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Webinar: All about Journal Reports

If you missed our webinar about journal reports, you can catch up by listening to the recording.

You can also download the slides we used in this webinar.

The webinar participants asked some very useful questions, and these are shared below together with our responses.

Q: What is the difference between Item_Requests and Item_Investigations?

A:There are several different types of usage metric in Release 5, which break down into investigations and requests.

An investigation is tracked when a user performs any action in relation to a content item or title, while a request is specifically related to viewing or downloading the full content item. Requests relate to full-text views or downloads. Please note Requests are also Investigations.

 

Q: What is the duration of a “session” in order to be assigned as unique?

A:The rules for calculating the unique title counts are as follows:

If multiple transactions qualifying for the metric type in question represent the same title and oc­cur in the same user-session, only one “unique” activity MUST be counted for that title.

A user session is defined in any of the following ways: by a logged session ID + transaction date, by a logged user ID (if users log in with personal accounts) + transaction date + hour of day (a day is divided into 24 one-hour slices), by a logged user cookie + transaction date + hour of day, or by a combination of IP address + user agent + transaction date + hour of day.

To allow for simplicity in calculating session IDs, when a session ID is not explicitly tracked, the day will be divided into 24 one-hour slices and a surrogate session ID will be generated by combining the transaction date + hour time slice + one of: user ID; cookie ID; or IP address + user agent. For example, consider the following transaction:

  • transaction date/time: 2017-06-15 13:35
  • IP Address: 192.1.1.168
  • User Agent: Mozilla/5.0
  • Generated Session ID: 192.1.1.168|Mozilla/5.0|2017-06-15|13

The above replacement for a session ID does not provide an exact analogy to a session. However, statistical studies show that the result of using such a surrogate for a session ID results in unique counts are within 1–2 % of unique counts generated with actual sessions. [PY – should this be analogue or analogy or another word?]

Q: So, if a user accessed the full text or an article and then accessed the same article an hour and a half later for example, it would count as two unique item requests?

A: That is correct in some cases, and this may result in a small amount of over counting.

 

Q: What are the best R4 & R5 reports to use for an overall usage total comparable over time?

A: Release 4 Journal Report 1 Period Total, minus Journal Report 1 GOA = Total_Item_Requests in TR_J1: Journal Requests

 

Q: When a user opens two different articles from the same issue of a journal, how are these counted?

A:This user behaviour counts as 2 Unique_Item_Requests and will also be added to the Total_Item_Requests.

 

Q: Is research funder public access in the reports also counted, e.g. papers that are freely available, but may not be Open access?  (Otherwise known as research public access.)

A: OA Gold is defined as a content item which was immediately and permanently available as open access because an APC was paid by an author, their institution or their funder. This type of content is not included in TR_J1. Other types of open/freely available content are not excluded from TR_J1 and counted as ‘Controlled’.

 

Q: If I filter TR_J3 Controlled Unique_Item_Requests, are the numbers the same as TR_J1 Unique Item_Requests?

A: Yes, because TR_J1 only includes Controlled usage and excludes Gold Open Access (GOA). [PY – I’ve added in “excludes Gold Open Access” – I hope that’s correct?]

 

Q: For the TR_J4 report, could the spreadsheet be reconfigured to display in the same way as the JR5 report with the dates along the top rather than multiple lines for each title?

A:No, this not possible due to the way in which all the Release 5 reports follow a consistent format. However, in Excel you can pivot the tabular reports.

 

Q:  We would like to use No_License metrics to make the decision whether to buy a journal archive (or not).  Is there No_License data per YOP in the title master report?

A: Yes, YOP is a column heading in the Title Master Report, and No_License is one of the metrics shown.

 

Q: We are concerned about the lack of zero usage information. We want titles that we subscribed to appear in our reports even if usage is 0.  Excluding them is likely to have an effect on our usage graph due to “no value” (this should be zero).

A: COUNTER looks for ways to ensure that usage reporting is consistent and comparable across various providers and attempts to have a Code of Practice that can be implemented by the majority of publishers and analysed by the majority of libraries. Including zero usage for e-books and journals creates two challenges that make it impossible to offer comparable and consistent reporting.

  • Not all publishers and content providers produce their COUNTER statistics from the same system that they use to manage their access control. More commonly, reporting systems are completely separate data warehouses where usage is pre-processed and optimized for reporting. In many cases, publishers lacking the necessary technical expertise/infrastructure will outsource their COUNTER reporting to third-party organizations specializing in COUNTER reports. Adding the “access control” layer to the reporting system increases both the complexity and the cost of producing reports and, for many publishers, creates a barrier that they cannot overcome.
  • JournalReports are big, and they will have even more rows with COUNTER R5, as clarity and more detail are added to the reporting. Assuming the publisher could get past the challenge of adding access-control data to their usage reporting, the inclusion of zero-use titles in Journal Reports or even BookReports where year-of-publication data is tracked could result in COUNTER reports that are hundreds of thousands or even millions of rows long. Reports of this size would exceed the limits of Excel and the capabilities of most libraries to analyse.

 

KBART provides a way to match holdings against the reports, and while on the webinar, two organisations offered to share their templates and methodologies. We will contact them to follow up these kind offers.

 
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