Academic literature on the topic 'Collaborative data usage'
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Journal articles on the topic "Collaborative data usage"
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Haguouche, Samira, and Zahi Jarir. "Towards a Secure and Borderless Collaboration between Organizations: An Automated Enforcement Mechanism." Security and Communication Networks 2018 (October 21, 2018): 1–13. http://dx.doi.org/10.1155/2018/1572812.
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During the last decade, organizations have been more and more aware of the benefits of engaging in collaborative activities. To attain a required collaborative objective, they are obligated to share sensitive resources such as data, services, and knowledge. However, sharing sensitive and private resources and exposing them for an external usage may prevent the organizations involved from collaborating. Therefore, this usage requires more preoccupation with security issues. Access control is one of these required security concerns. Several access control models are defined in the literature and this multitude of models creates heterogeneity of access control policies between the collaborating organizations. In this paper, we propose Access Control in Cross-Organizational coLLABoration ACCOLLAB, a solution for automatic mapping between heterogeneous access control policies in cross-organizational collaboration. To carry out this mapping, we suggest a mechanism founded mainly on XACML profiles and on a generic language derivative of XACML we define as Generic-XACML. We also formally prove that the mapping does not affect decision evaluation of policies. Thereby the proposed contribution ACCOLLAB allows each collaborating organization to communicate their access control policies and adopt other’s policies without affecting their existing access control systems.
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Ruijer, Erna, Stephan Grimmelikhuijsen, Jochem van den Berg, and Albert Meijer. "Open data work: understanding open data usage from a practice lens." International Review of Administrative Sciences 86, no. 1 (May 14, 2018): 3–19. http://dx.doi.org/10.1177/0020852317753068.
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During recent years, the amount of data released on platforms by public administrations around the world have exploded. Open government data platforms are aimed at enhancing transparency and participation. Even though the promises of these platforms are high, their full potential has not yet been reached. Scholars have identified technical and quality barriers of open data usage. Although useful, these issues fail to acknowledge that the meaning of open data also depends on the context and people involved. In this study we analyze open data usage from a practice lens – as a social construction that emerges over time in interaction with governments and users in a specific context – to enhance our understanding of the role of context and agency in the development of open data platforms. This study is based on innovative action-based research in which civil servants’ and citizens’ initiatives collaborate to find solutions for public problems using an open data platform. It provides an insider perspective of Open Data Work. The findings show that an absence of a shared cognitive framework for understanding open data and a lack of high-quality datasets can prevent processes of collaborative learning. Our contextual approach stresses the need for open data practices that work on the basis of rich interactions with users rather than government-centric implementations.
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SILVA, CHATHURANI, SANJAY MATHRANI, and NIHAL JAYAMAHA. "THE IMPACT OF ICT USAGE ON COLLABORATIVE PRODUCT INNOVATION PERFORMANCE." International Journal of Innovation Management 20, no. 05 (June 2016): 1640012. http://dx.doi.org/10.1142/s1363919616400120.
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Manufacturers are increasingly adopting collaborative product development (CPD) to achieve competitive advantage through joint synergies in introducing new products. Partners involved in CPD may be external such as suppliers and customers or internal cross-functional teams. As the number of dispersed partners increases, substantial rises in the use of information and communication technology (ICT) are evidenced in firms. Since most ICT implementations cost significantly to firms, uncovering a detailed picture of the effect of ICT usage on CPD performance would be immensely useful. Drawing on the relational resource-based view (RRBV), this study explores ICT impact on CPD performance comprising project performance and collaboration performance. Data collected from 244 collaborative product innovation projects were used. The study reveals positive direct and indirect impact of overall ICT usage on new product quality, commercial success, and time performance, through collaboration performance. The observed impact of three ICT usage aspects (frequency, proficiency, and intensity) and individual ICT types significantly contribute to extant literature while providing useful implications to product development practitioners.
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ANAYA, ANTONIO R., and JESÚS G. BOTICARIO. "A DOMAIN-INDEPENDENT, TRANSFERABLE AND TIMELY ANALYSIS APPROACH TO ASSESS STUDENT COLLABORATION." International Journal on Artificial Intelligence Tools 22, no. 04 (August 2013): 1350020. http://dx.doi.org/10.1142/s0218213013500206.
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Collaborative learning environments require intensive, regular and frequent analysis of the increasing amount of interaction data generated by students to assess that collaborative learning takes place. To support timely assessments that may benefit students and teachers the method of analysis must provide meaningful evaluations while the interactions take place. This research proposes machine learning-based techniques to infer the relationship between student collaboration and some quantitative domain-independent statistical indicators derived from large-scale evaluation analysis of student interactions. This paper (i) compares a set of metrics to identify the most suitable to assess student collaboration, (ii) reports on student evaluations of the metacognitive tools that display collaboration assessments from a new collaborative learning experience and (iii) extends previous findings to clarify modeling and usage issues. The advantages of the approach are: (1) it is based on domain-independent and generally observable features, (2) it provides regular and frequent data mining analysis with minimal teacher or student intervention, thereby supporting metacognition for the learners and corrective actions for the teachers, and (3) it can be easily transferred to other e-learning environments and include transferability features that are intended to facilitate its usage in other collaborative and social learning tools.
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Garrett, Alex, Karla Straker, and Cara Wrigley. "Digital channels for building collaborative consumption communities." Journal of Research in Interactive Marketing 11, no. 2 (June 12, 2017): 160–84. http://dx.doi.org/10.1108/jrim-08-2016-0086.
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Purpose Collaborative consumption firms leverage networked peers, communicating, collaborating and even delivering services to one another through a central marketplace channel. This raises questions as to the nature of this new form of digital channel strategy and deployment from a firm’s perspective. As a first step, this research seeks to help bridge the gap in knowledge by establishing an understanding of the digital channel usage of collaborative consumption firms. Design/methodology/approach A qualitative content analysis of 30 collaborative consumption firms was conducted using multiple data sources and coded into typologies against a predetermined coding scheme. These results were then compared against existing literature on digital channel usage in regards to a wider company usage. Findings This study identifies the digital channel usage and digital channel typology of each of the 30 firms associated within the collaborative consumption domain. The study shows a distinct increase in the use of social and community digital channels between traditional firms and collaborative consumption firms. As a result of this study, a concise definition of a collaborative consumption firm is provided, the digital channel usage of collaborative consumption firms is detailed and insights are provided for each sub-type of collaborative consumption. Research limitations/implications This study contributes to the understanding of the collaborative consumption phenomena, the business model of collaborative consumption firms and digital channels. This study assists in describing the shift from traditional firms to peer-to-peer systems. Finally, a theoretical model is provided that demonstrates the nuance of collaborative consumption channel choice within each subcategory for future researchers to test and reflect upon. Practical implications This study demonstrates how collaborative consumption firms are allowing customers to drive interaction rather than traditional business-to-customer messages. A theoretical model is provided which shows contemporary marketers how to best dictate a digital channel strategy for a collaborative consumption style initiative. Originality/value Contributions include: a definition of what a collaborative consumption firm and its channels pertain to and how to design a collaborative consumption digital channel strategy. This study presents a digital channel comparison between collaborative consumption firms and traditional organisations.
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Mohd Daud, Norzaidi, and Halimi Zakaria. "Impact of antecedent factors on collaborative technologies usage among academic researchers in Malaysian research universities." International Journal of Information and Learning Technology 34, no. 3 (May 6, 2017): 189–209. http://dx.doi.org/10.1108/ijilt-09-2016-0046.
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Purpose The purpose of this paper is to investigate the impact of antecedent factors on collaborative technologies usage among academic researchers in Malaysian research universities. Design/methodology/approach Data analysis was conducted on data collected from 156 academic researchers from five Malaysian research universities. This study employed an extensive quantitative approach of a structural equation modeling method to evaluate the research model and to test the hypotheses. Findings The main findings of this study are that personal innovativeness, task-technology fit, and perceived peer usage are significant predictors of individual usage of collaborative technologies; perceived managerial support and subjective norm were found not to be significant predictors to perceived usefulness and individual usage; and perceived usefulness is a significant mediator to individual usage in that it had fully mediated personal innovativeness whereas partially mediated peer usage. Practical implications The results provide practical insights into how the Malaysian higher education sector and other research organizations of not-for-profit structure could enhance their collaborative technologies usage. Originality/value This research is perhaps the first that concentrates on collaborative technologies usage in Malaysian research universities.
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Li, Patrick, Bob Chen, Evan Rhodes, Jason Slagle, Mhd Wael Alrifai, Daniel France, and You Chen. "Measuring Collaboration Through Concurrent Electronic Health Record Usage: Network Analysis Study." JMIR Medical Informatics 9, no. 9 (September 3, 2021): e28998. http://dx.doi.org/10.2196/28998.
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Background Collaboration is vital within health care institutions, and it allows for the effective use of collective health care worker (HCW) expertise. Human-computer interactions involving electronic health records (EHRs) have become pervasive and act as an avenue for quantifying these collaborations using statistical and network analysis methods. Objective We aimed to measure HCW collaboration and its characteristics by analyzing concurrent EHR usage. Methods By extracting concurrent EHR usage events from audit log data, we defined concurrent sessions. For each HCW, we established a metric called concurrent intensity, which was the proportion of EHR activities in concurrent sessions over all EHR activities. Statistical models were used to test the differences in the concurrent intensity between HCWs. For each patient visit, starting from admission to discharge, we measured concurrent EHR usage across all HCWs, which we called temporal patterns. Again, we applied statistical models to test the differences in temporal patterns of the admission, discharge, and intermediate days of hospital stay between weekdays and weekends. Network analysis was leveraged to measure collaborative relationships among HCWs. We surveyed experts to determine if they could distinguish collaborative relationships between high and low likelihood categories derived from concurrent EHR usage. Clustering was used to aggregate concurrent activities to describe concurrent sessions. We gathered 4 months of EHR audit log data from a large academic medical center’s neonatal intensive care unit (NICU) to validate the effectiveness of our framework. Results There was a significant difference (P<.001) in the concurrent intensity (proportion of concurrent activities: ranging from mean 0.07, 95% CI 0.06-0.08, to mean 0.36, 95% CI 0.18-0.54; proportion of time spent on concurrent activities: ranging from mean 0.32, 95% CI 0.20-0.44, to mean 0.76, 95% CI 0.51-1.00) between the top 13 HCW specialties who had the largest amount of time spent in EHRs. Temporal patterns between weekday and weekend periods were significantly different on admission (number of concurrent intervals per hour: 11.60 vs 0.54; P<.001) and discharge days (4.72 vs 1.54; P<.001), but not during intermediate days of hospital stay. Neonatal nurses, fellows, frontline providers, neonatologists, consultants, respiratory therapists, and ancillary and support staff had collaborative relationships. NICU professionals could distinguish high likelihood collaborative relationships from low ones at significant rates (3.54, 95% CI 3.31-4.37 vs 2.64, 95% CI 2.46-3.29; P<.001). We identified 50 clusters of concurrent activities. Over 87% of concurrent sessions could be described by a single cluster, with the remaining 13% of sessions comprising multiple clusters. Conclusions Leveraging concurrent EHR usage workflow through audit logs to analyze HCW collaboration may improve our understanding of collaborative patient care. HCW collaboration using EHRs could potentially influence the quality of patient care, discharge timeliness, and clinician workload, stress, or burnout.
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Durojaiye, Ashimiyu B., Scott Levin, Matthew Toerper, Hadi Kharrazi, Harold P. Lehmann, and Ayse P. Gurses. "Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data." Journal of the American Medical Informatics Association 26, no. 6 (March 19, 2019): 506–15. http://dx.doi.org/10.1093/jamia/ocy184.
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Abstract Objectives The study sought to identify collaborative electronic health record (EHR) usage patterns for pediatric trauma patients and determine how the usage patterns are related to patient outcomes. Materials and Methods A process mining–based network analysis was applied to EHR metadata and trauma registry data for a cohort of pediatric trauma patients with minor injuries at a Level I pediatric trauma center. The EHR metadata were processed into an event log that was segmented based on gaps in the temporal continuity of events. A usage pattern was constructed for each encounter by creating edges among functional roles that were captured within the same event log segment. These patterns were classified into groups using graph kernel and unsupervised spectral clustering methods. Demographics, clinical and network characteristics, and emergency department (ED) length of stay (LOS) of the groups were compared. Results Three distinct usage patterns that differed by network density were discovered: fully connected (clique), partially connected, and disconnected (isolated). Compared with the fully connected pattern, encounters with the partially connected pattern had an adjusted median ED LOS that was significantly longer (242.6 [95% confidence interval, 236.9–246.0] minutes vs 295.2 [95% confidence, 289.2–297.8] minutes), more frequently seen among day shift and weekday arrivals, and involved otolaryngology, ophthalmology services, and child life specialists. Discussion The clique-like usage pattern was associated with decreased ED LOS for the study cohort, suggesting greater degree of collaboration resulted in shorter stay. Conclusions Further investigation to understand and address causal factors can lead to improvement in multidisciplinary collaboration.
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Bai, Bing, Yushun Fan, Wei Tan, Jia Zhang, Keman Huang, and Jing Bi. "End-to-End Web Service Recommendations by Extending Collaborative Topic Regression." International Journal of Web Services Research 15, no. 1 (January 2018): 89–112. http://dx.doi.org/10.4018/ijwsr.2018010105.
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Mashup has emerged as a lightweight way to compose multiple web services and create value-added compositions. Facing the large amount of services, effective service recommendations are in great need. Service recommendations for mashup queries suffers from a mashup-side cold-start problem, and traditional approaches usually overcome this by first applying topic models to mine topic proportions of services and mashup queries, and then using them for subsequent recommendations. This solution overlooks the fact that usage record can provide a feedback for text extraction. Besides, traditional approaches usually treat all the usage records equally, and overlook the fact that the service usage pattern is evolving. In this article, the authors overcome these issues and propose an end-to-end service recommendation algorithm by extending collaborative topic regression. The result is a generative process to model the whole procedure of service selection; thus, usage can guide the mining of text content, and meanwhile, they give time-aware confidence levels to different historical usages. Experiments on the real-world ProgrammableWeb data set show that the proposed algorithm gains an improvement of 6.3% in terms of mAP@50 and 10.6% in terms of Recall@50 compared with the state-of-the-art methods.
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Jean-Quartier, Claire, Miguel Rey Mazón, Mario Lovrić, and Sarah Stryeck. "Collaborative Data Use between Private and Public Stakeholders—A Regional Case Study." Data 7, no. 2 (January 28, 2022): 20. http://dx.doi.org/10.3390/data7020020.
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Research and development are facilitated by sharing knowledge bases, and the innovation process benefits from collaborative efforts that involve the collective utilization of data. Until now, most companies and organizations have produced and collected various types of data, and stored them in data silos that still have to be integrated with one another in order to enable knowledge creation. For this to happen, both public and private actors must adopt a flexible approach to achieve the necessary transition to break data silos and create collaborative data sharing between data producers and users. In this paper, we investigate several factors influencing cooperative data usage and explore the challenges posed by the participation in cross-organizational data ecosystems by performing an interview study among stakeholders from private and public organizations in the context of the project IDE@S, which aims at fostering the cooperation in data science in the Austrian federal state of Styria. We highlight technological and organizational requirements of data infrastructure, expertise, and practises towards collaborative data usage.
Dissertations / Theses on the topic "Collaborative data usage"
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Oosthuizen, Ockmer Louren. "A multi-agent collaborative personalized web mining system model." Thesis, 2008. http://hdl.handle.net/10210/508.
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The Internet and world wide web (WWW) have in recent years, grown exponentially in size and in terms of the volume of information that is available on it. In order to effectively deal with the huge amount of information on the web, so called web search engines have been developed for the task of retrieving useful and relevant information for its users. Unfortunately, these web search engines have not kept pace with the boom growth and commercialization of the web. The main goal of this dissertation is the development of a model for a collaborative personalized meta-search agent (COPEMSA) system for the WWW. This model will enable the personalization of web search for users. Furthermore, the model aims to leverage on current search engines on the web as well as enable collaboration between users of the search system for the purposes of sharing useful resources between them. The model also employs the use of multiple intelligent agents and web content mining techniques. This enables the model to autonomously retrieve useful information for it’s user(s) and present this information in an effective manner. In order to achieve the above stated, the COPEMSA model employs the use of multiple intelligent agents. COPEMSA consists of five core components: a user agent, a query agent, a community agent, a content mining agent and a directed web spider. The user agent learns about the user in order to introduce personal preference into user queries. The query agent is a scaled down meta-search engine with the task of submitting the personalized queries it receives from the user agent to multiple search services on theWWW. The community agent enables the search system to communicate and leverage on the search experiences of a community of searchers. The content mining agent is responsible for analysis of the retrieved results from theWWWand the presentation of these results to the system user. Finally, a directed web spider is used by the content mining agent to retrieve the actual web pages it analyzes from the WWW. In this dissertation an additional model is also presented to deal with a specific problem all web spidering software must deal with namely content and link encapsulation.Prof. E.M. Ehlers
Books on the topic "Collaborative data usage"
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Products, LRC, Measures of Health (Firm), Henley Centre for Forecasting, and Nielsen Marketing Research, eds. The Durex report 1991: A summary of research into the usage of, and attitudes towards, condoms, conducted on behalf of LRC Products, manufacturers of the UK's leading condom brand, Durex, and incorporating data collected by Measures of Health, conducted by the Henley Centre in collaboration with Nielsen Market Research. [Great Britain]: [s.n.], 1991.
Find full textBook chapters on the topic "Collaborative data usage"
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Grčar, Miha, Dunja Mladenič, Blaž Fortuna, and Marko Grobelnik. "Data Sparsity Issues in the Collaborative Filtering Framework." In Advances in Web Mining and Web Usage Analysis, 58–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11891321_4.
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Gaudioso, Elena, and Jesus G. Boticario. "User Data Management and Usage Model Acquisition in an Adaptive Educational Collaborative Environment." In Lecture Notes in Computer Science, 143–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47952-x_16.
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Mohamed, Bahaaeldin, and Thomas Köhler. "The Fish Model: When Do Researchers Collaborate Online?" In Progress in IS, 29–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66262-2_3.
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AbstractThe questions of whether and how doctoral students are motivated for enhanced research collaboration deserve thorough consideration. Even though collaboration in general and its mediated forms, such as computer-supported cooperative work and collaborative learning (CSCW and CSCL), are prominent research topics, only a little is known about the methods necessary to design various activities to support research collaboration. With the upcoming generation of tools such as Mendeley, Conference Chair, ResearchGate, or Communote, scholars suspect that web 2.0 services play a decisive role in enabling and enhancing research collaboration. However, there is almost no data available on the extent to which researchers adopt these technologies, and how they do so. Therefore, the authors first present an overview of the current usage of web 2.0 among doctoral researchers in their daily academic routines, based on a survey (n = 140) conducted in the German Federal State of Saxony. It confirms a wide and often specified usage of web 2.0 services for research collaboration. For theoretical analysis, the authors propose a conceptual framework that reflects the requirements of scientific participation and scholarly collaboration within an average international doctoral programme adopting current digital technologies. The aim of this framework is to understand, support, and enhance research collaboration among doctoral researchers. Our fish model highlights the mutual relationship between the following dichotomous factors: (a) tasks/time factors; (b) beliefs/activities; (c) support/context; and (d) incentives/ethical issues. Our results indicate a significant relationship in terms of research collaboration. This relationship has particularly been identified between two dichotomous factors: beliefs/activities and incentives/ethics.
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Motti, Vivian Genaro, and Shlomo Berkovsky. "Healthcare Privacy." In Modern Socio-Technical Perspectives on Privacy, 203–31. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-82786-1_10.
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AbstractAs healthcare shifts towards the digital realm and healthcare delivery steers to patient-centric solutions, new privacy risks emerge. Such risks are acknowledged, but understanding and addressing them with privacy-enhanced technologies is practically challenging. This chapter describes privacy concerns and risks that emerge with the digitization of healthcare services, the availability of Internet-of-care-things, and the usage of online services for medical data. To ensure patients’ privacy, collaborative efforts from stakeholders are necessary. Patients, practitioners, and family members play an important role, along with medical organizations, including hospitals, insurance companies, and clinics. Privacy-preserving mechanisms go beyond the protection of patients’ data to the infrastructure of medical devices, networks, and systems. The data life cycle, from collection to disposal, must be considered when implementing privacy protections. Principles, policies, and regulations addressing privacy are limited and costly to implement, failing to cover novel technologies that collect and transmit medical data. In the USA, HIPAA is the de facto policy standard. Nevertheless, HIPAA disregards data collected by wearable sensors, fitness trackers, and smartwatches. It does not consider social media networks, mobile applications, and discussion forums where users share medical information. Lastly, genetic data available through online profiles rises privacy issues that are neither known nor regulated.
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Goram, Mandy, and Dirk Veiel. "Supporting Privacy Control and Personalized Data Usage Explanations in a Context-Based Adaptive Collaboration Environment." In Modeling and Using Context, 84–97. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34974-5_8.
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Hess, Anne. "Crossing Disciplinary Borders to Improve Requirements Communication." In Ernst Denert Award for Software Engineering 2020, 115–41. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83128-8_7.
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AbstractSoftware requirements specifications (SRS) serve as an important source of information for a variety of roles involved in software engineering (SE) projects. This situation poses a challenge to requirements engineers: Different information needs have to be addressed, which are strongly dependent on the particular role(s) that SRS stakeholders have within a project. This chapter summarizes the contributions of a thesis that aimed to address and reduce role-specific defects in SRS that negatively influence the efficient usage and acceptance of these documents. To achieve this goal, we collected empirical data about role-specific information needs in a series of empirical studies that served as a baseline for a secondary analysis toward the definition of role-specific views. Moreover, we realized a proof-of-concept implementation that is capable of generating role-specific views on SRS. The results of a case study revealed that role-specific views have the potential to efficiently support SRS consumers during the analysis of a given SRS. Besides conducting further empirical studies in industry, future work aims to foster cross-disciplinary collaboration and requirements communication, especially in agile teams. Thereby, we are exploring synergy potential with best practices from non-SE disciplines.
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Dai, Honghua, and Bamshad Mobasher. "Integrating Semantic Knowledge with Web Usage Mining for Personalization." In Data Warehousing and Mining, 3557–85. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-951-9.ch223.
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Web usage mining has been used effectively as an approach to automatic personalization and as a way to overcome deficiencies of traditional approaches such as collaborative filtering. Despite their success, such systems, as in more traditional ones, do not take into account the semantic knowledge about the underlying domain. Without such semantic knowledge, personalization systems cannot recommend different types of complex objects based on their underlying properties and attributes. Nor can these systems possess the ability to automatically explain or reason about the user models or user recommendations. The integration of semantic knowledge is, in fact, the primary challenge for the next generation of personalization systems. In this chapter we provide an overview of approaches for incorporating semantic knowledge into Web usage mining and personalization processes. In particular, we discuss the issues and requirements for successful integration of semantic knowledge from different sources, such as the content and the structure of Web sites for personalization. Finally, we present a general framework for fully integrating domain ontologies with Web usage mining and personalization processes at different stages, including the preprocessing and pattern discovery phases, as well as in the final stage where the discovered patterns are used for personalization.
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Zumbach, Joerg, Annette Hillers, and Peter Reimann. "Supporting Distributed Problem-Based Learning." In Online Collaborative Learning, 86–102. IGI Global, 2004. http://dx.doi.org/10.4018/978-1-59140-174-2.ch004.
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In this chapter we discuss possibilities and shortcomings of Internet usage for distributed problem-based learning. Several problems with the use of computer-mediated communication for collaborative learning online are identified. In our approaches we use data that is automatically tracked during computer-mediated communication and extract relevant information for feedback purposes. Partly automatically, partly manually prepared the feedback is a rich resource for learners to manage their own collaboration process as well as subsequent problem-solving processes. In a synchronous and an asynchronous distributed problem-based learning environment, we show how we applied this methodology to support learners’ motivation and problem solving. Analyses show encouraging benefits of our approach in overcoming common problems with computer-mediated communication.
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Boslau, Madlen, and Britta Lietke. "Consumer Attitudes toward RFID Usage." In Ubiquitous and Pervasive Computing, 1098–105. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-960-1.ch068.
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Ubiquitous computing environments grant organizations a multitude of dynamic context data emanating from embedded and mobile components. Such data may enhance organizations’ understanding of the different contexts in which they act. However, extant IS literature indicates that the utility of context data is frequently hampered by a priori interpretations of context embodied within the acquiring technologies themselves. Building on a 5-year canonical action research study within the Swedish transport industry, this paper reports an attempt to shift the locus of interpretation of context data by rearranging an assemblage of embedded, mobile, and stationary technologies. This was done by developing a vertical standard as a means to inscribe interpretive flexibility of context data. With the objective to extend the current understanding of how to enable crossorganizational access to reinterpretable context data, the paper contributes with an analysis of existing design requirements for context-aware ecosystems. This analysis reveals the complexity of accomplishing collaborative linkages between socio-technical elements in ubiquitous computing environments, and highlights important implications for research and practice.
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Ng, Wing Shui. "Web Data Mining in Education." In Advances in Data Mining and Database Management, 58–77. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1877-8.ch005.
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Web data mining for extracting meaningful information from large amount of web data has been explored over a decade. The concepts and techniques have been borrowed into the education sector and the new research discipline of learning analytics has emerged. With the development of web technologies, it has been a common practice to design online collaborative learning activities to enhance learning. To apply learning analytics techniques to monitor the online collaborative process enables a lecturer to make instant and informed pedagogical decisions. However, it is still a challenge to build strong connection between learning analytics and learning science for understanding cognitive progression in learning. In this connection, this chapter reports a study to apply learning analytics techniques in the aspect of web usage mining and clustering analysis with underpinning Bloom's taxonomy to analyze students' performance in the online collaborative learning process. The impacts of intermediate interventions are also elaborated.
Conference papers on the topic "Collaborative data usage"
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Reitenbach, S., M. Vieweg, C. Hollmann, and R. G. Becker. "Usage of Data Provenance Models in Collaborative Multi-Disciplinary Aero-Engine Design." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14139.
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Abstract The collaborative multi-disciplinary design of aircraft engines is a complex and highly iterative process. An essential characteristic of this design process is the involvement of a large number of experts from different disciplines, as well as the usage of numerous tools and workflows. Large amounts of data are produced and need to be exchanged via a multitude of interfaces. Furthermore, the data undergoes various transformations in the course of the design process. Understanding where a certain piece of data originates from and how it is connected to other datasets becomes therefore progressively essential. The purpose of this paper is to present a methodology to apply data provenance models in collaborative multi-disciplinary aero-engine design, supported by an approach for data standardization and identification. Besides the methodology, the software implementation to support this approach is presented in detail, including automated capturing and storage of provenance data, as well as methods for data investigation. In addition the presented methodology is evaluated by means of practical examples from the field of preliminary aero-engine design.
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Caldwell, Benjamin, and Gregory M. Mocko. "Product Data Management in Undergraduate Education." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-50015.
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Product Data Management (PDM) systems provide a means for sharing and controlling documents in collaborative product development. PDM are used in industrial applications for long-term archival of product information, to enhance collaboration and communication throughout the design process, support distributed design teams through advanced document sharing, track changes in product information, and control design documents ranging from requirements information to CAD. However, undergraduate mechanical engineering students typically graduate with limited or no exposure to PDM systems. This paper investigates the benefits and challenges associated with modern PDM systems. Moreover, the need for PDM systems in undergraduate education are discussed and means for integrating this technology is presented. A survey of engineering institutions in the U.S. is completed to understand the current usage in academic settings. Specifically, this paper describes appropriate course and project support of PDM systems.
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Batista, Matheus, Andréa Magdaleno, and Marcos Kalinowski. "A Survey on the use of Social BPM in Practice in Brazilian Organizations." In XIII Simpósio Brasileiro de Sistemas de Informação. Sociedade Brasileira de Computação, 2017. http://dx.doi.org/10.5753/sbsi.2017.6073.
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Social BPM is the combination of Business Process Management (BPM) with social and collaborative techniques for the purpose of exploring collaboration among stakeholders throughout the BPM lifecycle. Its goals are to reduce common problems in BPM by ensuring collaboration and transparency. To the best of our knowledge, there is no information on how Social BPM is being used in organizational environments and on its impacts. This study aims at showing how Brazilian organizations are using Social BPM practices and technologies. Therefore, a survey was conducted with employees from different companies in order to collect data on their usage of BPM collaborative practices. The survey received 31 replies and 3 of the respondents were also interviewed in order to provide depth to their answers and to enhance the overall understanding. The results show that collaboration happens predominantly in design, modeling, and improvement phases. Collaboration still happens mainly without formal planning and without tool support.
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Buzzetto-More, Nicole. "Navigating the Virtual Forest: How Networked Digital Technologies Can Foster Transgeographic Learning." In InSITE 2006: Informing Science + IT Education Conference. Informing Science Institute, 2006. http://dx.doi.org/10.28945/2948.
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During the past decade the globally networked digital technologies that operate within the realm of the internet have encouraged academicians and educators the world over to communicate, collaborate, and share knowledge. They have stimulated the creation of transgeographic educational initiatives which broaden the opportunities of learners and are an effective means of eradicating ethnocentrism, xenophobia, and cultural divides. The construction of transgeographic learning communities within the unmapped virtual forest of the internet requires an organized and systematic approach. Success is dependent on committed participants; a shared learning platform; a clear understanding of purpose; extensive student and instructor preparedness towards technology usage; exemplary curricula; a central focus for investigation; interaction with experts; extensive opportunities for intellectual discourse; and collaboration. The purpose of this paper is to offer an independent examination of a successful technology-dependent transgeographic learning project that serves as a model from which to base future projects. The Summer Ecosystems Experience for Undergraduates (SEE-U) is available to colleges and university students worldwide, operating at three geographically distinct locations concurrently. The program includes global networking, GPS and GIS usage, a shared investigative focus, real-time interactions, data collection, a globally networked geo-referenced digital database that was specifically created for this project, data manipulation, online lectures, bulletin board discussions, Web-based office hours, links to relevant resources, expert presenters, online demonstration videos, networked simulations, collaborative research, and a series of student presentations.
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Aduviri, Robert. "Feature Selection Algorithm Recommendation for Gene Expression data with Meta Learning." In LatinX in AI at Neural Information Processing Systems Conference 2019. Journal of LatinX in AI Research, 2019. http://dx.doi.org/10.52591/lxai2019120820.
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Feature selection is an important step in gene expression data analysis. However, many feature selection methods exist and a costly experimentation is usually needed to determine the most suitable one for a given problem. This paper presents the application of gradient boosting and neural network techniques for the construction of meta-models that can recommend rankings of {feature selection - classification} algorithm pairs for new gene expression classification problems through the usage of learning-to-rank and collaborative filtering approaches. Results in a corpus of 60 public datasets show the superiority of these techniques in producing more useful rankings in relation to classical meta-models
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Buzzetto-More, Nicole. "The IT Revolution: Applications and Strategies for Transgeographic Learning and Academia in the Twenty-First Century." In InSITE 2005: Informing Science + IT Education Conference. Informing Science Institute, 2005. http://dx.doi.org/10.28945/2874.
Full textAbstract:
Digital technologies are closing spatial and temporal gaps while engendering expansive new international communities. Replete with symbolic interactions, these transgeographic communities inspire new realms of educational possibility, allowing educators and learners to broaden perspectives through intellectual discourse and collaboration while eradicating cultural divides. The Summer Ecosystems Experience for Undergraduates (SEE-U) is a superior model of how such technology can be used to this end. Available to colleges and university students worldwide, the SEE-U program operates at three geographically distinct locations concurrently. The program includes global networking, GPS and GIS usage, real-time interactions, data collection, a globally networked geo-referenced digital database that was specifically created for this project, data manipulation, online lectures, bulletin board discussions, Web-based office hours, links to relevant resources, expert presenters, online demonstration videos, networked simulations, collaborative research, and a series of student presentations.
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Görl-Rottstädt, D., M. Heinrich-Zehm, M. Arnold, M. Köhler, and V. Hähnlein. "ONLINE TEACHING IN LOCKDOWN: ANALYSIS OF THE USAGE BEHAVIOUR OF COLLABORATIVE TOOLS BY STUDENTS AND TEACHERS IN THE CONTEXT OF HIGHER EDUCATION AND VOCATIONAL EDUCATION." In The 7th International Conference on Education 2021. The International Institute of Knowledge Management, 2021. http://dx.doi.org/10.17501/24246700.2021.7126.
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Due to the SARS-CoV-2 pandemic, many changes can be observed in almost all life situations, perhaps most notably, in the educational sector. In this context, concepts of learning counselling must be given more attention. This research contribution examines the question of how collaborative online tools to support the teaching-learning processes in higher education and vocational schools can be utilized. The aim is to improve the existing learning environment. For this purpose, the frequency of the usage of tools such as tests and forums on an open-source online learning platform ILIAS™ was analysed and discussed. In addition, the Adobe Connect™ web meeting software to be used in online teaching scenarios was also included in our investigation to explore the exchange of participants via discussion forums or virtual classrooms. The research team carried out an online sampling survey of ILIAS™ users at one university and five vocational schools in Germany in June 2020. The survey included these measures: Single answers, multiple answers, questions of scale, and free text questions. The response rate at the university was 25.10 % and at the vocational schools 17.2%. The data were evaluated with the help of descriptive statistics to determine frequency distributions and mean value calculations. This contribution will lead to a discussion regarding the continued disclosure of the learning potentials about a useful combination of both tools ILIAS™ and Adobe Connect™. The results shown suggest that the development towards virtual teaching scenarios, which has become a necessity under the forced conditions of the lockdowns, has a tremendous effect on teaching and learning processes in terms of didactics tailored to different target groups and needs in and outside the classroom. Keywords: Learning Consulting, Collaborative Learning, ILIAS™, Adobe Connect™
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Jahnke, Lori M., and Chris Palazzolo. "Collections Data, Tools, and Strategy: Applying R, Tableau, and Excel to Print Assessment." In Charleston Library Conference. Purdue Univeristy, 2020. http://dx.doi.org/10.5703/1288284317141.
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As is the case at most academic libraries, collection assessment has become an essential component of collection management and development work. Although much of the assessment focus has disproportionately fallen on e-resources, print collections remain fruitful areas for evaluation and review. At Emory, print collections, including a complex approval plan, continue to be a significant component of our overarching collection strategy (in volume and expenditure). However, shifting priorities for library space and the growth of interdisciplinary programs and centers within the University are placing a higher demand on subject librarians for communication and coordinated decision-making regarding print acquisitions. As a result, we are currently preparing for a comprehensive print collection review, of which the approval plan is an integral component. This assessment will inform a more coherent print strategy, which effectively and efficiently meets research and teaching requirements as well as administrative needs. Using data cleaning and visualization tools, such as R, Excel, and Tableau, we have enriched our local usage data with detailed Gobi approval data (e.g., series, publisher, subject, etc.) and profile parameters. Merging these data types and enriching local use data will allow us to analyze the print collection in a more nuanced fashion and ask questions that do not require the LC classification framework. This analysis considers the development of additional tools and approaches that facilitate subject specialist communication with collection management and overall collaborative decision-making, especially in cross disciplinary areas.
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Chang, Xiaomeng, and Janis Terpenny. "A Framework for Ontology-Based Heterogeneous Data Integration for Cost Management in Product Family Design." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49803.
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High quality, high impact and economical products and systems are important goals for an enterprise. The usage of product families can be strategic to achieving these goals, yet defining these families can be challenging, requiring the consideration of numerous cost factors. This requires bringing together a great number of heterogeneous data sources of varying formats in a manner that allows the product development team to easily locate and reuse information in a collaborative manner across time and space. To date, our work has focused on the development and use of an Activity-Based Cost ontology (ABC ontology) to guide designers drill down to get at information for product family design. However, this ontology is built in such a way that it can only support information retrieval from the ontology and does not bring together and connect heterogeneous data resources. It does not address the problem of designers who struggle with obtaining relevant details from different departments in an enterprise. While there have been several semantic data schema integration tools for heterogeneous data resources integration, these tools cannot guide users to related information, that would lead to the root cause of the high cost. In this paper, in order to better manage cost in product family design, an ontology-based framework is put forward that builds on our prior work and combines the advantages of ABC ontology and data schema integration tools. The ontology-based framework can guide users to the proper information aspects through querying the central ontology, and give users detailed information about these aspects from heterogeneous data resources with the support of local ontologies. Ultimately, this framework will facilitate designers with better utilization of cost-related factors for product family design from a whole enterprise perspective.
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Patterson, Michael K., Rainer Weidmann, Markus Leberecht, Manuel Mair, and Richard M. Libby. "An Investigation Into Cooling System Control Strategies for Data Center Airflow Containment Architectures." In ASME 2011 Pacific Rim Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Systems. ASMEDC, 2011. http://dx.doi.org/10.1115/ipack2011-52090.
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Data Center efficiency is critical to successful operation of today’s large IT installations. The reduction of infrastructure energy use will allow an increase in IT carrying capacity and / or a reduction in operating costs. The cooling portion of the data center Power Usage Effectiveness (PUE) can represent a significant cost and energy burden to the data center. The use of containment hardware (hot aisle, chimney, or cold aisle containment) is a good step in reducing the Data Center PUE; however the specifics of the implementation remains a challenge and some legacy controls strategies limit the efficacy of their use. The most typical control scheme in today’s data center is the return airflow temperature modulating a linked supply temperature and airflow. This control scheme is unsuitable for an advanced data center and limits the efficiency that can be gained with the containment strategy. But the optimal control scheme for a containment strategy remains a matter of discussion and debate. This paper reports on testing performed at our collaborative data center test lab facility in Munich, Germany where we have explored three different control designs for a containment strategy. The primary goal for energy savings in a containment strategy is to provide just enough cool air to the servers such that the server fans are satisfied without causing any recirculation to occur from the hot side of the containment. We investigated control based on temperature, pressure, and velocity measurements. The specifics of each are discussed as well as recommendations for choosing the appropriate controls. Practical considerations as well as system implementation recommendations are also shared. Each strategy can be made to work but the pressure control scenario provided the best level of control.
Reports on the topic "Collaborative data usage"
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Russell, H. A. J., and S. K. Frey. Canada One Water: integrated groundwater-surface-water-climate modelling for climate change adaptation. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329092.
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Canada 1 Water is a 3-year governmental multi-department-private-sector-academic collaboration to model the groundwater-surface-water of Canada coupled with historic climate and climate scenario input. To address this challenge continental Canada has been allocated to one of 6 large watershed basins of approximately two million km2. The model domains are based on natural watershed boundaries and include approximately 1 million km2 of the United States. In year one (2020-2021) data assembly and validation of some 20 datasets (layers) is the focus of work along with conceptual model development. To support analysis of the entire water balance the modelling framework consists of three distinct components and modelling software. Land Surface modelling with the Community Land Model will support information needed for both the regional climate modelling using the Weather Research & Forecasting model (WRF), and input to HydroGeoSphere for groundwater-surface-water modelling. The inclusion of the transboundary watersheds will provide a first time assessment of water resources in this critical international domain. Modelling is also being integrated with Remote Sensing datasets, notably the Gravity Recovery and Climate Experiment (GRACE). GRACE supports regional scale watershed analysis of total water flux. GRACE along with terrestrial time-series data will serve provide validation datasets for model results to ensure that the final project outputs are representative and reliable. The project has an active engagement and collaborative effort underway to try and maximize the long-term benefit of the framework. Much of the supporting model datasets will be published under open access licence to support broad usage and integration.
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Iatsyshyn, Anna V., Iryna H. Hubeladze, Valeriia O. Kovach, Valentyna V. Kovalenko, Volodymyr O. Artemchuk, Maryna S. Dvornyk, Oleksandr O. Popov, Andrii V. Iatsyshyn, and Arnold E. Kiv. Applying digital technologies for work management of young scientists' councils. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4434.
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The publication explores the features of the digital technologies’ usage to organize the work of the Young Scientists’ Councils and describes the best practices. The digital transformation of society and the quarantine restrictions caused by the COVID-19 pandemic have forced the use of various digital technologies for scientific communication, the organization of work for youth associations, and the training of students and Ph.D. students. An important role in increasing the prestige of scientific activity and encouraging talented young people to participate in scientific projects belongs to the Young Scientists’ Councils, which are created at scientific institutions and higher education institutions. It is determined that the peculiarities of the work of Young Scientists’ Councils are in providing conditions for further staff development of the institution in which they operate; contribution to the social, psychological and material support of young scientists and Ph.D. students; creating an environment for teamwork and collaborative partnership; development of leadership and organizational qualities; contribution to the development of digital competence. The advantages of using electronic social networks in higher education and research institutions are analyzed, namely: general popularity and free of charge; prompt exchange of messages and multimedia data; user-friendly interface; availability of event planning functions, sending invitations, setting reminders; support of synchronous and asynchronous communication between network participants; possibility of access from various devices; a powerful tool for organizing the learning process; possibility of organization and work of closed and open groups; advertising of various events, etc. Peculiarities of managing the activity of the Young Scientists’ Council with the use of digital technologies are determined. The Young Scientists’ Council is a social system, and therefore the management of this system refers to social management. The effectiveness of the digital technologies’ usage to manage the activities of the Young Scientists’ Council depends on the intensity and need for their use to implement organizational, presentation functions and to ensure constant communication. The areas to apply digital technologies for the work managing of Young Scientists’ Councils are sorted as the presentation of activity; distribution of various information for young scientists; conducting questionnaires, surveys; organization and holding of scientific mass events; managing of thematic workgroups, holding of work meetings. It is generalized and described the experience of electronic social networks usage for organizing and conducting of scientific mass events.
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Boone, Jonathan, Bobby Sells, Matthew Davis, and Dan McDonald. Alternative analysis for construction progress data spatial visualization. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42166.
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The U.S. Army Corps of Engineers (USACE) construction projects have multiple stakeholders that collaborate with project delivery team members during the execution of these projects. Many of these stakeholders are located across the U.S., which makes virtual interactions a common communication method for these teams. These interactions often lack spatial visualization, which can add complications to the progress reports provided and how the information is received/interpreted. The visualization of project progress and documents would be invaluable to the stakeholders on critical projects constructed by the USACE. This research was conducted to determine alternatives for migrating Resident Management System (RMS) data into a portal web viewer. This report provides proposed solutions to creating these links in efforts to better harmonize data management and improve project presentation.
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Kiianovska, N. M. The development of theory and methods of using cloud-based information and communication technologies in teaching mathematics of engineering students in the United States. Видавничий центр ДВНЗ «Криворізький національний університет», December 2014. http://dx.doi.org/10.31812/0564/1094.
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The purpose of the study is the analysis of the development of the theory and methods of ICT usage while teaching higher mathematics engineering students in the United States. It was determined following tasks: to analyze the problem source, to identify the state of its elaboration, to identify key trends in the development of theory and methods of ICT usage while teaching higher mathematics engineering students in the United States, the object of study – the use of ICT in teaching engineering students, the research methods are: analysis of scientific, educational, technical, historical sources; systematization and classification of scientific statements on the study; specification, comparison, analysis and synthesis, historical and pedagogical analysis of the sources to establish the chronological limits and implementation of ICT usage in educational practice of U.S. technical colleges. In article was reviewed a modern ICT tools used in learning of fundamental subjects for future engineers in the United States, shown the evolution and convergence of ICT learning tools. Discussed experience of the «best practices» using online ICT in higher engineering education at United States. Some of these are static, while others are interactive or dynamic, giving mathematics learners opportunities to develop visualization skills, explore mathematical concepts, and obtain solutions to self-selected problems. Among ICT tools are the following: tools to transmit audio and video data, tools to collaborate on projects, tools to support object-oriented practice. The analysis leads to the following conclusion: using cloud-based tools of learning mathematic has become the leading trend today. Therefore, university professors are widely considered to implement tools to assist the process of learning mathematics such properties as mobility, continuity and adaptability.
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Papí-Gálvez, Natalia, and Daniel La Parra-Casado. Informe 2022. Càtedra de Bretxa Digital Generacional. Les persones majors en l’era de la digitalització a la Comunitat Valenciana (Dades 2021). Càtedra de Bretxa Digital Generacional, 2022. http://dx.doi.org/10.14198/bua.2022.papi.infv.
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The Research Chair in the Generational Digital Divide undertakes activities aimed at furthering knowledge about the causes, consequences and solutions to the digital divides caused by age gaps. This report shows the research project carried out in 2021 to learn more about how the digital divide affects over 54s living in the Valencia Region, by province, with a focus on intergenerational relationships. To this end, an exploratory survey targeted at over 54s years old and over 39s years old in the Valencia Region, based on primary sources and combining quantitative and qualitative techniques, has been conducted. The data reveals that, while a large percentage of over 54s declare that they have access to and are users of new technologies, much remains to be done for access and usage to become universal, especially at older ages. The report analyses how technology is used, considering its purpose and context, according to age and other significant variables. Differences in technology usage have been found across age groups and between women and men. The report contains information on, among other relevant aspects, online services, and especially on e-banking, the healthcare system and e-administration. Differences between age groups have been found for all indicators, shedding light on intergenerational relationships within the family that are crucial for older people. The Research Chair is an initiative by the Valencia Region Government’s Directorate General for the Fight Against the Digital Divide and stems from the collaboration between the Regional Department for Innovation, Science, Universities and Digital Society and the University of Alicante.
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Papí-Gálvez, Natalia, and Daniel La Parra-Casado. Informe 2022. Cátedra de Brecha Digital Generacional. Las personas mayores en la era de la digitalización en la Comunidad Valenciana (datos 2021). Cátedra de Brecha Digital Generacional, 2022. http://dx.doi.org/10.14198/bua.2022.papi.infc.
Full textAbstract:
The Research Chair in the Generational Digital Divide undertakes activities aimed at furthering knowledge about the causes, consequences and solutions to the digital divides caused by age gaps. This report shows the research project carried out in 2021 to learn more about how the digital divide affects over 54s living in the Valencia Region, by province, with a focus on intergenerational relationships. To this end, an exploratory survey targeted at over 54s years old and over 39s years old in the Valencia Region, based on primary sources and combining quantitative and qualitative techniques, has been conducted. The data reveals that, while a large percentage of over 54s declare that they have access to and are users of new technologies, much remains to be done for access and usage to become universal, especially at older ages. The report analyses how technology is used, considering its purpose and context, according to age and other significant variables. Differences in technology usage have been found across age groups and between women and men. The report contains information on, among other relevant aspects, online services, and especially on e-banking, the healthcare system and e-administration. Differences between age groups have been found for all indicators, shedding light on intergenerational relationships within the family that are crucial for older people. The Research Chair is an initiative by the Valencia Region Government’s Directorate General for the Fight Against the Digital Divide and stems from the collaboration between the Regional Department for Innovation, Science, Universities and Digital Society and the University of Alicante.
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Suir, Glenn, Molly Reif, and Christina Saltus. Remote sensing capabilities to support EWN® projects : an R&D approach to improve project efficiencies and quantify performance. Engineer Research and Development Center (U.S.), August 2022. http://dx.doi.org/10.21079/11681/45241.
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Engineering With Nature (EWN®) is a US Army Corps of Engineers (USACE) Initiative and Program that promotes more sustainable practices for delivering economic, environmental, and social benefits through collaborative processes. As the number and variety of EWN® projects continue to grow and evolve, there is an increasing opportunity to improve how to quantify their benefits and communicate them to the public. Recent advancements in remote sensing technologies are significant for EWN® because they can provide project-relevant detail across a large areal extent, in which traditional survey methods may be complex due to site access limitations. These technologies encompass a suite of spatial and temporal data collection and processing techniques used to characterize Earth's surface properties and conditions that would otherwise be difficult to assess. This document aims to describe the general underpinnings and utility of remote sensing technologies and applications for use: (1) in specific phases of the EWN® project life cycle; (2) with specific EWN® project types; and (3) in the quantification and assessment of project implementation, performance, and benefits.
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Whitfield, Paula, Jenny Davis, Amanda Tritinger, Danielle Szimanski, Rebecca Golden, Joseph Gailani, Michael Ramirez, Brook Herman, Matt Whitbeck, and Jeffery King. Swan Island : monitoring and adaptive management plan. Engineer Research and Development Center (U.S.), August 2022. http://dx.doi.org/10.21079/11681/45044.
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Swan Island is a 10.12 ha island located in the Maryland waters of the Chesapeake Bay. Because of its value as a natural wave break for the town of Ewell on nearby Smith Island, as well as the ongoing erosion and subsidence of the island, in 2019 US Army Corps of Engineers (USACE)–Baltimore District placed 45,873 m³ of dredged sediment and planted 200,000 marsh plants. This restoration provided an opportunity to quantify the engineering (that is, resilience) and ecological performance of the island, postplacement. The lack of quantitative data on the performance of natural features such as islands has led to perceived uncertainties that are often cited as barriers to implementation. To address these data gaps, a multidisciplinary collaboration of five government entities identified project objectives and monitoring parameters through a series of mediated workshops and then developed a conceptual model to articulate those parameters and the linkages between them. This monitoring and adaptive management plan (MAMP) documents those monitoring parameters and procedures and can serve as an example for other scales, regions, and research questions. Documenting research and monitoring efforts may help to foster widespread acceptance of nature-based solutions such as islands.