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elag_15.Rpres
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Hacking article processing charges
========================================================
author: Najko Jahn, Bielefeld University Library
date: 9 - 11 June
========================================================
```{r, echo =FALSE}
knitr::opts_chunk$set(
comment = "#>",
collapse = TRUE,
warning = FALSE,
message = FALSE,
echo = FALSE,
fig.width = 8,
fig.height = 4,5,
dpi=300,
out.width="1920px",
height="1080px"
)
```
# Please introduce yourself!
# What do you expect from the workshop?
Objectives
========================================================
The aim of this workshop is to gain a first understanding of how to collect, process and disseminate APCs paid as Open Data
**Day 1** Considering available skills and tools
**Day 2** Producing useful inputs for the library community
**Day 3** Presentation of workshop results
Motivation
========================================================
[Bielefeld University Library](http://www.ub.uni-bielefeld.de) has been in charge of local funds to support publications in Open Access Journals since 2008.
The funds [are supported by the DFG](http://www.dfg.de/en/research_funding/programmes/infrastructure/lis/funding_opportunities/open_access_publishing/index.html), thus certain conditions have to be met, e.g:
- Fee per article may not exceed 2,000 €
- Yearly reporting and application duties including determination of publication output, fees paid, work programme on how we manage APCs and complementary support
**Huge workload, which is only available for review :-(**
========================================================
APCs spent by Bielefeld University Library (2012 - 2014)
```{r, cache.lazy=TRUE}
apc <- read.csv("data/apc_de.csv", header = T, sep =",")
unibi <- apc[apc$Institution == "Bielefeld U",]
# massage
unibi$publisher <- factor(unibi$publisher,
levels = c(rownames(data.frame(rev(sort(tapply(unibi$EURO, list(unibi$publisher), sum)))))))
levels(unibi$publisher)[4:length(levels(unibi$publisher))] <- paste("other (n=", length(unique(unibi$publisher)) - 3, ")", sep="")
my.df <- aggregate(unibi$EURO, list(publisher = unibi$publisher, period = unibi$Period), sum)
require(ggplot2)
q <- ggplot(my.df, aes(factor(period), x, fill= publisher, group = publisher)) + geom_area(position="stack") + geom_line(position = "stack", colour="black")
q + scale_fill_manual("Publisher", values = c("#f39c12", "#2980b9", "#2ecc71", "#bdc3c7")) + xlab("Year") + ylab("APCs spent in EURO") + theme_minimal()
```
========================================================
# What is the value of making this information openly available?
# Discuss potential uses and applications!
Open Data Initiatives for APCs
========================================================
- [FWF shares spreadsheet via figshare](http://dx.doi.org/10.6084/m9.figshare.98875).
- [Wellcome Trust](http://blog.wellcome.ac.uk/2014/03/28/the-cost-of-open-access-publishing-a-progress-report/). Crowdsourcing through [Google Spreadsheet](https://docs.google.com/spreadsheets/d/1RXMhqzOZDqygWzyE4HXi9DnJnxjdp0NOhlHcB5SrSZo/edit).
- [JISC APC Pilot](https://www.jisc-collections.ac.uk/Jisc-APC-project/About-the-Jisc-APC-pilot/). [Data modell and search environment](https://github.com/JiscMonitor/allapc).
- [OpenAPC](https://github.com/openapc).
OpenAPC - Aim
=========================================================
The aim of this repository is:
- to release datasets on fees paid for Open Access journal articles by German Universities under an Open Database License
- to share a copy of [Directory of Open Access Journals (DOAJ)](http://doaj.org/) journal master list (downloaded January 2014)
- to demonstrate how reporting on fee-based Open Access publishing can be made more transparent and reproducible across institutions.
Dataset
==========================================================
```{r, echo=FALSE, cache = FALSE}
my.apc <- read.csv("data/apc_de.csv", header = TRUE, sep =",")
```
Information on both open access journal articles and open access publication of articles in toll-access journals ("hybrid") are provided.
In total, `r format(sum(my.apc$EURO), scientific=FALSE)`€ for `r nrow(my.apc)` articles were paid by the participating unviversities. Average fee is `r format(sum(my.apc$EURO)/nrow(my.apc), digits = 5)`€ and the median `r median(my.apc$EURO)`€.
======================================================
Coverage
```{r}
my.apc <- read.csv("data/apc_de.csv", header = TRUE, sep =",")
q <- ggplot(my.apc, aes(Institution, EURO)) + geom_boxplot() + geom_point(alpha = 8/10, size = 2,aes(colour =is_hybrid)) + scale_colour_manual(values = c("#000A02", "#DC4E00"))
q + ylab("Fees paid (in EURO)") + coord_flip() + theme(legend.position="top") + theme_bw()
```
======================================================
|Source |variable |description |
|:--------------|:---------|:-----------------------------------------------|
|CrossRef |`publisher` |Title of Publisher |
|CrossRef |`journal_full_title` |Full Title of Journal |
|CrossRef |`issn` |International Standard Serial Numbers (collapsed) |
|CrossRef |`issn_print` |ISSN print |
|CrossRef |`issn_electronic` |ISSN electronic |
|CrossRef |`license_ref` |License of the article |
|CrossRef |`indexed_in_CrossRef` |Is the article metadata registered with CrossRef? (logical) |
|EuropePMC |`pmid` |PubMed ID |
|EuropePMC |`pmcid` |PubMed Central ID |
|Web of Science |`ut` |Web of Science record ID |
|DOAJ |`DOAJ` |Is the journal indexed in the DOAJ? (logical) |
============================================================
# Are there any other sources we can use to enrich and disambiguate metadata on fees paid?
# List three complementary sources!
Tools
============================================================
We were inspired by the growing landscape of Open Science Tools, especially
1. Version control with Git and collaboration through GitHub
2. Clients that provide access to bibliographic data ([rOpenSci](https://ropensci.org/), [Librecat](http://librecat.org/))
3. Authoring tools such as [knitr](http://yihui.name/knitr/) and [R Markdown](http://rmarkdown.rstudio.com/) for automatic report generation
Ram, K. (2013). Git can facilitate greater reproducibility and increased transparency in science. Source Code Biol Med, 8(1), 7. doi:[10.1186/1751-0473-8-7](http://doi.org/10.1186/1751-0473-8-7)
============================================================
============================================================
# What other tools are available to make use of APC data?
# Introduce your favorite Open Data tool!
Preparing Day Two
============================================================
Potential works:
- Provide a pre-filled spreadsheet for participating libraries
- Explore interesting patterns in the data
- Support semantic versioning of the data
- Create dynamic reporting templates with RStudio
Please, team up!
Summarizing Day 1
=============================================================
**What is the value of making this information openly available?**
- help negotiations with publishers
- open model from the start helps to keep the model open
- promoting library services
- teaches Open Data to library staff
- bench marking across universities, funders and countries
=============================================================
**Are there any other sources we can use to enrich and disambiguate metadata on fees paid?**
<<<<<<< HEAD
- [http://www.scimagojr.com/](Scimago)
=======
- [Scimago](http://www.scimagojr.com/)
>>>>>>> gh-pages
- article-level metric, e.g. usage
- author id, e.g. ORCID, however privacy issues may need to be solved
- links to full text
- indexed by GoogleScholar
<<<<<<< HEAD
- kudos
=======
- [Kudos](https://www.growkudos.com/)
>>>>>>> gh-pages
=============================================================
**What other tools are available to make use of APC data?**
- Excel, GoogleDocs, Open Refine
- Email and shared file storage
- LibreCat provides a list of ETL-tools
- Text editors, Sublime, Atom
Summarizing Day 2
=============================================================
Hands-On: adding APC information to the [OpenAPC dataset](https://github.com/OpenAPC/openapc-de/).
Pipeline:
1. clean DOI list
2. enrich with disambiguated metadata from CrossRef, Europe PMC and DOAJ
3. merge with main spreadsheet
4. automatic generation of report
5. push to github
6. generate Word Document for the Head Librarian
==============================================================
**Documentation**
https://github.com/OpenAPC/elag_workshop_15
**OpenAPC**
https://github.com/OpenAPC/e
**Contact**
>>>>>>> gh-pages