Examples of using Distributed data collection projects in English and their translations into Slovenian
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Colloquial
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Official
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Medicine
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Ecclesiastic
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Financial
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Computer
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Official/political
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Programming
Table 5.3: Examples of distributed data collection projects in social research.
In addition to creating human computation and open call projects, researchers can also create distributed data collection projects.
In distributed data collection projects, volunteers contribute data about the world.
In addition to creating human computationand open call projects, researchers can also create distributed data collection projects.
In distributed data collection projects, volunteers contribute data about the world.
The design of PhotoCity also elegantly solves the sampling and data quality challenges of eBird andother distributed data collection projects.
Finally, distributed data collection projects are ideally suited for large-scale data collection. .
As it was in PhotoCity, the use of redundancy is an important principle for assessing andensuring data quality in distributed data collection projects.
In distributed data collection projects, researchers enable participants to contribute new measurements of the world.
EBird researchers have two main solutions to these data quality issues,issues that arise in many other distributed data collection projects.
Further, it shows that distributed data collection projects are not limited to tasks that people are already doing anyway, such as watching birds.
EBird researchers have two main solutions to these data quality issues-solutions that might be helpful in other distributed data collection projects as well.
Further, it shows that distributed data collection projects are not limited to tasks that people are already doing anyway, such as watching birds.
EBird researchers have two main solutions to these data quality issues-solutions that might be helpful in other distributed data collection projects as well.
In human computation and distributed data collection projects, moreover, the best form of quality control comes through redundancy, not through a high bar for participation.
However, eBird, and related projects, indicate that challenges related tosampling and data quality are concerns for distributed data collection projects.
In human computation and distributed data collection projects, on the other hand, the best form of quality control comes through redundancy, not a high bar for participation.
However, eBird, and related projects, indicate that challenges related to sampling anddata quality are concerns for distributed data collection projects.
In human computation and distributed data collection projects, moreover, the best form of quality control comes through redundancy, not through a high bar for participation.
As more projects take advantage oftechnology that enables de-skilled and passive participation, distributed data collection projects should dramatically increase in scale, enabling researchers to collect data that were simply off limits in the past.
Going forward, I suspect that many distributed data collection projects will begin to make use of capabilities of mobile phones that are already carried by billions of people around the world.
As more projects take advantage of technology that enables de-skilled andpassive participation, distributed data collection projects should dramatically increase in scale, enabling researchers to collect data that were simply off limits in the past.
Going forward, I suspect that many distributed data collection projects will begin to make use of capabilities of the mobile phones that are already carried by billions of people around the world.
In addition to creating human computation and open calls,researchers can also create a distributed data collection project.
EBird is a distributed data collection project that solicits information from birders around the world, and it has already received over 260 million bird sightings from 250,000 participants(Kelling, Fink, et al. 2015).
EBird is a distributed data collection project that solicits information from birders around the world, and it has already received over 260 million bird sightings from 250,000 participants(Kelling, Fink, et al. 2015).
Overall, the PhotoCity project shows that sampling and data quality are not insurmountable problems in distributed data collection.
Overall, the PhotoCity project shows that sampling and data quality are not insurmountable problems in distributed data collection.