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What is Mozilla Data Collective?

The Mozilla Data Collective is a pioneering platform designed to revolutionize the AI-data ecosystem by focusing on the needs of various communities. It empowers those who create and manage data to share their datasets in accordance with their own wishes, all while retaining ownership and control over who can access the information and under what conditions. Users have the capability to upload their datasets, choose from different licensing options—such as Creative Commons or custom licenses—set access parameters, and specify conditions for compensation or acknowledgment, whether they operate as individuals, cooperatives, or trusts. This initiative underscores the importance of ethical data management, transparency, and community empowerment, actively opposing exploitative data extraction methods and encouraging equitable participation. Featuring more than 300 high-quality datasets crafted by and for communities, the platform covers a diverse range of applications, including multilingual speech-data collections. Furthermore, it offers accessible tools like a public API, which helps developers seamlessly integrate these datasets into their applications, thus improving both accessibility and usability. The overarching goal of the Mozilla Data Collective is to cultivate a more equitable and inclusive landscape for data sharing and utilization, ultimately benefiting all stakeholders involved. Through this innovative approach, the platform hopes to inspire similar initiatives in the data community.

What is Conseris?

Conseris accounts provide the flexibility to generate an unlimited number of datasets for a single, affordable monthly fee. You can easily duplicate your current datasets with just a click or establish unique field sets for each dataset as needed. Data can be entered directly into our web application, or you can utilize our mobile app for offline data collection. With a simple code, you can invite an unlimited number of contributors at no extra charge, granting them access to your data. You have the capability to analyze your data from various perspectives with limitless filtering options, automatic aggregations, and suggested visualizations. This feature enables you to understand the structure of your data without the need to create custom charts. Furthermore, your work continues seamlessly beyond the office environment. Designed for dedicated researchers, Conseris ensures that your valuable ideas can thrive outside conventional spaces. Whether you find yourself far from home or in remote locations, Conseris is there to support your research endeavors.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$12 per user per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Mozilla

Date Founded

2005

Company Location

United States

Company Website

datacollective.mozillafoundation.org

Company Facts

Organization Name

Kuvio Creative

Date Founded

2015

Company Location

United States

Company Website

www.conseris.io

Categories and Features

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Popular Alternatives

Popular Alternatives

Conseris Reviews & Ratings

Conseris

Kuvio Creative