The phrase "adoption of interoperability" is correct and usable in written English.
It can be used in contexts discussing the implementation or acceptance of systems or processes that allow different entities to work together effectively.
Example: "The adoption of interoperability standards is crucial for enhancing communication between various software applications."
Alternatives: "implementation of interoperability" or "embrace of interoperability".
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The wider adoption of ELNs will facilitate interoperability which will ultimately change the ways scientists perform experiments and manage their data.
Its goal is to promote "superior interactivity for a wide range of next-generation consumer devices, digital content and distribution scenarios [and] maximize consumer satisfaction worldwide by accelerating industrywide adoption of advanced interactivity and interoperability across a broad array of HD DVD products".
3) Service interoperability: the adoption of standards such as W3C's web standards, OASIS's RM-ODP [16] and OGC's view (WMS), download (WFS), discovery (CSW) services.
To achieve data interoperability, the adoption of standard data formats and vocabularies is essential (24).
[ 41] Its goals include laying the foundation for "an interconnected, electronic health information infrastructure by promoting the adoption of clinical data standards and interoperability".
As part of a communitywide effort for evaluating text mining and information extraction systems applied to the biomedical domain, BioC is focused on the goal of interoperability, currently a major barrier to wide-scale adoption of text mining tools.
Chado provides a common database schema for storing biological data and its wider adoption helps promote interoperability of tools and exchange of data between different databases.
Finally, appreciating the diversity of cloud computing activities is crucial to the process of deriving consistent and useful standards for cloud adoption and interoperability.
The use of workflows for orchestrating services and jobs within complex execution scenarios is becoming established in e-science research, but lack of interoperability between different workflow systems makes the reuse of workflows difficult, impeding the pace of adoption in academia and industry [5].
Currently, hindrances for such adoption include poor quality data, problems with the management of large volumes of data, patient confidentiality, security and lack of interoperability in healthcare systems.
