Make Data Count

https://doi.org/10.60804/DBT4-CZ71  Make Data Count is a community hub for the development of metrics that can help us understand how data is used in research and policy activities. We reached out to Make Data Count community members for their views on data metrics and data evaluation. In this post, we share their perspectives on why understanding the use and reach of open data is important, and on their interest in Make Data Count.

Community perspectives on data metrics and data evaluation

The Make Data Count Summit 2024 took place in London earlier this month. Over two days, we explored what areas of research infrastructure, practices, evidence and evaluation we need to focus on to advance data metrics and our understanding of the reach and impact of open data.

Evaluation, context and getting practical on data metrics: the Make Data Count Summit 2024

DOI 10.60804/6a1z-rr79   At the recent Make Data Count Summit 2024, we had the opportunity to explore the insights that the Data Citation Corpus provides for institutions and funders. A large-scale open aggregate of data citations, the Data Citation Corpus currently stores 5 million citations collected via persistent identifier metadata and text mining of article content to identify mentions to datasets.

The Data Citation Corpus in practice: Perspectives from a funder and an institution

Kicking off the year, we had the pleasure of announcing the first release of the Data Citation Corpus. In response to the multiple expressions of interest in learning more about the project and in using the data file for the corpus, we held a webinar dedicated to the Data Citation Corpus.

‘I would like to better identify citations for data’: Community feedback and use cases for the first release of the Data Citation Corpus

First-of-its-kind aggregation brings together millions of data citations to advance understanding of data usage


 https://doi.org/10.60804/r14z-mw10

DataCite, in partnership with the Chan Zuckerberg Initiative (CZI), is delighted to announce the first release of the Data Citation Corpus.

DataCite launches first release of the Data Citation Corpus

This post has been cross-posted on the DataCite blog. A critical piece of open data infrastructure that has received insufficient attention is the evaluation of data usage. We still lack a clear understanding and a body of evidence on how data are being accessed, utilized, and incorporated into research activities….

A critical piece of open data infrastructure that has received insufficient attention is the evaluation of data usage. We still lack a clear understanding and a body of evidence on how data are being accessed, utilized, and incorporated into research activities.

Make Data Count Summit: The Time Is Now to Advance Data Metrics

Make Data Count Team

Make Data Count (MDC) is convening a two-day summit dedicated to the evaluation of open data usage, reach, and impact.

Announcing the Inaugural MDC Summit

Daniella Lowenberg

Join us for a 3-part series on key issues and opportunities for the community to prioritize on our journey to open data metrics.   Watch the recordings of FORAGE, EXPLORE, and BEGIN!

MDC Virtual Events: Spring, 2022

aninkov

Joint Declaration of Data Citation Principles

antonninkov/ISSI2021: Datasets on DataCite - an Initial Bibliometric Investigation

Datasets on DataCite - an Initial Bibliometric Investigation

By Kathleen Gregory and Anton Ninkov

 Data citations hold great promise for a variety of stakeholders. Unfortunately, due in part to a lack of metadata, i.e. about disciplinary domains, many of those promises remain out of reach. Metadata providers – repositories, publishers and researchers – play a key role in improving the current situation.

The potentials of data citations are many.

Data citations in context: We need disciplinary metadata to move forward

Daniella Lowenberg, Rachael Lammey, Matthew B. Jones, John Chodacki, Martin Fenner

DOI: 10.5281/zenodo.4701079

Data Citation: Let’s Choose Adoption Over Perfection

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 &amp;

Open Metrics Require Open Infrastructure

Since 2014, the Make Data Count (MDC) initiative has focused on building the social and technical infrastructure for the development of research data metrics.

Igniting Change: Our Next Steps Towards Open Data Metrics

The Make Data Count team has been working on various infrastructure and outreach projects focused on how to measure the reach and impact of research data.

Open Data Metrics: Lighting the Fire

Following advice from our workshop attendees at RDA13, we invite you to join us for our spring webinar. Join us on

 May 8th at 8am PST/3pm GMT

as we demo our new aggregation services at DataCite and DataONE. This webinar is intended to spotlight the features and services we can build off of our central infrastructure such as aggregated usage and citations. This webinar will be recorded and posted on our website.

Save The Date: MDC Spring Webinar

Join us on

 March 26th at 8:00am PST/4:00pm GMT

for a webinar on repository implementation of our COUNTER Code of Practice for Research Data and Make Data Count recommendations. This webinar will feature a panel of developers from repositories that have implemented or about to release standardized data metrics: Dataverse, Dryad, and Zenodo. We will interview each repository on their implementation process.

Repository Implementation Webinar: March 26, 2019

When: April 1st, 10:00am-12:00pm Where: Loews Hotel, Philadelphia.

When:

April 1st, 10:00am-12:00pm

 Where:

Loews Hotel, Philadelphia.

Save the Date: Make Data Count Pre-RDA13 Workshop

Crossposted from DataONE blog: https://www.dataone.org/news/new-usage-metrics

Publications have long maintained a citation standard for research papers, ensuring credit for cited work and ideas. Tracking use of data collections, however, has remained a challenge. DataONE is pleased to share our latest effort in overcoming this barrier and in demonstrating data reuse with new data usage and citation metrics.

DataONE Implements New Usage and Citation Metrics to Make Your Data Count

With Make Data Count now in its second year, the focus is shifting from building infrastructure to driving adoption of our open data-level metrics infrastructure.

Make Data Count &amp; Scholix Join FORCE(2018)s

Crossposted from COUNTER on September 13, 2018

There is a need for the consistent and credible reporting of research data usage. Such usage metrics are required as an important component in understanding how publicly available research data are being reused.

COUNTER Code of Practice for Research Data Usage Metrics Release 1

It’s been two exciting months since we released the first iteration of our data-level-metrics infrastructure.  We are energized by the interest garnered and questions we’ve received and we wanted to share a couple of highlights!

 July Webinar

Soon after launch we hosted a webinar on “How-To” make your data count. Thank you to the 100 attendees that joined us for asking such thoughtful questions.

Make Data Count Summer 2018 Update

One year into our Sloan funded Make Data Count project, we are proud to release Version 1 of standardized data usage and citation metrics! As a community that values research data it is important for us to have a standard and fair way to compare metrics for data sharing. We know of and are involved in a variety of initiatives around data citation infrastructure and best practices; including Scholix, Crossref and DataCite Event Data.

It&#8217;s Time to Make Your Data Count!

Many publishers have implemented open data policies and have publicly declared  their support of data as a valuable component of the research process. But to give credit to researchers and incentivize behavior for data publishing, the community needs to promote proper citation of data.

Publishers: Make Your Data Citations Count!

The Make Data Count team is rapidly approaching the first release of standardized and comparable data level metrics (DLMs) on California Digital Library’s Dash and DataONE repositories. Resources on this release will be available shortly, but in the meantime the team would like to share updates on work completed in winter and our spring roadmap.

Make Data Count Update: Spring, 2018

Kicking off Love Data Week 2018, the Make Data Count (MDC) team is pleased to announce that the first iteration of our Code of Practice for Research Data Usage Metrics Release 1 has now been posted as a preprint. Beginning in June, members from the MDC team and COUNTER began conversations around what a standard for data usage metrics may look like. By September we were able to release an initial draft outline for community feedback.

Code of practice for research data usage metrics release 1

For the past few months, we have worked to garner interest and facilitate discussion about data usage metrics within the community. Internally, we are working to drive development toward comparable, standardized data usage metrics and data citations on repository interfaces. We are excited to share our progress and we want to thank those who have given us feedback or have gotten involved along the way!

Make Data Count Winter 2018 Update

The Make Data Count (MDC) project is moving ahead with full force and the team wanted to take a moment to update the research stakeholder community on our project resources and roadmap. In September, the MDC team sat down and mapped out the project plan for our two-year grant.

Make Data Count Update: November, 2017

Following our draft update and executive summary, Make Data Count and COUNTER are proud to release our first draft of a

 Code of Practice for Research Data

. This first iteration is meant to be a draft, and our goal is to receive input and feedback from the community. We ask that you please comment on and mark up the document with questions, suggestions, and/or overall feedback.

COUNTER Code of Practice for Research Data Draft 1

As a research and scholarly communications community, we value methods to gauge the impact of research outputs, and we do this in the forms of citations and downloads. But, until now this has been limited to traditional journal publications, and scholarly research is much more than an article. Foremost, data play a major role in the research process and deserve to be valued as a first-class scholarly output.

COUNTER Code of Practice for Research Data Draft Update

COUNTER is a non-profit organization supported by a global community of library, publisher and vendor members, who contribute to the development of the Code of Practice through working groups and outreach. COUNTER and MDC  are collaborating to develop and publish a Code of Practice for Research Data. This set of recommendations will focus on how data usage should be measured and reported.

COUNTER Code of Practice for Research Data

The Alfred P. Sloan Foundation has made a 2-year, $747K award to the California Digital Library, DataCite and DataONE to support collection of usage and citation metrics for data objects. Building on pilot work, this award will result in the launch of a new service that will collate and expose data level metrics.

Make Data Count:  Building a System to Support Recognition of Data as a First Class Research Output

Making Data Count (MDC) team members are at the center of many initiatives that focus on aspects of metrics, including DLM. We leverage existing channels to build a new data usage standard and to promote integration and adoption amongst data centers and data consumers.  If you want to get in contact and start collaborating with us, please: Join our mailing list Follow us on Twitter Contact us directly!

How to engage with MDC?

Journal articles are the currency of scholarly research. As a result, we as a community, use sophisticated methods to gauge the impact of research and measure the attention it receives by analyzing article citations, article page views and downloads, and social media metrics. While imprecise, these metrics offer us a way to identify relationships and better understand relative impact.

Understanding the problem

Blog post by Iratxe Puebla and Maria Alejandra Tejada Gómez.

DOI: 10.60804/zb5q-qy55 The Make Data Count Summit last September brought together researchers, infrastructure providers and representatives across institutions, funding and policy areas to discuss data metrics and the responsible evaluation of data usage.

‘Policies that make data count’: data evaluation in funder and policy-making processes

The Generalist Repository Ecosystem Initiative (GREI) has as one of its objectives the implementation of open metrics. A consistent approach to data citations is an important step to drive meaningful metrics that provide visibility on data usage, signal the added value of data repositories and enable reporting on the reach...

Why data citations?

Data citations are a useful measure to gain understanding on the use of research data. Data citations recognize the individual(s) or organization(s) that collected and shared the data, and researcher surveys regularly show that researchers value receiving citations to their dataset (see for example The State of Open Data report, or research by Kathleen Gregory and colleagues).

GREI recommendations to support consistent practices to collect, expose and aggregate citations to open data

The COUNTER Code of Practice for Research Data provided a key milestone in data evaluation practices by making it possible to report comparable usage counts across platforms. Over the last months, Make Data Count and COUNTER have collaborated to explore what a suitable direction would be for an update to the Code of Practice for Research Data, and we are now sharing our proposal to merge the Code of Practice for Research Data with COUNTER R5.1 for public consultation.

https://doi.org/10.60804/8hvp-e561


 This blog post is cross-posted on the COUNTER site.

The COUNTER Code of Practice for Research Data provided a key milestone in data evaluation practices by making it possible to report comparable usage counts across platforms.

Bringing the COUNTER Code of Practice for Research Data and COUNTER Release 5.1 together to enhance normalization

DOI:10.60804/AGQD-PF50  We are thrilled to share that Make Data Count has been selected by SCOSS as essential open infrastructure for participation in its next funding cycle.

SCOSS selects Make Data Count as infrastructure essential to open science

Redivis

DOI 10.60804/1516-e177

 Blog post by Ian Mathews, CEO at Redivis, Zach Chandler, Director of Open Scholarship Strategy at Stanford University, Erin DeLaney, Head of Design at Redivis


 
 Analyze data citations for any repository by forking
 
 
 this analytical workflow
 
 
 on Redivis!
 

At Redivis, we believe that data-driven research should be accessible, reproducible, and as open as

Analyzing the Data Citation Corpus on Redivis

https://doi.org/10.60804/fkfy-1162  Make Data Count is a community hub for the development of metrics that can help us understand how data is used in research and policy activities. Several Make Data Count community members have given us their insights on the Data Citation Corpus, our project to build a central open aggregate of data citations.

Community perspectives on the Data Citation Corpus

This week we are thrilled to welcome Clare Dean as Communications Consultant for Make Data Count. In this role, Clare will be supporting Make Data Count’s outreach and community engagement activities. Clare brings a wealth of experience working with organizations in scholarly communications and open science initiatives, but best to let her tell you about it. Here’s a brief introduction to Clare, in her own words. Welcome Clare!

Clare Dean

https://doi.org/10.60804/9aqp-4273

This week we are thrilled to welcome Clare Dean as Communications Consultant for Make Data Count. In this role, Clare will be supporting Make Data Count’s outreach and community engagement activities.

Welcoming Clare Dean as Communications Consultant for Make Data Count

Make Data Count is pleased to announce the Make Data Count Summit 2024, a two-day meeting dedicated to responsible data metrics and the evaluation of open data usage and impact.

https://doi.org/10.60804/zhtp-vs98

Make Data Count is pleased to announce the Make Data Count Summit 2024, a two-day meeting dedicated to responsible data metrics and the evaluation of open data usage and impact. The Make Data Count Summit 2024 will be held in London, UK on September 5-6 and will provide a forum for discussions about evidence-based data metrics and responsible assessment of open data.

Join us for the Make Data Count Summit 2024

[*https://doi.org/10.60804/8hvp-e561*](https://doi.org/10.60804/8hvp-e561){target="_blank"
rel="noopener"}

*This blog post is cross-posted on the [COUNTER
site](https://www.countermetrics.org/crd-consultation/){data-type="link"
data-id="https://www.countermetrics.org/crd-consultation/"
target="_blank" rel="noopener"}.*

The [COUNTER Code of Practice for Research
Data](https://www.projectcounter.org/code-of-practice-rd-sections/foreword/){target="_blank"
rel="noopener"} provided a key milestone in data evaluation practices by
making it possible to report comparable usage counts across platforms.
Over the last months, Make Data Count and COUNTER have collaborated to
explore what a suitable direction would be for an update to the Code of
Practice for Research Data, and we are now sharing our proposal to merge
the Code of Practice for Research Data with COUNTER R5.1 for public
consultation.

<figure class="wp-block-image size-full is-resized">
<img
src="https://makedatacount.org/wp-content/uploads/2024/09/COUNTER-CoP-RD.png"
class="wp-image-1217" style="width: 494px; height: auto;"
decoding="async" />
</figure>

Read on for the context and motivation for this update, and details on
how you can share feedback on the proposal.

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### **The COUNTER Code of Practice for Research Data** {#the-counter-code-of-practice-for-research-data .wp-block-heading}

The [COUNTER Code of Practice for Research
Data](https://www.projectcounter.org/code-of-practice-rd-sections/foreword/){target="_blank"
rel="noopener"} was released in 2017 as a framework to enable
repositories and data-publishing platforms to report the usage of
datasets in a standardized way. By providing a common framework to
process and report counts for data views and downloads (e.g. noting
whether usage originated from humans or machines, filtering out activity
from web robots and spiders), the Code of Practice made it possible to
report usage counts comparable across platforms. This framework has been
implemented by a number of repositories, including Zenodo, Dryad and the
Environmental Protection Agency repository.

The development of the Code of Practice for Research Data drew from
COUNTER's experience with standards for usage metrics for scholarly
resources, and its recommendations aligned as much as possible with
Release 5 of the COUNTER Code of Practice. At the time, the main COUNTER
Code of Practice was tailored towards publisher platforms, and the data
community felt it was important to have a dedicated framework for
reporting on the use of datasets. However, there was also interest
in maintaining close communication about updates to both Codes, and in
exploring further alignment across the codes in future releases.

### **Aligning the Codes** {#aligning-the-codes .wp-block-heading}

In the six years since the release of the Code of Practice for Research
Data, repository infrastructure has developed substantially, and COUNTER
completed Release 5.1 of the main Code (R5.1), which has extended the
type of outputs for which usage reports can be reported, including
datasets. The Make Data Count and COUNTER teams have resumed the
discussions about an update for the Code of Practice for Research Data,
and based on our exploration of the current status of both codes, we are
proposing to merge the Code of Practice for Research Data with R5.1. We
base this recommendation on the following factors:

- Many repositories host diverse research outputs, including articles,
 data, theses and many others. In order to report usage counts for the
 variety of resources hosted, the repositories would need to maintain
 two Codes, resulting in duplication of effort and resources, and a
 risk of data usage counts being processed differently over time
 depending on the Code the repository is applying. Having a single Code
 to implement simplifies implementation by mixed-content repositories,
 and ensures consistency in usage reports. 
- One of the items that arose early on as part of discussions for a
 revision to the Code of Practice for Research Data was how to
 accommodate additional granularity to report usage of datasets that
 included multiple files. R5.1 now includes Components, which allows
 reporting usage for both an item and for files nested within the item.
 This structure allows repositories to report on usage of the dataset
 as a whole, or to report usage of individual files within the data
 record at a more granular level. 
- Key aspects of the Code of Practice for Research Data and R5.1 overlap
 or have matching attributes. While some differences between the Codes
 exist, we feel that these can be addressed by providing dedicated
 guidance to repositories that report data usage on how to complete
 those fields (e.g instances where the fields do not apply to data and
 may be left blank).

This update will require some changes to the implementation of how usage
reports are created for data, but it is important to note that the
process for reporting usage reports does not change. Processed data
usage reports can be [sent to DataCite for
aggregation](https://support.datacite.org/docs/contributing){target="_blank"
rel="noopener"}, and are made accessible via DataCite's API.

As part of our work on this proposal, we have consulted with members of
repository teams for their input. We thank Zach Crockett (KBase), Alex
Ioannidis (Zenodo), Pablo Saiz (Zenodo) and Ana van Gulick (Figshare)
for their input and suggestions.

### **Share your feedback on the proposal** {#share-your-feedback-on-the-proposal .wp-block-heading}

 

We are confident that this proposal to merge the Code of Practice for
Research Data with R5.1 will bring efficiencies to repository teams and
ensure consistent and robust reporting of data usage, but of course, we
want your feedback!

Please check the details of the proposal and share your feedback on the
suggested implementation by repositories hosting data via [this
form](https://forms.gle/SZwzW6sDX2WUeQ2q6){target="_blank"
rel="noopener"}, or the [COUNTER Github
repository](https://github.com/Project-Counter/CodeRD/wiki/1.-Code-for-Research-Data-Community-Consultation){target="_blank"
rel="noopener"}. You can also email us with any comments, queries or
concerns: [Iratxe
Puebla](mailto:iratxe.puebla@datacite.org){data-type="mailto"
data-id="mailto:iratxe.puebla@datacite.org"} (Make Data Count), [Tasha
Mellins-Cohen](mailto:tasha@countermetrics.org){data-type="mailto"
data-id="mailto:tasha@countermetrics.org"} (COUNTER). The proposal is
open for public consultation until 31 July 2024. We'll present the
proposal at the [COUNTER
conference](https://projectcounter.glueup.com/event/counter-conference-and-agm-2024-99633/){target="_blank"
rel="noopener"} on May 16, do join the session to hear more.

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feedback](https://github.com/Project-Counter/CodeRD/wiki/1.-Code-for-Research-Data-Community-Consultation){.wp-block-button__link
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