STM, DataCite, and Crossref are pleased to announce an updated joint statement on research data.
In 2012, DataCite and STM drafted an initial joint statement on the linkability and citability of research data. With nearly 10 million data citations tracked, thousands of repositories adopting data citation best practices, thousands of journals adopting data policies, data availability statements and establishing persistent links between articles and datasets, and the introduction of data policies by an increasing number of funders, there has been significant progress since.
Have you attended any of our annual meeting sessions this year? Ah, yes – there were many in this conference-style event. I, as many of my colleagues, attended them all because it is so great to connect with our global community, and hear your thoughts on the developments at Crossref, and the stories you share.
Let me offer some highlights from the event and a reflection on some emergent themes of the day.
Hello, readers! My name is Luis, and I’ve recently started a new role as the Technical Community Manager at Crossref, where I aim to bridge the gap between some of our services and our community awareness to enhance the Research Nexus. I’m excited to share my thoughts with you.
My journey from research to science communications infrastructure has been a gradual transition. As a Masters student in Biological Sciences, I often felt curious about the behind-the-scenes after a paper is submitted and published.
In May, we updated you on the latest changes and improvements to the new version of iThenticate and let you know that a new similarity report and AI writing detection tool were on the horizon.
On Wednesday 1 November 2023, Turnitin (who produce iThenticate) will be releasing a brand new similarity report and a free preview to their AI writing detection tool in iThenticate v2. The AI writing detection tool will be enabled by default and account administrators will be able to switch it off/on.
We maintain an expansive set of relationship types to support the various content items that a research object, like a journal article, might link to. For data and software, we ask you to provide the following information:
identifier of the dataset/software
identifier type: DOI, Accession, PURL, ARK, URI, Other (additional identifier types are also accepted beyond those used for data or software, including ARXIV, ECLI, Handle, ISSN, ISBN, PMID, PMCID, and UUID)
relationship type: isSupplementedBy or references (use the former if it was generated as part of the research results)
description of dataset or software
We and DataCite both use this kind of linking. Data repositories which register their content with DataCite follow the same process and apply the same metadata tags. This means that we achieve direct data interoperability with links in the reverse direction (data and software repositories to journal articles).
The possible relationship types between content items can be as varied as the items themselves. We use a controlled vocabulary to define these relationships, in order to construct an orderly mapped network of content.
This is achieved by (i) an implicit approach where the relation type is a function of a specific service and is declared in the structure of the deposited XML, and (ii) in an explicit approach where the relation type is selected as a value within the deposited metadata.
Reference linking and Cited-by: implicitly creates cites and isCitedBy relationships between a content item and the items in its bibliography
Crossmark: explicit creation of update relations between an item and other items that materially affect it (for example, a retraction)
Funding data: implicit creation of isFundedBy and hasAward relationships between an item and the funding source that supported the underlying research
Linked clinical trials: implicit creation of a belongsTo relationship between and item and a registered clinical trial
Components: implicit creation of a isChildOf relationship between an item and its elemental parts that are assigned their own DOI (limited parent relation typing)
General typed relations: explicitly typed relation between an item with a Crossref DOI and an item with one of several possible identifiers.
Relationship types for associated research objects: intra-work (within a work)
Reciprocal relationship types
Relationship types for associated research objects: inter-work (between works)
Reciprocal relationship types
Related material, such as a protocol
Supplement, such as a dataset generated as part of research results
General typed relations
This service allows for the creation of a typed relationship between an item with a Crossref DOI and another content item. The other item may be represented by another Crossref DOI, a DOI from some other Registration Agency, or an item not identified with a DOI. When DOIs are used, the deposit process will fail if the DOI does not exist. Non-DOI identifiers are not verified.
When DOIs are used, a bidirectional relation is automatically created by us when a relation is created in the deposit of one item in a pair. The DOI with metadata creating the relation is said to be the claimant, the other item does not need to have its metadata directly contain the relationship.
Example: translated article
A single journal article is published in two languages with each being assigned its own DOI. In this example, both are published in the same journal. The original language instance has metadata that contains no indication of the translation instance. The alternative language instance includes in its metadata a relation to the original language instance. Here is a screenshot of the relevant section in the code. Please refer to the code snippet below to see it in context.
<title>Um artigo na língua original, que passa a ser o inglês</title>
<original_language_title language="en">An article in its original language which happens to be English</original_language_title>
<person_name sequence="first" contributor_role="author">
<description>Portuguese translation of an article</description>
<intra_work_relation relationship-type="isTranslationOf" identifier-type="doi">10.5555/original_language</intra_work_relation>