Presents a distinct scholarly question and original findings, with methods, analysis and evidence reported in enough detail for critical assessment.
About the Journal
EJSIR European Journal of Scientific Integration and Innovation
A cross-disciplinary forum for research that integrates scientific perspectives, technologies or methods to address complex questions. The journal welcomes methodological innovation and applied inquiry when the contribution of each field is explicit and conclusions remain proportionate to the evidence.
Journal overview
European Journal of Scientific Integration and Innovation is a journal in the EJSIR Publisher programme focused on scientific integration, technology convergence and applied innovation. Its sections cover Interdisciplinary Science Integration, Technology Convergence & Integrated Systems, Innovation Methods & Translational Research, Integrated Modelling, Data & Decision Systems and Sustainability, Society & Cross-Sector Innovation. The journal welcomes research that brings disciplines, technologies or methods together to address a clearly framed question and explains the contribution of each field.
Submissions may include original research, reviews and methods-focused work. Authors should describe how the participating approaches relate, identify assumptions and limitations, and provide transparent evidence suitable to the disciplines involved. The scope is interdisciplinary by design; a topic that spans fields is not sufficient unless the integration advances the work.
Editorial assessment considers scope, methodological quality, research integrity and clarity. The stated review model is double-anonymous peer review, normally with at least two independent reviewers. Publisher policies on ethics, access, authorship, conflicts, data and corrections apply alongside the journal’s scope. Manuscripts can be submitted only after the journal’s submission route opens.
Academic remit
The journal aims to publish work in which integration across scientific disciplines, technologies or methods is central to addressing a defined problem. It welcomes integrative concepts, cross-disciplinary research designs and carefully evaluated applications that make the relationship between contributing fields explicit.
Submissions may combine theoretical, experimental, computational, engineering, data-science or social-science approaches when each is justified by the question. Authors should explain how evidence is connected across fields, describe assumptions and methods, and report limitations and uncertainty. Interdisciplinary work should be more than parallel contributions assembled without a clear research logic.
Conclusions should follow from evidence appropriate to each component, and authors should distinguish demonstrated results from implications or future work. Research involving people, animals, sensitive data or protected material should report applicable ethics, consent, privacy and permissions.
Single-discipline studies without a clear integrative contribution, technology demonstrations without independent evaluation and proposals that do not support their conclusions with suitable evidence fall outside scope. Manuscripts must fit one or more of the academic sections described below.
Published work
Article types
Manuscripts must fit the journal scope and meet the relevant reporting, ethics and evidence requirements.
Synthesizes relevant scholarship to clarify the state of knowledge, compare interpretations and identify well-supported questions for further study.
Uses a clearly defined question and reproducible search, selection and synthesis methods, with the evidence base and limitations reported transparently.
Reports a focused result, observation or method whose concise presentation is useful to the field and supported by appropriate evidence.
Describes a practical method, instrument, workflow or technical refinement, explaining its operation, context and performance or validation.
Develops a reasoned scholarly interpretation of an important topic, distinguishing evidence from opinion and acknowledging relevant uncertainty.
Introduces a research dataset, software or other scholarly resource, documenting its provenance, structure, access conditions and quality checks.