SplineCloud’s primary mission is to facilitate open access to knowledge in science and engineering. Our members can make their inputs findable, accessible, interoperable, and reusable (FAIR) via a set of objects and tools tailored to unify the structure and access to knowledge regardless of its origin. The core building block in our paradigm that serves the needs of FAIR principles is the data repository.
Open data repositories already play a crucial role in modern science, offering a wide range of benefits to various stakeholders, from researchers and institutions to industry and the public. Open data enables:
By making data freely available, researchers can build more quickly on previous findings, driving faster progress. Open data minimizes duplication of effort.
Reproducibility and validation
Open data facilitates reproducibility and integrity in science and engineering. Transparent and reproducible research methods, analysis and results allow validation of findings and identification of errors.
Curated data repositories ensure valuable data remains findable, accessible and reusable into the future.
Sharing data encourages teamwork across institutions and disciplines, as researchers combine perspectives. Combining datasets from various origins may reveal new insights not possible working in isolation.
Data repositories give researchers credit via citation and metrics for sharing their data. This rewards open practices.
Open data aids learning and training of current and future generations of scientists and engineers. With open access, research data can inspire and assist in turning ideas into concepts, simplifying the journey into science and engineering.
Visibility and engagement
Open data exposes companies to a wider diversity of customers and partners. Standardized reusable product data enables more effective R&D and saves time and money compared to collecting proprietary datasets on demand.
There exist a number of platforms for open science, including Open Science Framework, Zenodo, Figshare and others. However, SplineCloud goes beyond just offering a common space to share research outputs. With a heavy accent on reusability SplineCloud provides a set of tools to work with data and gives the ability to assign valuable attributes, making data easier to find and understand.
SplineCloud provides free tools for data capture and data processing, that reduce the need to seek specialized instruments and hustle with transferring results. With SplineCloud you can work with data in common formats (spreadsheets, csv, text) and digitize image plots. The interactive curve fitting tool allows you to find the best fit to data in one click, fine-tune curves in advanced mode and reuse them in your code.
Basically, your data repository is just a cloud directory. You can create a folder structure and populate it with your data sources, after which you can start working with it, creating datasets and relations. SplineCloud allows you to upload and work with spreadsheets, text data, and scanned or captured image plots.
A short repository description and a number of topics, associated with your repository allow others to find your data on SplineCloud and discover similar data.
In order to allow for a more comprehensive description of your data SplineCloud provides a Wiki section. Describe your methods and add references here so that others can have a detailed picture of the approaches and sources that have led you to the results of your study.
Simple, but verified approach of attributing your research, gaining feedback and improving the ranking of your repository.
SplineCloud automatically parses your spreadsheets and creates a dataset for each sheet. If your data is presented as an image plot, you have the freedom to define datasets manually and use our integrated plot digitizer tool to extract data from plots.
Each data has something to say, and in most cases, it says that some variables exhibit a relation to another variable. To map these relations and turn them into reusable objects SplineCloud provides an interactive curve-fitting tool that allows you to find the best fit for your data in just a few clicks.
Standardized data and metadata representation together with open API facilitate seamless integration of data into your modeling environments and data processing workflows. All objects created on SplineCloud become accessible via SplineCloud API. We also provide free clients for Python and MATLAB that simplify access and reuse of data and relations in your code.
Excited to become a member of our open community? Sign up for free now and start sharing your knowledge on SplineCloud!
leave us a message here or write to email@example.com