2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Devi Premnath ◽  
Dr. C. Nateson

“Crowd sourcing” is a brand new concept which has started to make wave in the field of management'. It refers to the process of outsourcing of activities to an online community or crowd in the form of an open call. Any member of the crowd can complete the assignment who will then be paid for his efforts. This phenomenon is increasingly noticed in the field of advertising where companies have started generating ideas and strategies of advertisement from crowd, for a better realistic approach. The process is speedy and is less expensive in terms of time and money. This paper is an attempt to put light on the various nuances of “crowd sourcing”, the methodologies involved and its impacts related to competitive segment of business. The success mantra of crowd sourcing is the power of crowd that drives the future of management.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 57036-57048 ◽  
Author(s):  
Xinxin Wang ◽  
Danyang Qin ◽  
Ruolin Guo ◽  
Min Zhao ◽  
Lin Ma ◽  
...  

2021 ◽  
Author(s):  
Arthur Lackner ◽  
Said Fathalla ◽  
Mojtaba Nayyeri ◽  
Andreas Behrend ◽  
Rainer Manthey ◽  
...  

AbstractThe publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.


2014 ◽  
Vol 23 (01) ◽  
pp. 27-35 ◽  
Author(s):  
S. de Lusignan ◽  
S-T. Liaw ◽  
C. Kuziemsky ◽  
F. Mold ◽  
P. Krause ◽  
...  

Summary Background: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive. Objective: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines. Method: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars. Results: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowd-sourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the “internet of things”, and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources. Conclusions: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.


2015 ◽  
Vol 6 (4) ◽  
pp. 30-38
Author(s):  
SOBIROV BAKHTISHODOVICH BOBUR ◽  
KHAMIDOV OBIDJON ◽  
OLIM MAMAYUNUSOVICH PARDAEV ◽  
RAMOS RAMOS SERGIO ◽  
SOLIEV BOBIRSHOYEVICH MUKHAMMADKHON ◽  
...  

2016 ◽  
Vol 198 (6) ◽  
pp. 877-877
Author(s):  
Katrina T. Forest ◽  
Ann M. Stock
Keyword(s):  

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