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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm
|
|---|---|
| Published in |
BioData Mining, February 2015
|
| DOI | 10.1186/s13040-015-0037-5 |
| Pubmed ID | |
| Authors |
Xiuzhen Huang, Steven F Jennings, Barry Bruce, Alison Buchan, Liming Cai, Pengyin Chen, Carole L Cramer, Weihua Guan, Uwe KK Hilgert, Hongmei Jiang, Zenglu Li, Gail McClure, Donald F McMullen, Bindu Nanduri, Andy Perkins, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Karl Walker, Donald Wunsch, Donghai Xiong, Shuzhong Zhang, Yu Zhang, Zhongming Zhao, Jason H Moore |
| Abstract |
Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges. |
X Demographics
The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 36% |
| United Kingdom | 2 | 9% |
| Spain | 1 | 5% |
| Italy | 1 | 5% |
| Switzerland | 1 | 5% |
| Finland | 1 | 5% |
| France | 1 | 5% |
| Unknown | 7 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 50% |
| Scientists | 8 | 36% |
| Practitioners (doctors, other healthcare professionals) | 3 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Japan | 1 | 1% |
| Unknown | 68 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 17% |
| Researcher | 11 | 15% |
| Student > Ph. D. Student | 10 | 14% |
| Professor | 8 | 11% |
| Student > Doctoral Student | 6 | 8% |
| Other | 16 | 23% |
| Unknown | 8 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 14% |
| Biochemistry, Genetics and Molecular Biology | 8 | 11% |
| Agricultural and Biological Sciences | 8 | 11% |
| Business, Management and Accounting | 6 | 8% |
| Medicine and Dentistry | 6 | 8% |
| Other | 21 | 30% |
| Unknown | 12 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 January 2019.
All research outputs
#2,197,044
of 23,577,761 outputs
Outputs from BioData Mining
#41
of 315 outputs
Outputs of similar age
#32,478
of 355,596 outputs
Outputs of similar age from BioData Mining
#2
of 10 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 315 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 355,596 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.