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

*Blog post by Iratxe Puebla and [Maria Alejandra Tejada Gómez.
]{style="font-weight: 400;"}*[[DOI:
10.60804/zb5q-qy55](https://doi.org/10.60804/zb5q-qy55){target="_blank"
rel="noopener"}]{style="font-weight: 400;"}

[The ]{style="font-weight: 400;"}[[Make Data Count
Summit]{style="font-weight: 400;"}](https://makedatacount.org/read-our-blog/evaluation-context-and-getting-practical-on-data-metrics-the-make-data-count-summit-2024/)[
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.
Policy makers and funding agencies play a major role in driving forward
open science practices and the adoption of open data as well as data
evaluation, and so one of the sessions at the Summit focused on funder
and policy-making processes. ]{style="font-weight: 400;"}[Mercè Crosas
(Barcelona Supercomputing Center & CODATA) facilitated a discussion with
Dagmar Meyer (European Research Council), Anna Diaz Font (Medical
Research Foundation) and Maria Alejandra Tejada Gómez (Universidad
Javeriana)]{style="font-weight: 400;"}[ about data evaluation and the
role of data metrics]{style="font-weight: 400;"}[ to measure the impact
of open data and inform decision-making in national
contexts.]{style="font-weight: 400;"}

### [The need for data evaluation as part of open data policies]{style="font-weight: 400;"}

[A number of research funders support or require data sharing.
]{style="font-weight: 400;"}[Dagmar Meyer and Anna Diaz Font both noted
that the European Research Council and Medical Research Foundation
stipulate as part of their policies that data from the funded research
should be made available. Maria Alejandra Tejada Gómez shared that the
policies approved under the latest National Development Plan in Colombia
also expect access to the results and data from publicly-funded
research. The panelists noted that an evaluation of data availability
would fit within processes to check for policy compliance, but
acknowledged that such compliance checks are currently
rare.]{style="font-weight: 400;"}

[As for any other evaluation process, there is a need to consider what
is the purpose and scope of a data evaluation framework: is this at the
researcher level or at program or national level? Is it to check for
compliance or to inform funding or policy decisions? The metrics to
incorporate into the evaluation will depend on the type of evaluation to
undertake. When considering national policies, the framework will then
influence policies at institutional level, where requirements for data
management plans or data sharing are already implemented or in process.
The institutional policies need to align to the broader national
regulation for open data.]{style="font-weight: 400;"}

 

![](https://makedatacount.org/wp-content/uploads/2024/12/Policies-that-make-data-count-session-600x355.jpg){.size-medium
.wp-image-940 .aligncenter fetchpriority="high" decoding="async"
width="600" height="355"
srcset="https://makedatacount.org/wp-content/uploads/2024/12/Policies-that-make-data-count-session-600x355.jpg 600w, https://makedatacount.org/wp-content/uploads/2024/12/Policies-that-make-data-count-session-1024x606.jpg 1024w, https://makedatacount.org/wp-content/uploads/2024/12/Policies-that-make-data-count-session-768x455.jpg 768w, https://makedatacount.org/wp-content/uploads/2024/12/Policies-that-make-data-count-session-1536x909.jpg 1536w, https://makedatacount.org/wp-content/uploads/2024/12/Policies-that-make-data-count-session-2048x1212.jpg 2048w, https://makedatacount.org/wp-content/uploads/2024/12/Policies-that-make-data-count-session-1568x928.jpg 1568w"
sizes="(max-width: 600px) 100vw, 600px"}

 

### 

### [Current practices, challenges and opportunities]{style="font-weight: 400;"}

[While the policies in place at different funders indicate that
researchers may report any output as part of their grant applications or
reports, in practice, few funders currently complete evaluations of data
impact. This is also the case at institutional level, where policies
have so far focused on the aspects of data up to the stage of sharing,
with less attention beyond that point.]{style="font-weight: 400;"}

[The discussion explored the challenges around the implementation of
data evaluation in funder processes. The panelists raised a few elements
that could do with further definition. Conceptually evaluation of data
could be viewed in different ways: on the one hand, we have the aspect
of the quality of the data and its accompanying metadata -- e.g. use of
persistent identifiers (PIDs), alignment to FAIR and CARE principles,
compliance with privacy and security requirements -- and whether the
data shared is reproducible and reusable; on the other hand, there can
be an evaluation of the reuse and impact of the data, that is, assessing
whether others have reused the data and for what purposes. These two
axes of evaluation will require a different combination of metrics, with
the former possibly relying more on qualitative information and the
latter more on quantitative metrics such as data citations, downloads,
or the number of access requests. The metrics to implement may also
differ depending on whether the evaluation is related to an individual
researcher or rather a research program or a collection of
outputs.]{style="font-weight: 400;"}

[In addition to defining the metrics for each type of evaluation, there
were also questions raised about the information required to provide
adequate context so that panels would trust and incorporate it into
their reviews. And as a complementary point, it would be important to
have common ground on what the sources of data usage information would
be, what tools are available to access the information, and what are the
remaining gaps to address.]{style="font-weight: 400;"}

[An aspect that garnered substantial comments was that of the resourcing
needed to implement data evaluation in meaningful ways. The panel
recognized that in order to complete evaluations of data reach and
impact, there would need to be additional resources dedicated to curate
and preserve the data to make that evaluation possible, to sustain the
peer evaluation of data (with review panels incorporating the relevant
skills to complete this type of assessment), and to gather and interpret
quantitative measures collected through automated means or external
sources. Ensuring a comprehensive view on the usage of data also relies
on sustaining the infrastructure necessary to collect this information
-e.g. repositories, data storage, interoperable systems and
integrations-, and to make it openly
available.]{style="font-weight: 400;"}

[While this may seem challenging, there is a consensus that data is
critical to address global challenges. We saw the critical role of open
data in responding to the COVID-19 pandemic, and we should thus leverage
the potential of data to accelerate research progress to respond to
societal needs. To this end, there are a number of ways in which we can
take steps to make data evaluation a reality. Many institutions have
developed repositories and work with infrastructure providers that
supply interoperable systems. It will be important to sustain this
existing infrastructure while emphasizing interoperability to gain
economies of scale. There are also tools and services that provide open
information about data usage; while the usage measures may not be mature
for their use in all areas of evaluation, we can already put the
information available to use where this is meaningful. For example, the
number of data citations is scaling and in combination with other
information that funders collect, this can already provide insights into
the reach and impact of datasets at program
level.]{style="font-weight: 400;"}

### [Resourcing data evaluation processes is key]{style="font-weight: 400;"}

[The discussion highlighted the importance that funding and
policy-making agencies place on open data. The discussion touched on the
need to identify the right information for a responsible and equitable
evaluation of researchers and of research programs, and to resource
data-evaluation efforts. Importantly, all panelists highlighted that we
need a better understanding of how open data practices are evolving, and
of the impact and return-on-investment of open data policies. And so,
the time has come to match ]{style="font-weight: 400;"}[our recognition
that data evaluation is important with the investment in resources
necessary to make it happen.]{style="font-weight: 400;"}

 

*We thank Anna Diaz Font (Medical Research Foundation), Mercè Crosas
(Barcelona Supercomputing Center & CODATA), and Dagmar Meyer (European
Research Council) for their contributions during the Make Data Count
Summit and insightful discussions that fed into this post.*


[DOI
10.60804/6a1z-rr79](https://doi.org/10.60804/6a1z-rr79){target="_blank"
rel="noopener"}

At the recent [Make Data Count Summit
2024](https://makedatacount.org/evaluation-context-and-getting-practical-on-data-metrics-the-make-data-count-summit-2024/),
we had the opportunity to explore the insights that the [Data Citation
Corpus](https://makedatacount.org/data-citation/) 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. By aggregating data citations identified through different
methodologies, the Corpus provides a larger view into the use of data as
part of publications than was previously possible. This opens
possibilities for institutions and funders to better understand the
reach of open data associated with their programs and faculty
activities. The session 'Uses of the Data Citation Corpus' as part of
the Summit provided an exploration into the information within the
Corpus, focusing on the Wellcome Trust and the University of Cape Town
as use cases.

*Note that the dashboards developed for this session are based on a
sample of data citations available via DataCite metadata and three
repositories utilizing accession numbers (Protein Data Bank (PDB), Gene
Expression Omnibus (GEO) and ArrayExpress). The trends reported are
based on a subset of the data citations for each organization and do not
represent full coverage.*

**The funder use case: Wellcome Trust**

We provide examples below of some of the dashboards that fed the
discussion during the session, related to the repositories, affiliations
and grant programs for data citations where the constitutive data or
journal article were funded by the Wellcome Trust. The distribution of
repositories highlights the Protein Data Bank, Figshare and Gene
Expression Omnibus as popular venues for datasets used in publications.
The Protein Data Bank in particular stands out with over 1,000 citations
to datasets from this repository. With regard to affiliations, the
institutions commonly associated with datasets reused were the
University of Zurich, the European Bioinformatics Institute and the
Wellcome Sanger Institute.

![Dashboard
examples](https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.53.45%E2%80%AFAM-600x331.png){.alignnone
.size-medium .wp-image-710 loading="lazy" decoding="async" width="600"
height="331"
srcset="https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.53.45 AM-600x331.png 600w, https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.53.45 AM-1024x564.png 1024w, https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.53.45 AM-768x423.png 768w, https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.53.45 AM.png 1252w"
sizes="auto, (max-width: 600px) 100vw, 600px"}

A dive into grant programs highlighted the Wellcome Trust Centre, the
Institutional Strategic Support Fund and the Investigator Award in
Science programs as those commonly associated with datasets mentioned in
publications.

![](https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.54.42%E2%80%AFAM-2-e1727277053658.png){.alignnone
.size-full .wp-image-720 loading="lazy" decoding="async" width="297"
height="238"}

During the discussion [Peter
O'Donovan](https://summit.makedatacount.org/speakers/peter-odonovan/),
Head of Portfolio Integration at the Wellcome Trust, outlined this
funder's interest in evaluating the usage of data originating from their
funded programs. As a key research output, understanding the use and
reach of data from funded projects is a key piece to gain a holistic
view into the impact of Wellcome's programs, and to inform areas in need
of future funding. A particular use of the Corpus of value for funders
is the possibility of combining data citation metadata with grant
information collected internally, to obtain further context about the
distribution of datasets and their reach for different programs and
projects. While no single tool will provide the full picture on the
reach of outputs from funded research, Peter underlined that the Data
Citation Corpus provides another piece of the puzzle to inform the
assessment of whether and how Wellcome is delivering on its strategy.

**The institutional use case: University of Cape Town**

Turning to the institutional perspective, [Lynn
Woolfrey](https://summit.makedatacount.org/speakers/lynn-woolfrey/)
shared her view from the University of Cape Town and as manager of the
research data service
[DataFirst](https://www.datafirst.uct.ac.za/){target="_blank"
rel="noopener"}. Lynn discussed the data services that had been
developed at the university to encourage and support sharing of datasets
from South Africa and other African countries, with a particular focus
on the social sciences.

For data citations where the data or journal article was published by
staff/faculty from the University of Cape Town, popular repositories
hosting datasets in the Corpus included the Cambridge Crystallographic
Data Centre, Dryad and the Protein Data Bank. Common funders were the
National Science Foundation, followed by a number of NIH sections,
including the National Institute of Mental Health and the National
Institute on Drug Abuse.

![](https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.55.32%E2%80%AFAM-600x327.png){.alignnone
.size-medium .wp-image-712 loading="lazy" decoding="async" width="600"
height="327"
srcset="https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.55.32 AM-600x327.png 600w, https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.55.32 AM-1024x558.png 1024w, https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.55.32 AM-768x418.png 768w, https://makedatacount.org/wp-content/uploads/2024/09/Screenshot-2024-09-25-at-10.55.32 AM.png 1248w"
sizes="auto, (max-width: 600px) 100vw, 600px"}

Lynn noted that the trends already surfaced by the Data Citation Corpus
provide useful pointers for future conversations with funders and policy
makers about the impact of open data, but also to highlight areas of
need for further development of infrastructure, metadata or researcher
support within their institution.

We thank [Jennifer
Lin](https://summit.makedatacount.org/speakers/jennifer-lin/) for the
exploration of the data in the Data Citation Corpus, and Peter O'Donovan
and Lynn Wolfrey for sharing their perspectives.

The above is just a flavor of the insights that can already be gained
through the Data Citation Corpus. We invite you to dive into the [Corpus
data file](https://zenodo.org/records/13376773){target="_blank"
rel="noopener"} and let us know what you found useful for your uses, and
what additional items would be relevant for your context, e.g. do you
need to segment data citations by discipline? Is license information
relevant for your evaluation of data usage? We welcome your feedback to
inform next steps in our ongoing work to broaden the coverage of data
citations in the Corpus.

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<td>Explore the Data Citation Corpus data file: <a
href="https://zenodo.org/doi/10.5281/zenodo.11196858" target="_blank"
rel="noopener">https://zenodo.org/doi/10.5281/zenodo.11196858</a></td>
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