This package was developed during ozunconf19 and numbat hackathon 2020, to provide tools and ideas that will help gather the information required to apply for academic promotion.
This document was produced by Chris Brown, Belinda Fabian, Rob Hyndman, Maria Prokofiave, Nick Tierney, Huong Ly Tong, and Melina Vidoni,
You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("ropenscilabs/Rcademy")Typically, an application for academic promotion will require you to provide evidence of your performance in Research, Teaching, Engagement and (for senior appointments) Leadership. The rest of this document summarises what sort of things you could include in each of these sections.
For research, you will need a list of publications, the number of citations, and the ranking of the journals in which you have published
You can obtain a list of your publication from various sources, either a bib file, or from an online list such as PubMed, Google Scholar or Orcid. Normally you would only need to use one of these.
library(tidyverse)
#> ── Attaching packages ──────────────────────────────────────────────────────── tidyverse 1.3.0 ──
#> ✓ ggplot2 3.3.1 ✓ purrr 0.3.4
#> ✓ tibble 3.0.1 ✓ dplyr 1.0.0
#> ✓ tidyr 1.1.0 ✓ stringr 1.4.0
#> ✓ readr 1.3.1 ✓ forcats 0.5.0
#> ── Conflicts ─────────────────────────────────────────────────────────── tidyverse_conflicts() ──
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag() masks stats::lag()
library(rcademy)mypubs_bib <- read_bib("mypubs.bib")
mypubs_pubmed <- read_pubmed("Rob Hyndman")
mypubs_scholar <- read_scholar("vamErfkAAAAJ")
mypubs_orcid <- read_orcid("0000-0002-2140-5352")Each of these functions will return a tibble, with one row per publication and the columns providing information such as title, authors, year of publication, etc. The different sources provide some different information, and it is often useful to combine them. We will use the last two of these (from Google Scholar and ORCID) in the following examples.
mypubs_orcid
#> # A tibble: 142 x 8
#> journal title year volume issue pages type doi
#> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 International Jou… On continuous-t… 1992 <NA> <NA> <NA> <NA> <NA>
#> 2 Journal of Time S… YULE-WALKER EST… 1993 14 3 281-… journ… 10.1111/…
#> 3 Journal of Applie… Approximations … 1994 31 4 1103… journ… 10.2307/…
#> 4 Journal of Foreca… Highest-density… 1995 14 5 431-… journ… 10.1002/…
#> 5 The American Stat… Sample Quantile… 1996 50 4 361 journ… 10.2307/…
#> 6 The American Stat… Sample Quantile… 1996 50 4 361-… journ… 10.1080/…
#> 7 The American Stat… Computing and G… 1996 50 2 120 journ… 10.2307/…
#> 8 The American Stat… Computing and G… 1996 50 2 120-… journ… 10.1080/…
#> 9 Journal of Comput… Estimating and … 1996 5 4 315-… journ… 10.1080/…
#> 10 Journal of the Ro… Some properties… 1997 <NA> <NA> <NA> <NA> <NA>
#> # … with 132 more rows
mypubs_scholar
#> # A tibble: 289 x 8
#> title author journal number cites year cid pubid
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 Forecasting … S Makridakis… "John Wil… "" 5826 1998 73093598359… u5HH…
#> 2 Another look… RJ Hyndman, … "Internat… "22 (4… 3160 2006 13549848342… 9yKS…
#> 3 Automatic ti… RJ Hyndman, … "Journal … "" 2162 2007 16678312313… YsMS…
#> 4 Forecasting:… RJ Hyndman, … "OTexts" "" 2109 2018 71756992424… CrVL…
#> 5 Forecasting … RJ Hyndman, … "Springer… "" 1063 2008 88418756642… UeHW…
#> 6 Detecting tr… J Verbesselt… "Remote s… "114 (… 1003 2010 47121712280… 5nxA…
#> 7 25 years of … JG De Gooije… "Internat… "22 (3… 935 2006 33143054759… Tyk-…
#> 8 Sample quant… RJ Hyndman, … "The Amer… "50 (4… 880 1996 25243146458… u-x6…
#> 9 A state spac… RJ Hyndman, … "Internat… "18 (3… 782 2002 44453997602… 2osO…
#> 10 forecast: Fo… RJ Hyndman, … "" "" 739 2018 16844150736… UbXT…
#> # … with 279 more rowsIn general, ORCID will provide higher quality data, along with DOIs, but has no citation information and covers fewer publications than Google Scholar. A few papers may have two DOIs — for example, when they appear on both JStor and a journal website. We will remove these.
library(tidystringdist)
dups <- mypubs_orcid %>%
select(title, year) %>%
mutate_all(tolower) %>%
duplicated()
mypubs_orcid <- mypubs_orcid %>% filter(!dups)We will try to combine the two tibbles using fuzzy joining on the title and year fields.
mypubs <- mypubs_scholar %>%
# First remove any publications without years
filter(!is.na(year)) %>%
# Now find matching entries
fuzzyjoin::stringdist_left_join(mypubs_orcid,
by = c(title = "title", year = "year"),
max_dist = 2, ignore_case = TRUE) %>%
# Keep any columns where ORCID missing
mutate(
title.y = if_else(is.na(title.y), title.x, title.y),
journal.y = if_else(is.na(journal.y), journal.x, journal.y),
year.y = if_else(is.na(year.y), year.x, year.y),
) %>%
# Keep the ORCID columns
select(!ends_with(".x")) %>%
rename_all(~str_remove_all(.x,".y"))
mypubs
#> # A tibble: 301 x 13
#> author number cites cid pubid journal title year volume issue pages pe
#> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr>
#> 1 S Mak… "" 5826 7309… u5HH… "John … Fore… 1998 <NA> <NA> <NA> <NA>
#> 2 RJ Hy… "22 (… 3160 1354… 9yKS… "Inter… Anot… 2006 22 4 679-… jour…
#> 3 RJ Hy… "" 2162 1667… YsMS… "Journ… Auto… 2008 <NA> <NA> <NA> <NA>
#> 4 RJ Hy… "" 2109 7175… CrVL… "OText… Fore… 2018 <NA> <NA> <NA> <NA>
#> 5 RJ Hy… "" 1063 8841… UeHW… "Sprin… Fore… 2008 <NA> <NA> <NA> <NA>
#> 6 J Ver… "114 … 1003 4712… 5nxA… "Remot… Dete… 2010 114 1 106-… jour…
#> 7 JG De… "22 (… 935 3314… Tyk-… "Inter… 25 y… 2006 22 3 443-… jour…
#> 8 RJ Hy… "50 (… 880 2524… u-x6… "The A… Samp… 1996 50 4 361 jour…
#> 9 RJ Hy… "18 (… 782 4445… 2osO… "Inter… A st… 2002 18 3 439-… jour…
#> 10 RJ Hy… "" 739 1684… UbXT… "" fore… 2018 <NA> <NA> <NA> <NA>
#> # … with 291 more rows, and 1 more variable: doi <chr>You can add journal rankings for each publication, choosing between ABDC, CORE and SCImago.
mypubs <- mypubs %>%
mutate(
abdc_ranking = rank_abdc(journal),
core_ranking = rank_core(journal),
scimago_ranking = rank_scimago(journal)
)Then you can create a table of the number of papers by rank.
mypubs %>%
filter(!is.na(abdc_ranking)) %>%
count(abdc_ranking) The tibble contains Google scholar citations for all papers, you can use
the data obtained with read_scholar() which contains a cites column.
We can also obtain CrossRef citations via the citations() function
which uses the DOI codes.
mypubs %>%
mutate(cr_cites = citations(doi)) %>%
select(title, year, cites, cr_cites) %>%
arrange(desc(cites))
#> # A tibble: 301 x 4
#> title year cites cr_cites
#> <chr> <dbl> <dbl> <dbl>
#> 1 Forecasting methods and applications 1998 5826 NA
#> 2 Another look at measures of forecast accuracy 2006 3160 1461
#> 3 Automatic time series forecasting: The forecast package… 2008 2162 NA
#> 4 Forecasting: principles and practice 2018 2109 NA
#> 5 Forecasting with exponential smoothing: the state space… 2008 1063 NA
#> 6 Detecting trend and seasonal changes in satellite image… 2010 1003 648
#> 7 25 years of time series forecasting 2006 935 597
#> 8 Sample Quantiles in Statistical Packages 1996 880 100
#> 9 A state space framework for automatic forecasting using… 2002 782 349
#> 10 forecast: Forecasting functions for time series and lin… 2018 739 NA
#> # … with 291 more rowsAltmetrics can also be useful. For this, you will need the list of your DOIs.
mypubs %>%
get_altmetrics(doi) %>%
select(title, cited_by_tweeters_count) %>%
arrange(desc(cited_by_tweeters_count))
#> # A tibble: 39 x 2
#> title cited_by_tweeters_c…
#> <chr> <dbl>
#> 1 Handgun Acquisitions in California After Two Mass Shoot… 41
#> 2 Exploring the sources of uncertainty: Why does bagging … 16
#> 3 Associations between outdoor fungal spores and childhoo… 15
#> 4 Point and interval forecasts of mortality rates and lif… 12
#> 5 A Feature‐Based Procedure for Detecting Technical Outli… 12
#> 6 Forecasting Time Series With Complex Seasonal Patterns … 8
#> 7 Forecasting with temporal hierarchies 7
#> 8 Do human rhinovirus infections and food allergy modify … 6
#> 9 A note on upper bounds for forecast-value-added relativ… 6
#> 10 Grouped Functional Time Series Forecasting: An Applicat… 5
#> # … with 29 more rowsThe scholar package provides tools for obtaining your profile
information.
scholar::get_profile("vamErfkAAAAJ")
#> $id
#> [1] "vamErfkAAAAJ"
#>
#> $name
#> [1] "Rob J Hyndman"
#>
#> $affiliation
#> [1] "Professor of Statistics, Monash University"
#>
#> $total_cites
#> [1] 31532
#>
#> $h_index
#> [1] 63
#>
#> $i10_index
#> [1] 150
#>
#> $fields
#> [1] "verified email at monash.edu - homepage"
#>
#> $homepage
#> [1] "http://robjhyndman.com/"
#>
#> $coauthors
#> [1] "George Athanasopoulos" "Ralph Snyder"
#> [3] "Han Lin Shang" "Kate Smith-Miles"
#> [5] "Keith Ord" "Spyros Makridakis"
#> [7] "Bircan Erbas" "Fotios Petropoulos"
#> [9] "Christoph Bergmeir" "Heather Booth"
#> [11] "Jan Verbesselt" "Souhaib Ben Taieb"
#> [13] "Darius Culvenor" "Mitchell O'Hara-Wild"
#> [15] "Muhammad Akram" "Michael Abramson"
#> [17] "Leonie Tickle" "Shyamali Chandrika Dharmage"
#> [19] "Roman Ahmed" "Glenn Newnham"The teaching section will usually involve collecting data on your teaching performance and teaching innovations.
- Student evaluations
- Emails from grateful students
- Peer review reports
- Development of new subjects or degrees
- New teaching methods or materials
- Honours students supervised
- Masters students supervised
- PhD students supervised
Note that a list of PhD students may go in the Research section rather than the Teaching section.
This section includes suggestions for engagement activities that could be included in academic promotion applications. These examples are indicative only and do not provide a list of expectations. Engagement is interpreted in a broad sense to include discipline, industry, government and community engagement.
- Partnerships with organisations: for profit, not-for-profit, volunteering
- Consulting projects -> could list value of projects, reports completed
- Participation in project development programs e.g. CSIRO On Prime
- Patents
- Service on industry boards and/or committees at the local, state or national level
- Policy development, such as changes resulting from your work
- Advocacy programs e.g. Science Meets Parliament
- Service with government bodies
- Public presentations - list of locations
- Blogging (own blog or collaborative), with stats available from blog backend e.g. views, visitors, followers.
- Twitter. Such as number of followers from profile, Twitter analytics shows impressions, engagement rate, likes, retweets, replies (only allows viewing of the last 90 days of data).
- Community programs e.g. National Science Week, etc.
- Media appearances e.g. appearances on TV, radio, web.
- Writing for general audience e.g. The Conversation, university news platforms (e.g. The Lighthouse).
- Public works e.g. art installations, consulting on museum exhibit.
- Service on community boards and/or committees at the local, state or national level.
- Contributions to community support websites e.g. Stack Overflow
- Data science competitions e.g. Kaggle
- Community engagement projects e.g. citizen science
- Community development e.g. meetup groups, RLadies, rOpenSci, hackathons
- Creation of software packages/tools for open use
- Curriculum development e.g. STEM at School.
- Interactions with school students e.g. Skype a Scientist (discussing science with students).
- University events e.g. Open Day.
- Establishing student links with industry/professional societies.
- Participating in professional practice teaching e.g. teamwork, communication, problem solving, grant writing.
- Professional society membership & activity.
- Membership of professional or foundation boards/councils
- Peer review (It should go into the research section). This can include: journal article review, ARC college of experts, grant review panels.
This section includes examples of leadership activities in academic promotion applications.
- University committee (e.g. department, faculty, university-level). List how many events/meetings you have in a year.
- Board membership, and list position, length of service.
- Conference organisation. List your role (e.g. scientific committee, symposium chair), scale of conference (e.g number of attendees, funding, international/local).
- Leading projects and initiatives (e.g. sustainability, diversity inclusion initiatives).
- Event organisation (e.g. writing retreat).
- Training events (e.g. university management course). List the course, completion date.
- Leadership roles in external professional or industry associations
- Mentoring. List how many mentees you have, length of relationship, where they are working now.