Scientific Data Made Easy


We live in an exciting age of unprecedented data growth across all aspects of our lives. The scientific community produces tremendous amounts of structured and unstructured data both in volume, and in a variety of formats. This data evolves at immense speeds. The way this data has been handled in the past is becoming inadequate and obsolete, drastically decreasing productivity.

Science Data Software is a company that sees a great opportunity to apply its passion for technology and innovation, its experience in building complex systems and its ability to find talented experts to the goal of helping scientists both connect with the data they need and gain powerful insights for productivity growth. We work in a number of domains including bioinformatics, spectroscopy, cheminformatics and statistical data collection, processing and management, data analytics and data driven solutions. We specialize in enterprise- level solutions that leverage the power of cloud computing to solve various data science problems.

VISION

Data Preservation and Security

  • Provide an easy and secure way to store data
  • Handle any amount of data
  • Enable flexible and intelligent data workflows

Data Transformation and Curation

  • Domain-specific processing
  • Machine learning algorithms to pre-process either structured or unstructured data
  • Validation and visualization
  • Collaborative curation

Data Discovery, Sharing, and Analytics

  • Make more data available on submission processes, guidelines and templates
  • Allow researchers to gain greater insight into data content, data origins and interconnections
  • Create intelligent analytical models to extract the most relevant information from data

PROJECTS

Open Science Data Repository

Open Science Data Repository (OSDR) is a platform focused on scientific data management
  • Various domain-specific data types supported
  • Integration with social networks and cloud drives
  • Real-time data deposition and processing
  • Microservice-based architecture
  • Integration with machine learning tools

Electronic Laboratory Notebook

  • Open source
  • Flexible workflows, tailored to your organization or laboratory
  • Custom screen constructor
  • Support for various file formats
  • Audit trail

Machine Learning

  • Simple and efficient APIs for machine learning model training
  • Compare machine learning algorithms
  • Predict biological activities, physicochemical properties, and other processes
  • Utilize pre-built algorithms, including: Support Vector Machines, Na├»ve Bayesian, k-Nearest Neighbors, Random Forest, Boosted Decision Trees, Logistic Regression, Deep Neural Networks
  • Share trained models with others

CLIENTS AND COLLABORATORS

Rockville, MD 20850, USA
Info at SciDataSoft.com