Data management planning (DMP): Tools focused on enabling preparation and submisssion of data management plans:
- DMPonline
- Argos (machine actionable data plan)
- RDMO (provided a comprehensive documentation in English, a demo area, and it's open source.)
Project planning: Tools designed to enable project planning:
- MS Project (the standard tool for project management.)
- Trello (probably the second most well known project management tool and, possibly, integration with Atlassiana.)
- Asana (looked more a project management tool than Monday.com, with connectors to other tools.)
Combined DMP/project: Tools which combine project planning with the ability to prepare data management plans:
- DSW (This is the only tool that combines everything in the description above.)
Quantitative data collection tool: Tools that collect quantitative data:
- MATLAB Data Aquistion Toolbox (a complete, although expensive, solution.)
- CEDAR Workbench (biomedical data) (emphasis on the metadata.)
Qualitative data collection (e.g. Survey tool): Tools that collect qualitative data:
- REDCap
- SurveyJS (interesting project open-source project to create forms for surveys.)
- Kobo
- TeamScope (Clinical Research Collection App)
- Animal Tracker App (track animals in the wild.)
- Track3D (track animals in a confined space)
- Citizen Science Tools (citizen science) (this seems to be a kind of marketplace for citizen science projects.)
Note: there isn't much science here since I'm not familiar with these tools.
Harvesting tool (e.g. WebScrapers): Tools that harvest data from various sources:
- Beautiful Soup (Python)
- Scrapy (Python)
- Netlytic (collect data from social media)
Electronic laboratory notebooks (ELNs): Tools that enable aggregation, management, and organization of experimental and physical sample data:
- Benchling (Biology)
- E-lab FTW (Open source)
- Mbook (Chemistry)
- RSpace ELN
Scientific computing across all programming languages: Tools that enable creation and sharing of computational documents
- Jupyter
- Mathematica
- WebAssembly
Metadata Tool: Tools that enable creation, application, and management of metadata, and embedding of metadata in other kinds of tools
- CEDAR Workbench (biomedical data)
Repository (e.g. MySQL, DSpace): Tools that structure and provide a framework to organise information
- Generalist repository: DSpace, Figshare, Zenodo, Dryad, etc.
- Data repository: CKAN, Dataverse, NOMAD-OASIS (material science), etc
- RDMS: Oracle, MySQL, MariaDB, Postgres, sqlite
Archive: Tools that facilitate the long-term storage of data
- Libsafe
- Preservica
Management tool (e.g. iRODS, GLOBUS, Mediaflux ): Tools that facilitate the organisation of data:
Data repository: Tools that enable storage, and public sharing of data
- Data repository: CKAN, Dataverse, NOMAD-OASIS
Electronic laboratory notebooks (ELNs): Tools that enable aggregation, organization and management of experimental and physical sample data
Scientific computing across all programming languages: Tools that enable creation and sharing of computational documents
Electronic laboratory notebooks (ELNs) Tools that enable aggregation, management, and organization of experimental and physical sample data
- Benchling (Biology)
- E-lab FTW (Open source)
- Mbook (Chemistry)
- RSpace ELN
Programming languages:
- Python (including Pandas, Numpy, etc.)
- R
- Julia
Extract, Transform, Load (ETL) tools: Tools that enable 'extract, transform, load'—a data integration process used to combine data from multiple sources into a single, consistent data set for loading into a data warehouse, data lake or other target system:
- Apache Spark
- Apache Hadoop
- Google: Cloud Data Fusion + Dataflow + Dataproc
- AWS Glue
- Microsoft SQL Server Integration Services (SSIS) or Azure Data Factory
- Oracle Data Integrator
Note: The problem with the term ETL is that implies big data.