The COUNTER Code of Practice for Research Data

The Code of Practice for Research Data Usage Metrics standardizes the generation and distribution of usage metrics for research data, enabling for the first time the consistent and credible reporting of research data usage.

COUNTER welcomes input and feedback from the community on this first iteration, so that it can be further developed and refined.

A downloadable PDF is now available in the download section below.

Code of Practice

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Glossary

Appendix A: Glossary of Terms for CoPRD

Aligned as much as possible with the COUNTER Code of Practice Release 5 glossary.

Abstract	See Description.
Access_Method	A COUNTER attribute indicating whether the usage related to investigations and requests was generated by a human user browsing and searching a website (Regular) or by a computer (Machine).
Author(s)	See Creator
Collection	A curated collection of metadata about content items.
Component	A uniquely identifiable constituent part of a content item composed of more than one file (digital object).
Content item	A generic term describing a unit of content accessed by a user of a content host. Typical content items include articles, books, chapters, datasets, multimedia, etc.
Content provider	An organization whose function is to commission, create, collect, validate, host, distribute, and trade information in electronic form.
Creator(s)	The person/people who wrote/created the datasets whose usage is being reported-
Data repository	A content provider that provides access to research data.
Data type	The field identifying type of content. The Code of Practice for Research Data Usage Metrics only recognizes the Data type Dataset.
Dataset	An aggregation of data, published or curated by a single agent, and available for access or download in one or more formats, with accompanying metadata. Other term: data package.
Description	A short description of a dataset. Accessing the description falls into the usage category of Investigations.
DOI (digital object identifier)	The digital object identifier is a means of identifying a piece of intellectual property (a creation) on a digital network, irrespective of its current location (IDF).
Double-click	A repeated click or repeated access to the same resource by the same user within a period of 30 seconds. COUNTER requires that double-clicks must be counted as a single click.
Host types	A categorization of Content Providers used by COUNTER. The Code of Practice for Research Data Usage Metrics uses the following host types: ● Repository ● Data Repository
Internet robot, crawler, spider	An identifiable, automated program or script that visits websites and systematically retrieves information from them, often to provide indexes for search engines rather than for research. Not all programs or scripts are classified as robots.
Investigation	A category of COUNTER metric types that represent a user accessing information related to a dataset (i.e. a description or detailed descriptive metadata) or the content of the dataset itself.
Log file analysis	A method of collecting usage data in which the web server records all of its transactions.
Machine	A category of COUNTER Metric Types that represents a machine accessing content, e.g. a script written by a researcher. This does not include robots, crawlers and spiders.
Master reports	Reports that contain additional filters and breakdowns beyond those included in the standard COUNTER reports.
Metadata	A series of textual elements that describes a content item but does not include the item itself. For example, metadata for a dataset would typically include publisher, a list of names and affiliations of the creators, the title and description, and keywords or other subject classifications.
Metric types, Metric_Type	An attribute of COUNTER usage that identifies the nature of the usage activity.
ORCID (Open Researcher and Contributor ID)	An international standard identifier for individuals (i.e. authors) to use with their name as they engage in research, scholarship, and innovation activities.
Persistent Identifier (PID)	Globally unique identifier and associated metadata for research data, or other entities (articles, researchers, scholarly institutions) relevant in scholarly communication.
Platform	An interface from an aggregator, publisher, or other online service that delivers the content to the user and that counts and provides the COUNTER usage reports.
Provider ID	A unique identifier for a Content Provider and used by discovery services and other content sites to track usage for content items provided by that provider.
Publication date, Publication_Date	An optional field in COUNTER item reports and Provider Discovery Reports. The date of release by the publisher to customers of a content item.
Publisher	An organization whose function is to commission, create, collect, validate, host, distribute and trade information online and/or in printed form.
Regular	A COUNTER Access_Method. Indicates that usage was generated by a human user browsing/searching a website, rather than by a computer.
Reporting period, Reporting_Period	The total time period covered in a usage report.
Request	A category of COUNTER Metric Types that represents a user accessing the dataset content.
Session	A successful request of an online service. A single user connects to the service or database and ends by terminating activity that is either explicit (by leaving the service through exit or logout) or implicit (timeout due to user inactivity). (NISO).
SUSHI	An international standard (Z39-93) that describes a method for automating the harvesting of reports. Research Data SUSHI API Specification is an implementation of this standard for harvesting Code of Practice for Research Data Usage Metrics reports.
Total_Dataset_Investigations	A COUNTER Metric_Type that represents the number of times users accessed the content of a dataset, or information describing that dataset (i.e. metadata).
Total_Dataset_Requests	A COUNTER Metric_Type that represents the number of times users requested the content of a dataset. Requests may take the form of viewing, downloading, or emailing the dataset provided such actions can be tracked by the content provider’s server.
Transactions	A usage event.
Unique_Dataset_Investigations	A COUNTER Metric Type that represents the number of unique “Datasets” investigated in a user-session.
Unique_Dataset_Requests	A COUNTER Metric Type that represents the number of unique datasets requested in a user-session.
User	A person who accesses the online resource.
User agent	An identifier that is part of the HTTP/S protocol that identifies the software (i.e. browser) being used to access the site. May be used by robots to identify themselves.
Version	Multiple versions of a dataset are defined by significant changes to the content and/or metadata, associated with changes in one or more components.
Year of publication	Calendar year in which a dataset is published.

Sections and Appendices »

Sections

Appendices

6.0 Logging Usage

Usage data can be generated in a number of ways, with two common approaches:

Log file analysis, which reads log files containing web server transaction A usage event.records
Page tagging, which uses JavaScript to notify a third-party server when a page is rendered by a web browser.

Each of these approaches has advantages and disadvantages, summarized below.

6.1 Log File Analysis

Advantages of log file analysis over page tagging “Page Tagging” is a method of collecting usage data which uses code, for example, JavaScript on each page to notify a third-party server when a page is rendered by a web-browser.include:

Web servers normally produce log files, so the raw data are already available. No changes to the website are required.
The data is on the organization’s own servers in a standard rather than proprietary format. This makes it easy for an organization to switch analysis programs later, use several different programs, and analyze historical data with a new program.
Log files contain information on visits from search A user-driven intellectual query, typically equated to submitting the “Search” form of the online service A branded group of online information products from one or more vendors that can be subscribed to/licensed and searched as a complete service, or at a lower level (e.g. a collection)to the server.engine spiders. Although these MUST NOT be reported as part of user A person who accesses the online resourceactivity, it is useful information for search A user-driven intellectual query, typically equated to submitting the “Search” form of the online service A branded group of online information products from one or more vendors that can be subscribed to/licensed and searched as a complete service, or at a lower level (e.g. a collection)to the server.engine optimization.
Log files require no additional DNS lookups. Thus, there are no external server calls which can slow page load speeds or result in uncounted page views.
The web server reliably records every transaction A usage event.it makes, including items such as content generated by scripts, and does not rely on the visitor’s browser.

6.2 Page Tagging

The main advantages of page tagging “Page Tagging” is a method of collecting usage data which uses code, for example, JavaScript on each page to notify a third-party server when a page is rendered by a web-browser.over log file analysis are:

Counting is activated by opening the page, not requesting it from the server. If a page is cached it will not be counted by the server. Cached pages can account for a significant proportion of page views.
Data is gathered via a component (tag) in the page, usually written in JavaScript, in conjunction with a server backend to manipulate and store the data in a database allowing complete control over how the data is represented.
The script may have access to additional information on the web client user A person who accesses the online resourcethat was not sent in the query.
Page tagging can report on events that do not involve a request A category of COUNTER “Metric Type” that represent a user A person who accesses the online resourceaccessing content (i.e. full text of an “Article”)to the web server.
Page tagging is available to companies who do not have access to their own web servers.
The page-tagging service A branded group of online information products from one or more vendors that can be subscribed to/licensed and searched as a complete service, or at a lower level (e.g. a collection)manages the process of assigning cookies to visitors; with log file analysis, the server must be configured to do this.
Log file analysis is almost always performed in-house. Page tagging can be done in-house but is more often provided as a third-party service. The cost differences between these two models can also be a consideration.

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How to become Counter Compliant

All academic libraries across the world use and trust COUNTER usage reports to inform renewal and new purchasing decisions, to inform faculty about the value of the library and its resources and to understand user behaviour and improve the user experience.

Counter will help publishers and vendors to become compliant. The The Friendly Guide for Providers Release 5 and Technical Notes and will provide the information you will need to start the process. Content providers transitioning from Release 4 to Release 5 compliance will also find transition timeline useful in their planning.

Audit Process

To comply with the Code of Practice, publishers and vendors must be independently audited within six months of signing the Declaration of COUNTER Compliance, and annually thereafter.

There are three approved COUNTER auditors:

COUNTER will also accept an audit by any Chartered Accountant (UK), CPA (USA) or their equivalent elsewhere.