Repository of Materials Research Data

Deposit your published research data and increase citations of your research

Assign DOI numbers to your datasets for accurate data citation and bibliometrics

Have your research indexed in the Data Citation Index (DCI) - Web of Science (WoS)

Comply with data management plan requirements of grants and project applications

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Published papers for which the data has been made publicly available attract up to 30% more citations, compared to the papers for which there is no publicly available data.

Source: Piwowar HA, Vision TJ. (2013) Data reuse and the open data citation advantage. PeerJ 1:e175

What Is Data Citation?

Basic terms and ideas behind the data citation initiative

Data citation refers to the practice of providing a reference to data in the same way as bibliographic reference is routinely provided to other scholarly resources.

Citing bibliographical references (journal papers, books, dissertations, reports, etc.) when performing and writing your own research work is a standard practice. As a norm, research work is based on different types of data:

  • In some cases it is original data produced in different ways and methods by yourself, the researcher.
  • However, in vast majority of cases it is (at least partially) data provided by other researchers or obtained from existing, published sources.

The latter holds true especially for materials research where data underlying the findings and subsequent published scientific work is crucial.

Driven by publisher and funding bodies’ requirements for reproducible research and reusable research outputs, data has come to be regarded as a primary research output rather than a by-product of research.

When datasets are cited, they become:

  • discoverable,
  • reusable, and
  • citable by others.

Citation of data also enables recognition of scholarly effort in disciplines and organisations that want to acknowledge and reward data outputs.

(Source: Australian National Data Service website ( Accessed 09 April 2018.)

How Data Citation Works?

  • 1. Research dataset is created and stored in a repository
  • 2. A unique identifier (DOI - digital object identifier) is assigned to the dataset
  • 3. Dataset becomes available to the research community and is used to create new publications
  • 4. Through data citation the use of the dataset is tracked, measured and properly attributed
  • 5. Original research(ers) benefit from increased citations

Why Deposit Your Data?

Here’s what it means to deposit data, datasets and data packages underlying material research publications (papers in journals, conferences, etc.) in repositories such as MATDAT Repository of Materials Research Data:

  • increased citability and citation count for data and related publications
  • safe, reliable management and long-term preservation of deposited research data
  • assignment of DOI designations to deposited datasets for better and more accurate data citation and bibliometrics
  • indexing datasets in Data Citation Index (DCI) in Web of Science and linking datasets with corresponding full-texts
  • making deposited data available to global academic and research community
  • improving searchability, discoverability and visibility of authors and their research
  • promoting data reuse and data citation, a very important collaborative trend in the global research and academic community

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Publications which publicly share their data received more citations.

The image on the left, taken from a 2007 research, is showing distribution of 2004–2005 citation counts of 85 trials by data availability. The 41 clinical trial publications which publicly shared their microarray data received more citations, in general, than the 44 publications which did not share their microarray data. In this plot of the distribution of citation counts received by each publication, the extent of the box encompasses the interquartile range of the citation counts, whiskers extend to 1.5 times the interquartile range, and lines within the boxes represent medians.

(Source: Piwowar HA, Day RS, Fridsma DB (2007) Sharing Detailed Research Data Is Associated with Increased Citation Rate. PLoS ONE 2(3): e308. doi:10.1371/journal.pone.0000308)


In order to reflect the importance and desire to enhance data sharing and re-use, corresponding requirements are becoming more strict.

Already back in 2013 in at-that-time-current Guide for preparation and submission of The US National Science Foundation’s applications in summary of significant changes, the following was clearly stated: “Applications that do not contain the requisite data management plan will be rejected or returned without review”. The same requirement is valid and present also in the most current 2018 Application Guide.
Data Management Plans are reviewed as an integral part of the project application proposals and are considered under Intellectual Merit or Broader Impacts or both, as appropriate for the scientific community of relevance.

(Source: The National Science Foundation Application Guide - A Guide for Preparation and Submission of NSF Applications via, January 29, 2018)

MATDAT and Data Citation

Right from the beginning, only highly relevant and detailed material datasets were included in MATDAT Database of Material Properties.

We have meticulously checked all content and made sure that all literature sources were fully referenced. Our goal was to enable our users to quickly and easily find the underlying reference(s) so that they could find additional information contained in original full-texts.

Our efforts were recognized in 2015 when we established collaboration with Thomson Reuters (now Clarivate Analytics) in the framework of which MATDAT Materials Properties Database and datasets hosted are covered by the Data Citation Index (DCI).


Data Citation Index database is a part of the Clarivate Analytics Web of Science research platform and is a single point of access to quality research data from repositories across disciplines and around the world. Through linked content and summary information this data is displayed within the broader context of the scholarly research.

Currently, DCI indexes about 300 databases and repositories from well-known universities and institutes. To be included in the index, we had to meet a number of very strict criteria. To our knowledge, MATDAT is for now the only database dealing with engineering-class materials that is included in Data Citation Index.

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At this moment, all existing datasets in MATDAT Database of Material Properties - including the ones that are being contributed and added to it - are being periodically indexed in the DCI.

We’re currently working on launching the Repository, but before we do, find out how you can contribute your data and have it indexed in the DCI.

Special Benefits for Academic Institutions

Access to all MATDAT services (Repository, Database, Directory) for all members of your organization


Learn more

Proposals submitted or due on or after January 18, 2011, must include a ... "Data Management Plan". This supplementary document should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results.

The National Science Foundation (US), Dissemination and Sharing of Research Results, NSF Data Management Plan Requirements

The National Science Foundation (US), Proposal & Award Policies & Procedures Guide (PAPPG), January 2018

What to Know More?

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