Consider cross-disciplinary research questions such as: How does the effect of training differ in tasks that involve semantic i. How does the design of online training systems impact task performance? Leverage similarities in underlying technology to better understand the impact of designs on IQ. For example, addressing the question of how mobile environments due to their limited screen space, but also novel affordances related to sensors and mobility could impede or promote user engagement in citizen science vs social networking settings.

General framework on IQ that considers citizen science. Existing frameworks for understanding an improving information quality have focused on corporate data production Blake and Shankaranarayanan ; Madnick et al. To better integrate citizen science into the broader IQ tradition in IS, existing frameworks need to be extended to include UGC and citizen science. This is important as citizen science does not exhaust the IQ landscape of emerging technologies nor vice versa, so their inclusion should lead to more robust frameworks.

Indeed, some IQ topics have received relatively less attention in citizen science compared to other UGC contexts and other areas. For example, much of work that relates to the impact of content moderation and editing appears to originate in the context of online forums and wikis Arazy et al. Wikipedia is the prototypical case for work on collaborative content production and its impact on IQ Arazy et al. Applying data mining to automatically parse through data to make UGC more usable by consumers tends to concentrate on social media and social networking data Abbasi et al.

Other open collaboration contexts include online reviews Pavlou and Dimoka , Linked Open Data Heath and Bizer , micro-tasks and crowdsourcing markets Deng et al. Thus, it is important to provide a comprehensive assessment of the entire space of UGC. Early work in this direction has been undertaken by Tilley et al. The diversity of UGC landscape calls for the development of general framework for understanding IQ in UGC that would also position citizen science relative to other forms of information production.

Create a general IQ framework which would account for citizen science and other emerging technologies. Integrate the framework on emerging technologies with traditional IQ to provide a general and unified view of IQ management. As follows from the illustration of some recent theoretical and practical contributions, along with many fertile areas for future work discussed above, citizen science is an area of exciting opportunities for intellectually stimulating and socially impactful research.

As IQ is arguably one of the core problems of the information systems discipline, quality becomes a common thread that can connect IS with many other disciplines in sciences and humanities. As astronomers, biologists, physicists, anthropologists, and geographers constantly grapple with the daunting task of ensuring that the data provided by ordinary people meets their high standards, information systems research with its long IQ tradition, explicit IQ focus, and proven IQ solutions has the potential to become the foundation on which the citizen science architecture of the future is built.

In closing, although we focused on the opportunities in conducting information quality research on citizen science in IS, we reiterate the general call made by Levy and Germonprez for information systems researchers to adopt citizen science as a rich, promising, and socially important research context. For example, one traditional expertise area of information systems researchers is adoption of new technologies Dwivedi et al. Adoption issues are fraught with challenges in citizen science, as information quality concerns place real, or at times, psychological Lewandowski and Specht barriers for scientists or policymakers interested in engaging with the public and using citizen-generated data in research or public policy decisions.

Conducting research in citizen science also heeds the call within the IS discipline to conduct research that promotes or supports environmental sustainability through innovative information technologies Goes ; Melville ; Seidel et al. We hope that this paper adds to this momentum and impels more work in IS to explore this new research frontier. Skip to main content Skip to sections. Advertisement Hide. Download PDF.


Information Systems Frontiers pp 1—23 Cite as. Open Access. First Online: 10 April Although citizen science is an established topic in natural sciences below, we briefly discuss the history of citizen science , it is a relatively recent area of research in the information systems discipline, including a stream focused on information quality, and in related fields such as computing.

Before discussing specific issues that relate to the quality of data in citizen science, we position citizen science in the context of other related phenomena. Table 1 provides definitions of some of related concepts note: the list is not exhaustive, and is meant to show major categories to elaborate the niche which citizen science occupies from an IS perspective.

Table 1 Examples of concepts closely related to citizen science. Concept Definition Reference Sources Scope of Phenomenon User generated content Information created online by the members of the general public, rather than organizational employees or other actors formally associated with an organization e. However, high user interactivity may not be suitable for some citizen science projects for reasons we discuss below , or can be simply unnecessary for the fulfilment of specific project objectives.

Finally, the essence of social media is facilitation of social exchange. Issues of scientific discovery, high information quality, pursuit of objective truth, adherence to protocols and standards, and environmental conservation are very much on the fringes for most social media projects. As Maddah et al. Table 2 Examples of recent discoveries made by citizen scientists. Discovery Details of the discovery Who facilitated the discovery? One of the interesting aspects of citizen science is its typically democratic and open nature Irwin Citizen science is fundamentally about empowering ordinary people in advancing research endeavors.

Consequently, it is against the spirit of citizen science to discriminate against participants based on lack of scientific training or low literacy ESCA Citizen science also puts an important premium on unique local knowledge. While this is technically also possible to do in citizen science, it both runs against the spirit of openness and inclusion and can jeopardize the recruitment and retention of contributors that is key to success in projects that rely on voluntary labor. Yet, as noted earlier, high-quality consistent data is needed to make strong inferences and conclusions.

Thus, scientists face a dilemma of optimizing information quality while keeping participation levels high enough to meet research needs and remaining sensitive to all relevant stakeholders. The challenge therefore becomes to preserve the openness of citizen science, allowing anybody interested to participate while delivering information of sufficient quality for scientific research.

Figure 1 shows the growth of research on and with citizen science across disciplines and time. This is a conservative method for identifying the extant literature on citizen science, as not all relevant publications use this currently popular terminology, but our initial query results included items. The results were manually de-duplicated by using title name and DOI for reference, since there was extensive cross-indexing in several sources. We also removed editorial introductions to journal issues, dissertations, workshop papers, and posters to leave only full papers.

Abstracts were then examined for papers with titles that were not obviously relevant to citizen science to evaluate the extent of focus on citizen science as a phenomenon or method. Papers mentioning citizen science only in passing, e. Open image in new window. It is further notable that the range of disciplinary specialties represented within Computing was not entirely out of line with the interests for IS scholars; Fig.

Across the entire data set, the topic of Information Quality appeared 49 times, including 29 Conservation papers where it was a more common primary focus than species groups or habitats, and 15 papers in Computing, although Information Quality was in fact a dominant theme in far more publications than was captured by this analysis. Table 3 Sample contributions of IQ in citizen science research. Based on our review of research on citizen science IQ, several themes emerged: Citizen science is being actively pursued by scientists from different disciplines, who are rarely familiar with IS; Many of the disciplines engaged in citizen science view IQ issues from their own perspectives, using their own vocabularies, with limited incentive to contribute beyond their own areas of research e.

Research Direction 1 Survey of the state of the art in citizen science. Among others, we encourage researchers to pursue the following questions: Which themes are emerging in IQ citizen science research in other disciplines? Research Direction 2 Integration of research in citizen science with broader information quality research. To begin integrating citizen science with IS, we suggest researchers address the following questions and needs: What basic assumptions of IS IQ research does citizen science violate? Research Direction 3 Investigating and developing novel information quality approaches in citizen science.

We encourage researchers to adopt citizen science as their domain and investigate such pressing questions as: How can citizen science platforms be designed to allow maximally open citizen participation and to motivate contributions while delivering highest quality data to scientists? Research Direction 4 Considering citizen science implications of research findings. We thus encourage researchers to: Conduct cross-disciplinary literature reviews which identify common trends related to IQ e.

Research Direction 5 General framework on IQ that considers citizen science. Accordingly, we call on future studies to: Create a general IQ framework which would account for citizen science and other emerging technologies. Abbasi, A. Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17 2 , 3. CrossRef Google Scholar. Text analytics to support sense-making in social media: A language-action perspective.

MIS Quarterly, 42 2 , 1— Google Scholar. Allahbakhsh, M.

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Quality control in crowdsourcing systems: Issues and directions. Alonso, O. Challenges with label quality for supervised learning. Journal of Data and Information Quality, 6 1 , 2. Amir B, Ralph P Proposing a theory of gamification effectiveness. Hyderabad: ACM. Asilomar: CIDR. Andriole, S. Business impact of web 2. Communications of the ACM, 53 12 , 67— Arazy, O. On the measurability of information quality. Information quality in Wikipedia: The effects of group composition and task conflict. Journal of Management Information Systems, 27 4 , 71— Turbulent stability of emergent roles: The dualistic nature of self-organizing knowledge coproduction.

Information Systems Research, 27 4 , — Heuristic principles and differential judgments in the assessment of information quality. Journal of the Association for Information Systems, 18 5 , Awal GK, Bharadwaj K Leveraging collective intelligence for behavioral prediction in signed social networks through evolutionary approach. Information Systems Frontiers 1— Azzurro, E. Citizen science detects the undetected: The case of Abudefduf saxatilis from the Mediterranean Sea.

Management of Biological Invasions, 4 2 , — Ballou, D. Designing information systems to optimize the accuracy-timeliness tradeoff. Information Systems Research, 6 1 , Modeling completeness versus consistency tradeoffs in information decision contexts. Journal of Management Information Systems. Barwise, P. The one thing you must get right when building a brand. Harvard Business Review, 88 12 , 80— Batini C, Scannapieca M Data quality: concepts, methodologies and techniques.

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Batini, C. From data quality to big data quality. Journal of Database Management, 26 1 , 60— Bauer, M. Beath, C. Expanding the frontiers of information systems research: Introduction to the special issue. Journal of the Association for Information Systems, 14 4 , 5. Becker-Klein R, Peterman K, Stylinski C Embedded assessment as an essential method for understanding public engagement in citizen science. Citizen Science: Theory and Practice, 1 1 , 1— Belden, O.

Citizens unite for computational immunology! Trends in Immunology, 36 7 , — Watson-Manheim, M. Discontinuities and continuities: A new way to understand virtual work. Information Technology and People, 15 3 , — Bifet, A. Sentiment knowledge discovery in twitter streaming data discovery science. Pfahringer, G. Hoffmann Eds. Heidelberg: Springer Berlin. Bird, T. Statistical solutions for error and bias in global citizen science datasets. Biological Conservation, , — Blake R, Shankaranarayanan G Data and information quality: Research themes and evolving patterns.

AMCIS , 1— Bodker, S. Creating conditions for participation: Conflicts and resources in systems development. Human Computer Interaction, 11 3 , — Bonabeau, E. Decisions 2. Bonney, R. Citizen science: A developing tool for expanding science knowledge and scientific literacy. BioScience, 59 11 , — Next steps for citizen science.

Science, , — Baltimore: ACM. Portland: ACM. Boyajian, T. Planet hunters IX. Monthly Notices of the Royal Astronomical Society, 4 , — Brabham, D. Cambridge: MIT Press. Bratteteig, T. Disentangling participation: Power and decision-making in participatory design. New York: Springer International Publishing. Brossard, D. Scientific knowledge and attitude change: The impact of a citizen science project. International Journal of Science Education, 27 9 , — Brynjolfsson, E.

The second machine age: Work, progress, and prosperity in a time of brilliant technologies. Biological Conservation, , — Google Scholar. Burton-Jones, A. How can we develop contextualized theories of effective use? A demonstration in the context of community-care electronic health records. Information Systems Research, 28 3 , — Calero, C. An applicable data quality model for web portal data consumers. World Wide Web, 11 4 , — Chau, M. Business intelligence in blogs: Understanding consumer interactions and communities. MIS Quarterly, 36 4 , — Chittilappilly, A. A survey of general-purpose crowdsourcing techniques.

Choy, K. Crowdsourcing for a better world: On the relation between IT affordances and donor motivations in charitable crowdfunding. Information Technology and People, 29 1 , — Clark, F. Dimensions of civic science introductory essay. Science Communication, 23 1 , 5— Clark, C. The Einstein home gamma-ray pulsar survey. Search methods, sensitivity, and discovery of new Young gamma-ray pulsars. The Astrophysical Journal, 2 , Cohn, J. Citizen science: Can volunteers do real research? AIBS Bulletin, 58 3 , — Crall, A. Assessing citizen science data quality: An invasive species case study.

Conservation Letters, 4 6 , — Daniel, F. Quality control in crowdsourcing: A survey of quality attributes, assessment techniques, and assurance actions. Daugherty, T. Exploring consumer motivations for creating user-generated content. Journal of Interactive Advertising, 8 2 , 16— Davenport, T. Competing on analytics: Updated, with a new introduction: The new science of winning.

Cambridge: Harvard Business Press. Davis, A. Spring recolonization rate of monarch butterflies in eastern North America: New estimates from citizen-science data. Journal of the Lepidopterists' Society, 59 1 , 1—5. Delaney, D. Marine invasive species: Validation of citizen science and implications for national monitoring networks. Biological Invasions, 10 1 , — DeLone, W. Information systems success: The quest for the dependent variable.

Information Systems Research, 3 1 , 60— Delort, J. Automatic moderation of online discussion sites. International Journal of Electronic Commerce, 15 3 , 9— Deng, X. The duality of empowerment and marginalization in microtask crowdsourcing: Giving voice to the less powerful through value sensitive design. MIS Quarterly, 40 2 , — Doan, A. Crowdsourcing systems on the world-wide web.

Communications of the ACM, 54 4 , 86— Dwivedi, Y. Research on information systems failures and successes: Status update and future directions. Information Systems Frontiers, 17 1 , — Eitzel, M. Citizen science terminology matters: Exploring key terms. Citizen Science: Theory and Practice, 2 1. Elevant K Why Share Weather? European Citizen Science Association. Toronto: ACM.

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Fielden, M. Aedes japonicus japonicus Diptera: Culicidae arrives at the most easterly point in North America. Canadian Entomologist, 06 , — Flanagin, A. The credibility of volunteered geographic information. GeoJournal, 72 3 , — ACM, Athens, Greece , 61— French, A. Current status, issues, and future of bring your own device BYOD.

CAIS, 35 , Galloway, A. The reliability of citizen science: A Case study of Oregon white oak stand surveys. Wildlife Society Bulletin, 34 5 , — Garcia-Molina, H. Challenges in data crowdsourcing. Garrity, E. Synthesizing user centered and designer centered IS development approaches using general systems theory. Information Systems Frontiers, 3 1 , — Gemino, A. A framework for empirical evaluation of conceptual modeling techniques.

Requirements Engineering, 9 4 , — Ghezzi, A. Crowdsourcing: A review and suggestions for future research. International Journal of Management Reviews, 00 , 1— Girres, J. Quality assessment of the French OpenStreetMap dataset. Transactions in GIS, 14 4 , — Goes, P. MIS Quarterly, 38 1 , iii—viii. Goodchild, M. Citizens as sensors: The world of volunteered geography.

GeoJournal, 69 4 , — Crowdsourcing geographic information for disaster response: A research frontier.

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International Journal of Digital Earth, 3 3 , — Gregor, S. Positioning and presenting design science research for maximum impact. MIS Quarterly, 37 2 , — Gura, T. Citizen science: amateur experts. Nature, , — Hailey, D. Systematic review of evidence for the benefits of telemedicine. Journal of Telemedicine and Telecare, 8 1 , 1—7.

Haklay M Citizen science and volunteered geographic information: Overview and typology of participation. Crowdsourcing Geographic Knowledge. Dordrecht: Springer. Haklay, M. OpenStreetMap: User-generated street maps. Hand, E. People power. He, Y. International Journal of Environment Science Education, 12 6 , — Heath, T. Linked data: Evolving the web into a global data space. Heikkila, T. Citizen involvement and performance management in special-purpose governments. Public Administration Review, 67 2 , — Hevner, A. Design science in information systems research. MIS Quarterly, 28 1 , 75— Higgins, C.

Hochachka, W. Data-intensive science applied to broad-scale citizen science. Hopkins, N. Motivations for 21st century school children to bring their own device to school. Information Systems Frontiers, 19 5 , — Howe, J.

  • Jesus Killer: A Centurions Mission!
  • Children of the Cromlech;
  • Merlyna Lim!
  • Sweet Uncertainty.
  • Lucy and the witch (Tales for Telling Book 6).
  • New Releases;
  • Professor Gerard Goggin!

Crowdsourcing: How the power of the crowd is driving the future of business. New York: Random House. Proceedings of the 23rd international conference on World wide web pp. Seoul: ACM. Irwin A Citizen science: A study of people, expertise and sustainable development Psychology Press. Cincinnati, Ohio , 1— Syracuse, NY , 1— Jackson, M. Chapter twelve-recommendations for the next generation of global freshwater biological monitoring tools. Advances in Ecological Research, 55 , — Janssens, A. Research conducted using data obtained through online communities: Ethical implications of methodological limitations.

PLoS Medicine, 9 10 , e Jordan, J. Challenges to large-scale digital organization: The case of Uber. Journal of Organization Design, 6 1 , Kane, G. Research note—Content and collaboration: An affiliation network approach to information quality in online peer production communities. Information Systems Research, 27 2 , — A framework and research agenda. MIS Quarterly, 38 1 , — Kapoor, K. Advances in social media research: Past, present and future.

Information Systems Frontiers, 20 3 , — Khatib, F. Crystal structure of a monomeric retroviral protease solved by protein folding game players. Khoury, G. WeFold: A coopetition for protein structure prediction. Proteins Struct. Funct Bioinforma, 82 9 , — Kim S, Mankoff J, Paulos E Sensors: evaluating a flexible framework for authoring mobile data-collection tools for citizen science.

ACM , — Klein, H. Choosing between competing design ideals in information systems development. Information Systems Frontiers, 3 1 , 75— Korpela, E. Annual Review of Earth and Planetary Sciences, 40 , 69— Kosmala, M. Assessing data quality in citizen science. Frontiers in Ecology and the Environment, 14 10 , — Kullenberg, C.

What is citizen science? PLoS One, 11 1 , e