2015
DOI: 10.1177/0002716215570007
|View full text |Cite
|
Sign up to set email alerts
|

From Big Data to Knowledge in the Social Sciences

Abstract: One of the challenges associated with high-volume, diverse datasets is whether synthesis of open data streams can translate into actionable knowledge. Recognizing that challenge and other issues related to these types of data, the National Institutes of Health developed the Big Data to Knowledge or BD2K initiative. The concept of translating “big data to knowledge” is important to the social and behavioral sciences in several respects. First, a general shift to data-intensive science will exert an influence on… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
27
0
1

Year Published

2016
2016
2023
2023

Publication Types

Select...
5
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 48 publications
(28 citation statements)
references
References 41 publications
0
27
0
1
Order By: Relevance
“…Many researchers [51][52][53][54][55] have concentrated on human mobility patterns, venue tagging, and check-in behavior toward using location-based social networks. Automatic venue tagging is one of the new concepts to observe spatial differences in many applications [56,57]. However, Gao and Liu [58] argued that when human mobility is integrated into an application that ranked locations based on a user's check-in history, temporal features were shown to be irrelevant.…”
Section: Related Workmentioning
confidence: 99%
“…Many researchers [51][52][53][54][55] have concentrated on human mobility patterns, venue tagging, and check-in behavior toward using location-based social networks. Automatic venue tagging is one of the new concepts to observe spatial differences in many applications [56,57]. However, Gao and Liu [58] argued that when human mobility is integrated into an application that ranked locations based on a user's check-in history, temporal features were shown to be irrelevant.…”
Section: Related Workmentioning
confidence: 99%
“…JITAIs are based on decision rules for determining when, where, and how interventions (i.e., recommendations, information, nudges) should be delivered in order to have optimal impact (12). Data collected through EMA can inform the development of intervention content and messages, as well as timing of intervention delivery for JITAIs targeting physical activity change.…”
Section: Future Directionsmentioning
confidence: 99%
“…Such standards have recently been deemed necessary in ensuring that data from research can be translated into “actionable knowledge” and have also been prioritized by US federal agencies (such as NOAA and NASA) in the domains of environmental and climate‐change studies (Hesse et al . ; Schaefer et al . ).…”
Section: Community‐based Observingmentioning
confidence: 99%
“…Successfully archiving and sharing data from research and scholarly work is increasingly seen as critical to the practice of science, and adherence to interoperability standards ensures that research results are available to users who could make use of the data (Austin et al 2015). Such standards have recently been deemed necessary in ensuring that data from research can be translated into "actionable knowledge" and have also been prioritized by US federal agencies (such as NOAA and NASA) in the domains of environmental and climatechange studies (Hesse et al 2015;Schaefer et al 2015). Consciously addressing interoperability standards not only increases the ability of CBO projects to share data, but also encourages adoption of data standards, thereby improving data quality.…”
Section: How Are Data Interoperability and Quality Ensured?mentioning
confidence: 99%