| Title |
Experiences and challenges in building a data intensive system for data migration
|
|---|---|
| Published in |
Empirical Software Engineering, February 2017
|
| DOI | 10.1007/s10664-017-9503-7 |
| Authors |
Marco Scavuzzo, Elisabetta Di Nitto, Danilo Ardagna |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 27% |
| Researcher | 6 | 13% |
| Student > Master | 6 | 13% |
| Student > Doctoral Student | 4 | 9% |
| Student > Bachelor | 2 | 4% |
| Other | 7 | 16% |
| Unknown | 8 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 60% |
| Engineering | 3 | 7% |
| Business, Management and Accounting | 2 | 4% |
| Social Sciences | 1 | 2% |
| Earth and Planetary Sciences | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 11 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 04 May 2018.
All research outputs
#17,945,904
of 23,043,346 outputs
Outputs from Empirical Software Engineering
#558
of 709 outputs
Outputs of similar age
#223,947
of 309,525 outputs
Outputs of similar age from Empirical Software Engineering
#17
of 18 outputs
Altmetric has tracked 23,043,346 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 709 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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 309,525 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.