Discover

Workflows

Collaboration

Finance

Project Management

Research

Planning

Journal Related

Notifications

Reference Management

Searching

Exploring

Analysis

Experiment

Sharing

Analyzing

Citation

Code

Visualization

Writing

Documenting

Archiving

Impact Measurement

Journal Selection

Peer Review (Post Pub)

Peer Review (Pre Pub)

Presentation

Publication

Research Assessment

Researcher Networks

Publishing

Biology

Earth and Environment

Health

Humanity

Physical Science and Technology

Sociology

Execution

Code Editor

Data Visualizations

Graph Visualizations

Collaborative Writing

Data Analysis

Data Collection

OpenML

OpenML is an online platform and service for machine learning, whose goal is to make machine learning and data analysis simple, accessible, collaborative and open with an optimal division of labour between computers and humans. People can upload and share data sets and questions (prediction tasks) on OpenML that they then collaboratively solve using machine learning algorithms. It is accessible to everyone for free. It can be used to download or upload OpenML data such as datasets and machine learning experiment results. It provides easy access to all datasets, tasks and experiments on OpenML from within Python.

A free and open science machine learning platform

Data Mining

Data Cleaning

Data Extraction

Network Visualizations

University of Waikato

The machine learning framework Weka contains several tools for data mining and preparation, classification, regression, clustering, deep learning and visualization. Besides the use within your own Java program, the functionality is also available via GUI.

Weka

Electronic Lab Notebook

RDKit

Open source toolkit for cheminformatics Business-friendly BSD license Core data structures and algorithms in C++ Python 3.x wrappers generated using Boost.Python Java and C# wrappers generated with SWIG 2D and 3D molecular operations Descriptor generation for machine learning Molecular database cartridge for PostgreSQL Cheminformatics nodes for KNIME

Open source toolkit for cheminformatics and machine learning.

Discovery

Facilitate Contracts

Discover Funders

Crowdsourced Analysis

Crowdsourced Computing Analysis

Statistical Checks

Google LLC

Machine learning competitions were Kaggle's first product and still what the site is most famous for. Companies post problems and machine learners compete to build the best algorithm. Kaggle Kernels is a cloud-based workbench for data science and machine learning that allows data scientists to share code and analysis in Python and R. 
Over 150K "kernels" (code snippets) have been shared on Kaggle covering everything from sentiment analysis to object detection. Via the Public datasets platform community members share datasets with each other.

Kaggle is an online community of data scientists and machine learners.

Kaggle

Preparation

Discover Data

Discover Journals

Discover Citations

Discover References

Discover Literature

Open Access Search

Access Journals

Open Access Journal

Semantic Search

Multidisciplinary Search

Search Engine

Semantic Scholar

Semantic Scholar is a project developed at the Allen Institute for Artificial Intelligence. Publicly released in November 2015, it is designed to be an AI-backed search engine for scientific journal articles. The project uses a combination of machine learning, natural language processing, and machine vision to add a layer of semantic analysis to the traditional methods of citation analysis, and to extract relevant figures, entities, and venues from papers. As of January 2018, following a project that added biomedical papers and topic summaries, the Semantic Scholar corpus included more than 40 million papers from computer science and biomedicine. As of August 2019, the number had grown to more than 173 million after the addition of the Microsoft Academic Graph records.

Semantic Scholar helps researchers find better academic publications faster

Discover Abstracts

Discover Research Projects

Arxiv Sanity

Arixv Sanity tracks arXiv papers related to artificial intelligence and machine learning and makes them browsable by comparing papers based on their content. Users can comment on papers. It is developed and maintained by Andrej Karpathy.

Browse recent arXiv papers based on semantic similarity.

Share Data

Import.io

Import.io is a United Kingdom software company that was founded in 2012. It extracts web data and permits use it in all sorts of ways. Import.io returns data that can be used for price monitoring, lead generation, market research, app development, academic research or machine learning. It uses highly sophisticated machine learning algorithms to extract data automatically the first time. The tool offers a URL generator to find common patterns and generate thousands of URLs in seconds.

A data extractor that requires no coding, turning the web into data

Reader

Management

Open Access Project Management

Idea Database

Cermine

CERMINE is a comprehensive open-source system for extracting structured metadata from scientific articles in a born-digital form. The system is based on a modular workflow, whose loosely coupled architecture allows for individual component evaluation and adjustment, enables effortless improvements and replacements of independent parts of the algorithm and facilitates future architecture expanding. The implementations of most steps are based on supervised and unsupervised machine learning techniques, which simplifies the procedure of adapting the system to new document layouts and styles.

Automatic extraction of structured metadata from scientific literature.

KNIME

KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface and use of JDBC allows assembly of nodes blending different data sources, including preprocessing (ETL: Extraction, Transformation, Loading), for modeling, data analysis and visualization without, or with only minimal, programming. Since 2006, KNIME has been used in pharmaceutical research,[3] it also used in other areas like CRM customer data analysis, business intelligence, and financial data analysis. KNIME's headquarters are based in Zurich, with additional offices in Konstanz, Berlin, and Austin.

KNIME a free and open-source data analytics, reporting, and integration platform

Google, Inc.

Kaggle is an online community of data scientists and machine learners, owned by Google, Inc. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges. Kaggle got its start by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science.

Community of data scientists to share, analyze, & discuss data

Kaggle Datasets

mloss

Our goal is to support a community creating a comprehensive open source machine learning environment. Ultimately, open source machine learning software should be able to compete with existing commercial closed source solutions. To this end, it is not enough to bring existing and freshly developed toolboxes and algorithmic implementations to people's attention. More importantly the MLOSS platform will facilitate collaborations with the goal of creating a set of tools that work with one another. Far from requiring integration into a single package, we believe that this kind of interoperability can also be achieved in a collaborative manner, which is especially suited to open source software development practices.

Producing reproducible research via open-source software.

Formatting

Text Editing

Code Conversion

Manuscript Editing

Online Writing

Permalinking

XPANSA

WHAT IS SCI.AI
sci.AI is a free platform that “understands” research papers and “explains” them to analytics and search algorithms. It takes biomedical research in plain text and produces semanticized machine-readable versions. 

These structured versions are designed to simplify the publishing process, to provide readers with beautiful easy-to-read HTML versions of the papers and to help search engines retrieve relevant papers, therefore increasing their impact.

OUR VISION
The current time-to-market in biomedical innovations is too long. Through the use of relevant algorithms and a global knowledge graph, our goal is to make scientific innovation at least 2x faster.

Publishing with biomedical metadata has never been so easy

sci.AI

Open Access Publication

Journal Platform

Journal List

Bibliography Options

EurekaMag

Covering life, earth, and health science scholarly literature, the site contains 52+ million articles, 30 million abstracts, and over 2 million PDF full texts. It was launched in November 1998, covering biology, applied life sciences, agriculture, horticulture and forestry, earth, environmental, and medical sciences. It features many disciplines of biology. Horticultural topics cover the cultivation and production of primary and secondary fruit and vegetable species, whereas other subjects include information on numerous aspects of agriculture and forestry. Other science disciplines covered on this site are the environmental sciences, including biodiversity and global warming, as well as health sciences.

An online learning portal that provides articles & textbooks based on natural sciences.

Outreach

Academic Social Network

Researcher Profiles

Publisher

Discover Research

Discover Experts

Discover Research Groups

Center for Open Science

An open source software project that facilitates open collaboration in science research. This framework was used to work on a project in the reproducibility of psychology research. The reproducibility project samples from three major journals: Journal of Personality and Social Psychology, Psychological Science, and Journal of Experimental Psychology: Learning, Memory, and Cognition. Scientists from all over the world volunteer to replicate a study of their choosing from these journals, and follow a structured protocol for designing and conducting a high-powered replication of the key effect. Whilst OSF initially focused on psychology, it has since broadened into any research field.

Open source software that facilitates open collaboration in science research.

Open Science Framework

Code Analysis

Annotating

CrowdTruth

CrowdTruth is an approach to machine-human computing for collecting annotation data on text, images and videos. The approach is focussed specifically on collecting annotation data by capturing and interpreting inter-annotator disagreement.

Open-source framework for crowdsourcing annotation data on text, images, videos

Commenting

Tagging

HyperStudio, Massachusetts Institute of Technology

Annotation Studio is an open-source web application that engages students in close reading and textual interpretation. It allows members of groups or classes to take notes on a shared document. Users can upload their own texts, and annotate with styled text, video, images, and weblinks. It is designed for teaching and learning in the humanities, and with aspirations to more general use. To date, the project has been used with great success in disciplines such as Writing, Literature, Foreign Languages, Anthropology, Film and Media Studies, and others at institutions including Harvard.

An open-source, a suite of collaborative web-based annotation platform.

Annotation Studio

Reviews

Collaborative Review

Reference Managing

Annotate.co

Annotate provides smarter document collaboration made for the digital workplace providing a single, secure platform that gets everyone working together seamlessly, from the first draft to the final sign off. Their intuitive, feature-rich solution is used to create, share, discuss, review and verify documents. It helps you organize your research material, collaborate for peer review and provide or gather feedback on assignments and learning materials. students can annotate documents offline or in the cloud.

Annotate and collaborate on documents and images.

Europeana

Europeana works with thousands of European archives, libraries, and museums to share cultural heritage for enjoyment, education, and research. It builds on Europe’s rich cultural heritage and makes it easier for people to use for work, learning, or pleasure. It brings together organisations that have great content, with the people and sectors that want to research, share, and create new things.
Europeana Collections provides access to over 50 million digitised items – books, music, artworks, and more – with sophisticated search and filter tools to help you find what you’re looking for. The dedicated thematic collections on art, fashion, music, photography, and World War I contain galleries, blogs, and exhibitions to inform and inspire.

Platform for digital cultural heritage, with a mission to "transform the world with culture". 

JetBrains s.r.o.

PyCharm provides smart code completion, code inspections, on-the-fly error highlighting and quick-fixes, along with automated code refactorings and rich navigation capabilities. PyCharm integrates with IPython Notebook, has an interactive Python console, and supports Anaconda as well as multiple scientific packages including matplotlib and NumPy. Run, debug, test, and deploy applications on remote hosts or virtual machines, with remote interpreters, an integrated ssh terminal, and Docker and Vagrant integration.

The Python IDE for Professional Developers.

pyCharm

Thinkable

Individuals & organisations:

- Host & Manage any funding opportunity that challenges the community around objectives important to them.
- Access & attract the world’s most innovative researchers in over 250 specialist fields from over 1400 top institutions.
- Ideate, award & collaborate on projects most aligned with innovation objectives.
- Promote their organisations to the worlds top students, scientists & PhD’s.

Scientists & researchers:

- Find funding from external organisations by applying to opportunities that leverage their skills and interest them the most.
- Build their profiles by showcasing research & sharing knowledge.
- Reward peers by learning & voting on projects in your field of expertise.
- Engage the public by sharing specialist knowledge and fact-checking claims made in your field.

Host prizes in science, promoted to researchers, societies and universities.

University of Groningen

GROningen MAchine for Chemical Simulations (GROMACS) is a molecular dynamics package mainly designed for simulations of proteins, lipids, and nucleic acids. It was originally developed in the Biophysical Chemistry department of the University of Groningen and is now maintained by contributors in universities and research centers worldwide. GROMACS is one of the fastest and most popular software packages available and can run on central processing units (CPUs) and graphics processing units (GPUs). It is free, open-source software released under the GNU General Public License (GPL),[3] and starting with version 4.6, the GNU Lesser General Public License (LGPL).

A software package for the simulation of biological macromolecules.