This chapter of the Administrator’s Guide provides a general overview of usage statistics in Open Journal Systems (OJS) and by extension in Open Monograph Press (OMP). It contains general usage guidelines for common scenarios suitable for editors and journal managers to use. It also contains a fair bit of technical detail suitable for systems administrators. Where possible we have tried to distinguish between both areas of expertise.
The development of this chapter has been funded by the Government of Canada via a grant from Canadian Heritage and by the Canadian Association of Learned Journals / Association canadienne des revues savantes. Public Knowledge Project provided additional in-kind assistance toward the development of this project.
To best use this document, it is necessary to understand the following definitions as they relate to Open Journal Systems (OJS).
“What counts as a view” can seem like a straightforward enough question when considering article use metrics, but there are any number of ways to provide - or complicate - the answer. Answering this question depends on which counting mechanism is being used (e.g., Google Analytics vs. log file hits vs. filtered metrics), whether attempting to review historical data spans different methodologies, and whether these methodologies have been configured correctly or not.
This handbook mainly serves to explain, in some detail, how to configure, use, and troubleshoot PKP’s Usage Statistics Framework. It also contains some information on other statistics-gathering methods that are supported by OJS.
OJS has recorded article usage since the beginning of the launch of OJS 2. The methodology used to count metrics has undergone one significant change between then and now. That change is key to understanding how to review and manage historical statistical data.
Versions of OJS prior to OJS 2.4.3 count views in a very rudimentary manner: they record page views and file downloads for article landing pages and galley files only and do not filter out bot views/downloads, multiple clicks, and so on. These views are recorded in a simple database table and represented in OJS 2.4.2 and below via a “View” report. Metrics are only available for abstract/landing pages and galley downloads and only track one facet: whether the item was viewed or downloaded. These counts are considered accurate though possibly misrepresentative of actual readership, as bot views, crawler indexing, and potential author or visitor abuse (eg. multi-clicking) are not filtered out.
As of version 2.4.3, Open Journal Systems uses a new structure for collecting statistics and generating reports. These metrics count abstract and galley views, date viewed, and regional information like country and city (if properly configured). Beyond article metrics, issue and homepage views are also included. Finally, these metrics are filtered according to COUNTER Project processing rules so that multi-clicks and bot views are filtered by default.
The following describes the data to which users of various iterations of OJS have access. The OJS version can be determined by a journal staff member by visiting About > About this Publication System (OJS 2).
OJS’ reports can be broadly grouped into “usage” reports that contain usage metrics indicative of visitor readership and “content” reports that provide data on the respective item (eg. subscriber info). Some of these reports also contain legacy information, provided that your OJS install was created at some point before OJS 2.4.3. OJS 3 has dropped support for legacy reports.
To generate reports in OJS 3.x, log in as Journal Manager and go to Tools > Statistics.
To generate reports in OJS 2.x, log in as Journal Manager and go to User Home > Stats & Reports.
The following table is a quick cheatsheet and comparison tool for each report; more detailed descriptions of each report follow.
|Name||Description||Contents||Legacy||OJS 2||OJS 3|
|Timed Views||Provides article and galley views by date span. Can be used to retrieve legacy or current data.||Usage||Y/N||Y||N|
|View||Provides overall usage counts for abstract/landing page and galley downloads, per article.||Usage||Y||Y||N|
|Usage Statistics||Provides granular daily usage metrics for all article, article file, issue and homepage views/downloads. Will include visitor country data, if that is being logged.||Usage||N||Y||Y|
|Custom Report Generator||Customizable version of the Usage Statistics report, where various facets can be selected and specific date spans can be set.||Usage||N||Y||Y|
|COUNTER||Provides COUNTER reports for all journals on the OJS application. Provides monthly and year to date aggregate counts for abstract and galley views.||Usage||N||Y||Y|
|Articles||Provides general information on all articles in the system, incl. Title, abstract, authors, editor decision, and status.||Content||N||Y||Y|
|Subscriptions||Provides information on any individual and institutional subscriptions.||Content||N||Y||Y|
|Review||Provides review information on all articles in the system, incl. reviewer names, reviews, and recommendation.||Content||N||Y||Y|
Availability: OJS 2 only
Description: This report provides overall usage metrics for articles and galley usage. A date span must be specified. It has a legacy and non-legacy mode available. It is the only report that operates in this way.
Use for: downloading legacy or non-legacy timed view data.
Do Not Use for: downloading data in OJS 3.0+, as it no longer exists. Instead, use the Custom Report Generator.
Example Data (edited for clarity):
In the sample below, which was generated for the date span March 29 2017 - March 30 2017 (i.e., 1 day), we can see that the article “Amusing Ourselves to Death” was quite highly viewed, with 2 abstract views and 11 total galley views (3 PDF and 8 HTML). The “Comobility” article only had its abstract viewed once.
|ID||Article Title||Authors||Issue||Date Published||Abstract||Total Galley||HTML|
|2508||“Amusing Ourselves to Death?” Social Media, Political Satire, and the 2011 Election||Ian Reilly||Vol 36, No 3 (2011): Canadian Fascinations||2011-09-13 22:11||2||11||3||8|
|2512||Comobility: How Proximity and Distance Travel Together in Locative Media||Jen Southern||Vol 37, No 1 (2012): Media Arts Revisited (MARs)||2012-04-13 9:38||1||**||**||**|
Availability: OJS 2 only
Description: This report provides per-article abstract views and galley views/downloads. It is a pre-OJS 2.4.3 legacy report; use it only to retrieve basic usage metrics from journals that are or have been using OJS from before version OJS 2.4.3.
Use For: legacy view data only.
Do Not Use for: current usage metrics, unless you are still on OJS < 2.4.3.
Example Data (slightly edited for clarity):
In the sample below we can see that article 95, “The Making of the Canadian Media,” has had 443 abstract views and 1476 total galley views. The PDF and Total Galley views are the same because there were no HTML views. With article 1125, “Digital Networks,” the abstract was viewed 1821 times and total galley views are 8478, which is the sum of the HTML and PDF views.
|ID||Article Title||Issue||Date Published||Abstract||Total Galleys||HTML|
|95||The Making of the Canadian Media||Vol 6, No 1 (1979)||1979-01-03||443||1476||1476|
|1125||Digital Networks||Vol 24, No 4 (1999)||1999-04-01||1821||8478||2093||6385|
Availability: OJS 2 and 3
Description: This report provides granular data on monthly views for the journal homepage, issue TOCs, article abstract/landing pages, and file views. It provides country information (if configured). Each row provides a total monthly view count for a particular object (journal home page, article abstract page, article galley, or issue table of contents). It further facets this by country if country support has been enabled and properly configured.
Use for: generating a multifaceted overview content usage from month to month. It lists monthly view counts for all articles, article file downloads, issue TOC views, and journal homepage views for the specified timespan. Additional manual manipulation of the resulting report must be done to achieve aggregate results.
Do Not Use for: attempting to get a quick usage snapshot, legacy usage, or journals that have a very large metrics dataset (due to long history, high readership, or depth of metrics granularity). Use the Custom Report Generator instead.
Example Data (slightly edited for clarity):
|1||Journal||Canadian Journal of Communication||CJC||CA||201502||1678|
|112||Article||Toronto Star Fires Reporter Claire Hoy, Sues Him and TV Stations on Libel Charge||Vol 1, No 3 (1974)||CJC||CA||201502||3|
|112||Article||Toronto Star Fires Reporter Claire Hoy, Sues Him and TV Stations on Libel Charge||Vol 1, No 3 (1974)||CJC||US||201502||1|
From the above example, we can see that in February 2015 the main CJC journal homepage was viewed 1,678 times, which the article “Toronto Star Fires Reporter …” was viewed 3 times from Canada and once from the United States.
Availability: OJS 2 and 3
Description: This report provides granular data on daily views for the journal using the full metrics dataset. You are able to aggregate results by:
Metrics are tracked against specific item types (AKA “objects”):
You are also able to limit results to specific date spans. This is the most flexible report option available in OJS and can provide a very detailed amount of data. For more information, see Appendix C, OJS Report Generator: Examples and Tips.
Use for: creating very specific bespoke reports for new data
Do Not Use for: legacy data
Example Data (slightly edited for clarity):
The following example will provide us with article abstract and galley view counts broken down into daily, monthly, and country columns for the current month. In order to do this we set the following parameters:
In the resulting data below, we can see that the article abstract “Toronto Star Fires Reporter” was downloaded once on March 4 2018, while the article “Blowing up the Brand” was downloaded four times from Germany on March 22nd 2018 and twice from the US on March 4th 2018. (Note the difference between an “Article” type, which refers to the abstract view, and the “Galley” type, which refers to the galley file view or download.)
|Article||Toronto Star Fires Reporter Claire Hoy, Sues Him and TV Stations on Libel Charge||Vol 1, No 3 (1974)||US||20180304||201803||1|
|Galley||Blowing Up the Brand: Critical Perspectives on Promotional Culture||Digital Life||DE||20180322||201803||4|
|Galley||Blowing Up the Brand: Critical Perspectives on Promotional Culture||Digital Life||US||20180304||201803||2|
This section was originally authored by Andrea Kosavic at York University Library and has been slightly revised (mostly with OJS 3 updates).
The Report Generator can be found in OJS 2 at Home > User > Journal Management > Stats & Reports > Generate Custom Report
The Report Generator can be found in OJS 3 at Dashboard > Tools > Statistics > Generate Custom Report
…is actually repeated in the “Columns” section below…along with a number of other options. (Visible in the advanced options.)
This particular query will give you a monthly count of how many full text galleys have been downloaded from a particular issue. You’ll have a column for month and total count for month and a separate row for every month.
Save the URL at the bottom of the page for your records!
This report will present a list of article titles (and the issues they come from) ordered by descending download counts.
This query displays a count of fulltext downloads for each journal issue and orders the results from highest to lowest.
This query will display aggregate counts for fulltext downloads by country in descending order. Note that one will need to specify a date range.
OJS 3.1.2 now offers Editors and Journal Managers the option of viewing graph and table representations of article usage, including abstract views and full-text downloads.
The visual statistics can be found under Statistics on the left menu panel, by clicking Articles.
The Articles statistics show the articles’ abstract views in both graph and table format. The visual graphic can be changed from Monthly or Daily view. While the table format will allow you to filter the Total in ascending or descending order.
The calendar icon on the top right corner of your dashboard gives you the option of changing the article view to the Last 30 days, Last 90 days, Last 12 months, All dates or a Custom Date Range.
The filter icon on the top right corner of your dashboard gives you the option of filtering the articles by Sections.
You also have the option of searching the statistics of a specific article by title, author, or manuscript ID by using the search function under Article Details.
In OJS 3 you can display an article’s usage statistics for the current year as a graph on the article landing page by using the Usage Statistics Plugin, like in this image.
To enable the Usage Statistics Plugin:
To configure the Usage Statistics Plugin:
Please note the following:
This section is only relevant to those using OJS 2.4.3+ and OJS 3.0+. Older versions of OJS do not have this framework and need no configuration.
In most cases, the Statistics Framework should “just work,” in particular with fresh installs. Just the same, there are a number of configuration options available to you, and they should be reviewed after installation or upgrade. You also need to put in place some sort of mechanism to run scheduled tasks so that usage stats are processed regularly.
Note for Journal Managers and Editors: Most of the following steps would be considered expert level and should only be undertaken by Site Administrators and systems administrators. If you have questions about the more advanced issues presented here, consult with your service provider. The main exception to this is the Statistics Display option described in the next section. If you want to publicly display article usage statistics on article abstract pages, you can enable this option.
There are three configuration steps that you will have to consider: configuring the usage statistics plugin, configuring scheduled tasks, and configuring regional data tracking, if you want to track regional data. (OJS can track country, region, and city data.)
OJS 2.4.3+ and 3+ include a generic Usage Statistics Plugin that is responsible for how these statistics are logged and recorded in the system. The plugin’s default configurations are reasonable and work for most use cases, though you will want to review them after you install or upgrade OJS. To enable the collection of usage data, make sure that this plugin is enabled.
The plugin settings can be found in OJS 2 by going to User Home > Journal Manager > System Plugins > Generic Plugins > Usage Statistics Plugin > Settings.
The plugin settings can be found in OJS 3 by going to Dashboard > Settings > Website > Plugins > Generic Plugins > Usage Statistics Plugin > Settings.
We won’t go into detail for every single configuration option for the plugin, but we do suggest the following as a reasonable setup:
Once the Usage Statistics plugin has been enabled, you need to ensure that statistics are logged and processed as part of OJS’ “scheduled tasks.” There are two ways to do this:
The plugin can be found in OJS 2 by going to User Home > Journal Manager > System Plugins > Generic Plugins > Acron Plugin.
The plugin can be found in OJS 3 by going to Dashboard > Settings > Website > Plugins > Generic Plugins > Acron Plugin.
Once enabled, this plugin should result in the processing of log files (along with other scheduled tasks, such as review and subscription reminders).
This is a more advanced option requiring command-line access to the server and should only be configured by an experienced systems administrator. You will need to create a cron job that will trigger the following script in your OJS system directory:
This script expects an accompanying parameter in the form of a pointer to an XML file describing the scheduled task. This file will differ depending on whether you are using OJS log files, external log files (eg. Apache log files), or OJS log files with an automated staging process. Most journals will be using the simple “OJS log file” option (option 1 below). The location of these XML files are slightly different depending on whether you are using OJS 2 or 3. The full commands are as follows and will have to be added to the server cron job, ideally so that they run daily.
Commands to be run (OJS 2)
|OJS log files||php tools/runScheduledTasks.php plugins/generic/usageStats/scheduledTasks.xml|
|OJS log files with automated staging process||php tools/runScheduledTasks.php plugins/generic/usageStats/scheduledTasksAutoStage.xml|
|External log files||php tools/runScheduledTasks.php plugins/generic/usageStats/scheduledTasksExternalLogFiles.xml|
Commands to be run (OJS 3)
|OJS log files||php tools/runScheduledTasks.php lib/pkp/plugins/generic/usageStats/scheduledTasks.xml|
|OJS log files with automated staging process||php tools/runScheduledTasks.php lib/pkp/plugins/generic/usageStats/scheduledTasksAutoStage.xml|
|External log files||php tools/runScheduledTasks.php lib/pkp/plugins/generic/usageStats/scheduledTasksExternalLogFiles.xml|
After you configure either the Acron plugin or a cron job, your statistics should start processing. They only process at set times: once every 24 hours if using the Acron plugin and at whatever frequency set in the cron job, if that is being used. Wait for that amount of time, and then check to see if stats are now available. If they aren’t, proceed to the Troubleshooting section.
The Usage Statistics plugin can also track regional data, including visitor country, region, and city information.
Note 1: This is an entirely optional step.
Note 2: Storing geographical data can take up a lot of space and can also increase processing time when generating reports. If you are running into space issues or are running into timeouts when attempting to generate reports, you may have to either increase disc or memory resources or disable geographic logging.
Note 3: If you don’t enable and configure geographic tracking immediately and decide to enable it at a later date, you will have to reprocess your old log files in order for this data to be available in older usage statistics.
In order to track this information:
$ wget http://geolite.maxmind.com/download/geoip/database/GeoLiteCity.dat.gz $ gunzip GeoLiteCity.dat.gz $ mv GeoLiteCity.dat plugins/generic/usageStats
OJS, by default, automatically starts logging the usage events into its own access log files. It also automatically process those files on a daily basis. So, for example, if you installed OJS today at 2:00 pm, the processing of the usage events for today would start tomorrow at 2:00 pm. If you don’t change any setting, this will proceed without any input.
If you really want to control your stats processing, you can go to the Plugins management page in the Generic Plugins category and search for the Acron plugin. If disabled, automatic processing will stop. Read the following steps to understand how to manually trigger the processing.
OJS needs to process the files to be able to retrieve statistics data from them. This process can be done using the File Loader task tool, which comes with the Usage Statistics plugin.
The file loader task implements a process to reliably handle all file processing. It works with 4 folders: stage, processing, archive, and reject. Everytime the file loader is run, it will search for files inside the stage folder. If there are any, it will move one file to the processing folder and start working on it. If anything goes wrong, it will send an email to the system administrator with valuable information about what went wrong and will move the file to the reject folder. If the processing went well, then it will move the file to the archive folder. It will continue this process until there are no more files inside the stage folder.
The file loader is a scheduled task tool, which can be periodically invoked using cron or another system task management tool. The command to run this task depends on which process are you willing to use:
File loader task processes:
|1||OJS log files||php tools/runScheduledTasks.php plugins/generic/usageStats/scheduledTasks.xml|
|2||OJS log files with automated staging process||php tools/runScheduledTasks.php plugins/generic/usageStats/scheduledTasksAutoStage.xml|
|3||External log files||php tools/runScheduledTasks.php plugins/generic/usageStats/scheduledTasksExternalLogFiles.xml|
This should be executed from the OJS installation base directory.
NB.: For OJS 3.x, the scheduled task XML files have moved to the shared library, e.g. lib/pkp/plugins/generic/usageStats/scheduledTasks.xml
Process 1 and 3 require files to be moved inside the stage folder (regardless of whether it’s an apache log file or an OJS log file). Process 2 already automatically moves OJS log files into stage folder, so the command only needs to be executed.
Everything else is handled by the file loader task. If this task isn’t scheduled for automatic execution using cron or a similar mechanism, it will have to be run manually.
Note that for any process you choose, you can move files into the stage folder anytime, even while the scheduled task is running. You can also move any number of files inside the stage directory. What determines the period of time that you will be moving files into the stage directory is mainly your necessity for updated statistics.
The only thing that is not recommended is to move a log file that is still being used by the system (OJS or apache) to log access. OJS already controls that for process 2, but for 1 and 3 you have to be careful. It is not recommended because you can waste processing time when you reprocess the same file. You can guarantee that you will not do that by paying attention to the apache log files rotation (moving only the ones that were already rotated) or, if you use OJS log files, not moving the file that has its filename with the current day.
If you really need updated statistics from the same day, you can still copy the files (instead of moving) so the system can continue logging more access into the same file. However, you will be able to process what has already been logged. The system can handle with files reprocessing (see next topic), as long as the filename is unchanged the final copied version of the file contains all access logging.
Let’s imagine that we have the following scenarios, all three with a cron job calling the file loader task tool on a daily basis:
In scenario 1, if JM can’t configure the apache log files rotation to a smaller period of time, they can copy the 20130929-access.log file to the usageStats/stage directory every time they want new statistics to be processed. The system will, each time, delete all data that were processed for that file and reprocess everything again. That is why this process is not as efficient as an smaller period of log file rotation. At day 20131006 the log rotation will occur and JM can finally move or copy the 20130929-access.log file to the stage directory so the stats logged between the last time the file was staged and the log rotation can also be processed.
In scenario 2, JM can move one file per day, always moving the file from the previous day. On Monday they can move two files at the same time (from Saturday and Sunday). They will have a small time between access and available statistics (one day only, for most of the week) and will avoid reprocessing same access log entries.
In scenario 3, JM does not have to move the files. Each time the file loader task is executed, the system will automatically grab the log files that were not processed yet avoiding the current day one, will stage them, and will start processing each one.
In scenarios 1 and 2, if for some reason JM can’t move files for a whole week, in the next opportunity they can move all of them at once. The scheduled task will process one by one then until the stage directory is empty again.
If you need to reprocess any log file (if a new robot list or geolocation database is introduced or you fixed problems inside rejected files) you can move them back to the stage process. Even if they were inside “rejected” or “archived” directories. They will be processed and any existing data from these logs will be replaced by reprocessed data.
The important thing is that after a file is successfully processed and moved to the archive folder, its filename is preserved. The filename is used to keep track of statistics data and the file that it was retrieved from. For the same reason, it’s important that all log files have unique filenames. You don’t have to worry about this if you are using OJS log files. But if you are using apache access log files, ensure that you are using something unique such as dates in the filenames.
These are the most frequently asked questions and answers concerning OJS and statistics. This isn’t an exhaustive list. If you are running into further questions for which you don’t have answers, notify your hosting service provider or take a look at the PKP Community Forum <https://forum.pkp.sfu.ca> to see if anyone else has run into the same thing.
First, upgrade to the latest stable version of OJS 2 or 3. Optionally, also consider reprocessing your logs (see the previous section Processing Log Files).
Second, figure out what statistics you want and use the same method to get them each time. If you are using the Custom Report Generator, make sure you save the URL it provides to you so you can re-run that particular report.
It all depends on what kind of data you need. For legacy data (i.e., data from pre-OJS 2.4.3), the Views report gives a great overall snapshot of article usage and it’s the least complicated metric to understand.
For more recent data, we’d really recommend the Custom Report Generator. It’s quite complex, but it can provide a very wide range of data and uses the Statistics Framework to its fullest. Just make sure that you use it consistently! We have included a great set of tips and tricks, written by our colleague Andrea Kosavic at York University Library, at the end of this document that focuses specifically on the Custom Report Generator.
Yes, but only if you have web server logs from before the time that you upgraded. If you have these web server logs (e.g., Apache access_log files) from before the upgrade, you can process these (See Appendix B: Processing Log Files). If you don’t have these old logs, you are unfortunately out of luck.
Also, it’s worth noting that you can still retrieve the old, basic usage metrics using the legacy reports (in OJS 2 only - not OJS 3). These aren’t as comprehensive as the new metrics, and they have bot visits and multi-clicks included as well, but they are still a good representation of general usage.
This option is only available for OJS 3.x using the Usage Statistics Plugin. For instructions on how to enable and configure the Usage Statistics Plugin, see the previous section in this document Display Usage Statistics.
This is not currently possible with OJS but will be available in the future.
OJS collects statistics based on the internal IDs of issues, articles, and galleys.
If you replace a PDF file for a galley, the galley ID will not change. This means download statistics for the galley will continue to accumulate across the two versions of the file.
If you remove a galley from an article and later add a new galley for the article, the new galley will have a new ID. The cumulative statistics for article views will be unchanged but the usage statistics for the galley file will start again at 0. Historic statistics for the old galley will remain in the metrics, unless you rebuild the access logs into new metrics. New statistics will be collected for the new galley as access happens over time.
The specific impact will also vary by report, as the reports differ as to whether they are giving information for issues, articles, galleys, or a combination of these items.
These are the most frequently encountered problems when trying to generate usage reports, with some suggested solutions.
The Statistics Framework now filters views as per the COUNTER Project code of conduct. Specifically:
This will result in lower overall usage metrics. The drop shouldn’t be significant, though it can be noticeable.
The COUNTER Project is always adding new bots to their specification, and OJS tracks this specification on each release.
Chances are, there is a problem with your general statistics configuration. You should review this as per the Configuration section below.
That is a known bug in OJS 2.4.5. The solution is to upgrade, which will fix the problem immediately. You shouldn’t need to reprocess statistics to fix this problem.
A: If you are using OJS 188.8.131.52, this is a bug. To solve this, you will have to upgrade to the most recent version of OJS 2.4, or OJS 3, and reprocess your logs.
There are two likely causes for this:
Cause 1: At some point the statistics processing scheduled task was stopped. This can happen if your OJS instance has been migrated by a systems administrator from one server to another or if OJS has been upgraded but its configuration hasn’t been reviewed. You can confirm this in a few (very technical) ways:
files/usageStats/stage, the scheduled task isn’t running.
metricstable in the mysql database. If it’s empty or if metrics seem to have been recorded but stop at a particular date, the scheduled task isn’t running.
The solution to this problem is to review your configuration and reprocess statistics, as per the Configuration section below.
Cause 2: The report is hitting the report plugin’s 5,000-row limit. This should be obvious by looking at the .csv report: if it stops at or around row 5,000 (usually around row 5,006 due to some extra rows at the top of the report), then this is the issue. The solution here is to shrink the amount of data you are trying to extract, for example by limiting the date span, and downloading multiple reports. You can manually merge multiple reports together. Note: This issue only applies to OJS 3.1.1 or older. The 5,000 row limit was removed in OJS 3.1.2.
Q: I’m trying to download regional information using the Custom Report Generator, but I’m not seeing any of this in my reports.
A: Regional Data tracking hasn’t been properly or completely configured. See the Configuration section below.
This happens when the amount of data you are trying to download exceeds the server’s capacity to deliver it. This can be resolved either by shrinking the amount of data you are trying to extract in one go (i.e., by downloading reports in multiple date spans) or by increasing the problem resource (e.g.. PHP’s memory_limit or max_execution_time parameters). The latter can only be undertaken by a systems administrator.
See Appendix C: Processing Log Files.
Project COUNTER: https://www.projectcounter.org/
Using Cron: https://help.ubuntu.com/community/CronHowto
PKP Statistics Framework Technical Documentation (very verbose): https://pkp.sfu.ca/wiki/index.php?title=PKP_Statistics_Framework
PKP Community Forum (for follow-up questions): https://forum.pkp.sfu.ca