Automated Author ProfileHowison, Mark
0000-0002-0764-4090
Howison, Mark
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 11.2 (sum of 9 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Geocoding is an important tool for research, but precise street addresses and geospatial coordinates may risk revealing personally identifiable information if not used carefully. Censuscoding is a self-contained tool for determining the Census block group that contains a street address, to solve this challenge. Censuscoding maintains privacy by providing an anonymous view of location through block groups, which vary between 600 to 3,000 individuals in population. These replication files are used to build the lookup data distributed with censuscoding v0.2.0. Please see the corresponding GitHub repositories https://github.com/ripl-org/censuscoding and https://github.com/ripl-org/censuscoding-data.
Authors
- Howison, Mark
Geocoding is an important tool for research, but precise street addresses and geospatial coordinates may risk revealing personally identifiable information if not used carefully. Censuscoding is a self-contained tool for determining the Census block group that contains a street address, to solve this challenge. Censuscoding maintains privacy by providing an anonymous view of location through block groups, which vary between 600 to 3,000 individuals in population. These replication files are used to build the lookup data distributed with censuscoding v0.2.0. Please see the corresponding GitHub repositories https://github.com/ripl-org/censuscoding and https://github.com/ripl-org/censuscoding-data.
Authors
- Howison, Mark
A data resource, derived with natural-language processing techniques from over 42 million unstructured job postings in the National Labor Exchange, that empirically models the associations between occupation codes, skill keywords, job titles, and job descriptions in the United States during the years 2019 and 2021. This version of the data corresponds with the python package sockit v0.3.0 (https://github.com/ripl-org/sockit/releases/tag/v0.3.0) and sockit-data v0.3.0 (https://github.com/ripl-org/sockit-data/releases/tag/v0.3.0).
Authors
- Howison, Mark
A data resource, derived with natural-language processing techniques from over 42 million unstructured job postings in the National Labor Exchange, that empirically models the associations between occupation codes, skill keywords, job titles, and job descriptions in the United States during the years 2019 and 2021. This version of the data corresponds with the python package sockit v0.3.0 (https://github.com/ripl-org/sockit/releases/tag/v0.3.0) and sockit-data v0.3.0 (https://github.com/ripl-org/sockit-data/releases/tag/v0.3.0).
Authors
- Howison, Mark
This dataset contains text file snapshots from the National Drug Code Directory during the years 2000-2018, as available in the Internet Archive (web.archive.org) on April 11, 2018. The files span several database and formatting changes, but together they provide a more comprehensive list of National Drug Codes than are available in the most recent database snapshot (https://www.fda.gov/Drugs/InformationOnDrugs/ucm142438.htm).
Authors
- Howison, Mark ;
- Lawless, Ted ;
- Ucles, John
This dataset contains text file snapshots from the National Drug Code Directory during the years 2000-2018, as available in the Internet Archive (web.archive.org) on April 11, 2018. The files span several database and formatting changes, but together they provide a more comprehensive list of National Drug Codes than are available in the most recent database snapshot (https://www.fda.gov/Drugs/InformationOnDrugs/ucm142438.htm).
Authors
- Howison, Mark ;
- Lawless, Ted ;
- Ucles, John
The study "A Comprehensive Analysis of Primer IDs to Study Heterogeneous HIV-1 Populations" includes Illumina sequencing data deposited in the Sequence Read Archive and code for performing alignments and calling Primer ID consensus sequences, available from github. We have recomputed these intermediate alignment and consensus sequence results for use in other studies of HIV plasmid sequences.
Authors
- Howison, Mark
The study "A Comprehensive Analysis of Primer IDs to Study Heterogeneous HIV-1 Populations" includes Illumina sequencing data deposited in the Sequence Read Archive and code for performing alignments and calling Primer ID consensus sequences, available from github. We have recomputed these intermediate alignment and consensus sequence results for use in other studies of HIV plasmid sequences.
Authors
- Howison, Mark
No description available
Authors
- Zapata, Felipe ;
- Goetz, Freya E. ;
- Smith, Stephen A. ;
- Howison, Mark ;
- Siebert, Stefan ;
- Church, Samuel H. ;
- Sanders, Steven M. ;
- Ames, Cheryl Lewis ;
- McFadden, Catherine S. ;
- France, Scott C. ;
- Daly, Marymegan ;
- Collins, Allen G. ;
- Haddock, Steven H. D. ;
- Dunn, Casey W. ;
- Cartwright, Paulyn