By: John Chodacki, Martin Fenner, Daniella Lowenberg

Today, Zenodo announced their intentions to remove the altmetrics.com badges from their landing pages–and we couldn’t be more energized by their commitment to open infrastructure, supporting their mission to make scientific information open and free.

“We strongly believe that metadata about records including citation data & other data used for computing metrics should be freely available without barriers” – Zenodo Leadership

In the scholarly communications space, many organizations rally around the idea that we want the world’s knowledge to be discoverable, accessible, and auditable. However, we are not all playing by the same rules. While some groups work to build shared infrastructure, others work to build walls. This can be seen by the use of building barriers to entry around freely open information, or, information that should be open and free but isn’t. 

In light of emerging needs for metrics and our work at Make Data Count (MDC) to build open infrastructure for data metrics, we believe that it is necessary for corporations or entities that provide analytics and researcher tools to share the raw data sources behind their work. In short, if we trust these metrics enough to display on our websites or add to our CVs, then we should also demand that they be available for us to audit. 

This isn’t a new idea. The original movement to build Article Level Metrics (ALMs) and alternative metrics were founded on this principle. The challenge is that while infrastructure groups have continued to work to capture these raw metrics, the lopsided ecosystem has allowed corporations to productize and sell them, regardless of there being a true value-add on top of open information or not. 

We believe that the open metrics space should be supported, through contributions and usage, by everyone: non-profits, corporations, and community initiatives alike. In supporting open metrics, though, it is particularly important to acknowledge the projects and membership organizations that have moved the needle by networking research outputs through PIDs and rich metadata. We can acknowledge these organizations by advocating for open science graphs and bibliometrics research to be based on their data, so that others can reproduce and audit the assumptions made. Other ideals that we believe should guide the development of the open metrics space include:

  • Publishers and/or products that deal in building connections between research outputs should supply these assertions to community projects with full permissive CC0 license. 
  • Companies, projects, and products that collect and clean metrics data are doing hard work.  We should applaud them. But we should also recognize when metrics are factual assertions (e.g., counts, citations), they should be openly accessible. 
  • Innovation must continue and, similarly, productization can and should help drive innovation. However, only as a value add. Aggregating, reporting, making data consumption easier, building analysis tools and creating impact indicators from open data can all be valuable. But, we should not reward any project that provides these services at the expense of the underlying data being closed to auditing and reuse.
  • Show our work. We ask researchers to explain their methods and protocols and publish the data that underlies their research. We can and must do the same for the metrics we use to judge them by–and we must hold all actors in this space accountable in this regard as we work toward full transparency.   

These principles are core to our mission to build the infrastructure for open data metrics. As emphasis shifts in scholarly communication toward “other research outputs” beyond the journal article, we believe it is important to build intentionally open infrastructure, not repeating mistakes made in the metrics systems developed for articles. We know that it is possible for the community to come together and develop the future of open metrics, in a non-prescriptive manner, and importantly built on completely open and reproducible infrastructure.

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