scholarly journals Analysis on Survey Data of Special Physical Training for Skiers in Summer Training Based on Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Zheng Jinhui ◽  
Wang Sheng ◽  
Zheng Jinhong ◽  
Cai Guoliang ◽  
Cai Zhiqiang ◽  
...  
Keyword(s):  
Big Data ◽  
Survey Data ◽  
Physical Training ◽  
Current Situation ◽  
Training Effect ◽  
Natural Conditions

Due to the geographical and natural conditions, the development of skiing events is more resistant in China, and the training venues, methods, and concepts are insufficient, making it difficult for Chinese skiers to make some progress and aspire to the highest peak in this field. The purpose of this study is to explore and analyze the survey data of the professional physical training of skiers in summer training based on big data. Big data is employed to investigate and analyze the special physical training of skiers in summer training. Based on the data of professional physical training of skiers in summer training under big data, the current situation of skiers in summer training is examined, and the limitations are compared to improve the traditional physical training of skiers. Results show that the special physical training of skiers based on big data is more feasible in summer training, and the improvement of training effect is more obvious than traditional physical training. The training effect of the proposed method can more effectively solve the difficulties in summer training for skiers and understand the essentials of the action.

Role of Urban Big Data in Travel Behavior Research

2020 ◽  
pp. 036119812097502
Author(s):  
Chihuangji Wang ◽  
Daniel Baldwin Hess
Keyword(s):  
Big Data ◽  
Survey Data ◽  
Travel Behavior ◽  
Data Science ◽  
Location Based Service ◽  
Labor Costs ◽  
Public And Private ◽  
Public And Private Sector ◽  
Data Analytic

Understanding urban travel behavior (TB) is critical for advancing urban transportation planning practice and scholarship; however, traditional survey data is expensive (because of labor costs) and error-prone. With advances in data collection techniques and data analytic approaches, urban big data (UBD) is currently generated at an unprecedented scale in relation to volume, variety, and speed, producing new possibilities for applying UBD for TB research. A review of more than 50 scholarly articles confirms the remarkable and expanding role of UBD in TB research and its advantages over traditional survey data. Using this body of published work, a typology is developed of four key types of UBD—social media, GPS log, mobile phone/location-based service, and smart card—focusing on the features and applications of each type in the context of TB research. This paper discusses in significant detail the opportunities and challenges in the use of UBD from three perspectives: conceptual, methodological, and political. The paper concludes with recommendations for researchers to develop data science knowledge and programming skills for analysis of UBD, for public and private sector agencies to cooperate on the collection and sharing of UBD, and for legislators to enforce data security and confidentiality. UBD offers both researchers and practitioners opportunities to capture urban phenomena and deepen knowledge about the TB of individuals.

Is Bigger Always Better? Potential Biases of Big Data Derived from Social Network Sites

2015 ◽  
Vol 659 (1) ◽  
pp. 63-76 ◽  
Author(s):  
Eszter Hargittai
Keyword(s):  
Socioeconomic Status ◽  
Big Data ◽  
Social Network ◽  
Survey Data ◽  
Social Network Sites ◽  
Biased Sampling ◽  
Methodological Challenges ◽  
Internet Skills ◽  
The Social ◽  
Race Ethnicity

This article discusses methodological challenges of using big data that rely on specific sites and services as their sampling frames, focusing on social network sites in particular. It draws on survey data to show that people do not select into the use of such sites randomly. Instead, use is biased in certain ways yielding samples that limit the generalizability of findings. Results show that age, gender, race/ethnicity, socioeconomic status, online experiences, and Internet skills all influence the social network sites people use and thus where traces of their behavior show up. This has implications for the types of conclusions one can draw from data derived from users of specific sites. The article ends by noting how big data studies can address the shortcomings that result from biased sampling frames.

scholarly journals Connecting and linking neurocognitive, digital phenotyping, physiologic, psychophysical, neuroimaging, genomic, & sensor data with survey data

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Charles E. Knott ◽  
Stephen Gomori ◽  
Mai Ngyuen ◽  
Susan Pedrazzani ◽  
Sridevi Sattaluri ◽  
...  
Keyword(s):  
Big Data ◽  
Survey Data ◽  
Emergency Departments ◽  
Ecological Monitoring ◽  
Data Driven ◽  
Sensor Data ◽  
Trauma Patients ◽  
Long Term Effects ◽  
Digital Phenotyping ◽  
Data Elements

AbstractCombining survey data with alternative data sources (e.g., wearable technology, apps, physiological, ecological monitoring, genomic, neurocognitive assessments, brain imaging, and psychophysical data) to paint a complete biobehavioral picture of trauma patients comes with many complex system challenges and solutions. Starting in emergency departments and incorporating these diverse, broad, and separate data streams presents technical, operational, and logistical challenges but allows for a greater scientific understanding of the long-term effects of trauma. Our manuscript describes incorporating and prospectively linking these multi-dimensional big data elements into a clinical, observational study at US emergency departments with the goal to understand, prevent, and predict adverse posttraumatic neuropsychiatric sequelae (APNS) that affects over 40 million Americans annually. We outline key data-driven system challenges and solutions and investigate eligibility considerations, compliance, and response rate outcomes incorporating these diverse “big data” measures using integrated data-driven cross-discipline system architecture.

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