Data is the bedrock of all machine learning systems. As such, working with the right data collection company is critical in order to solve a supervised machine learning problem.
If you don’t have a particular goal or project in mind, there is a wealth of open data available on the web to practice with. However, if you’re looking to tackle a specific problem, chances are you’ll need to collect data yourself or work with a company that can collect data for you.
There are many data collection companies that provide crowdsourcing services to help individuals and corporations gather data at scale. Working with a crowdsourcing partner allows teams to collect lots of diverse data at a fraction of the cost of traditional data collection methods.
How to Select the Best Data Collection Company
Before you select a data collection partner, consider the following factors:
- Experience: Does the company have an established track record of successful data collection projects? Logos, testimonials, and case studies allow you to get a closer look into the company’s background, solutions, and results.
- Technology: One of the key benefits of outsourcing the data collection process is access to pre-built data collection tools.
- Quality: Before partnering with any data collection company, ask what kinds of quality control mechanisms they have in place to ensure the quality of data.
Without further ado, here are the top providers of data collection services.
The Best Data Collection Companies for Machine Learning
Lionbridge AI is a data collection company that that partners with anyone with machine learning data needs, from research teams to the Fortune 500. While most other data collection companies do not support languages other than English, Lionbridge provides data services in over 300 languages. With solution centers in 27 countries, Lionbridge AI covers both simple data collection use cases as well as linguistically complex long-term projects. Unlike MTurk, Lionbridge manages the entire process, from designing workflows to sourcing qualified workers.
Working with Lionbridge unlocks access to a network of 500,000+ qualified linguists, in-country speakers, and experienced project managers capable of collecting data for a range of use cases. With over 20 years of experience, Lionbridge has built all the necessary crowd management capabilities necessary to source and manage thousands of contributors.
In addition to providing managed crowd services, Lionbridge AI also provides an open platform for users to design and manage their own data collection projects.
Also known as MTurk, Amazon Mechanical Turk is a crowdsourcing marketplace designed to recruit remote workers to complete labor-intensive tasks. These human intelligence tasks (HITs) range in length, complexity and compensation. MTurk has rapidly become a popular way to collect data for machine learning research due to its brand name and low cost appeal.
Despite these advantages, the tool is only feasible for small-scale data collection projects with budget constraints. While MTurk is often considered a cheap solution to data collection, there are actually many hidden costs. Requesters must be very explicit in defining HIT descriptions, which can be incredibly time consuming. As a result, good projects require a lot of effort to create and manage.
Another key problem in using MTurk to collect training data is the issue of quality control. The platform itself offers very little in the way of quality control mechanisms, advanced worker targeting, or detailed reporting. Whereas other companies conduct rigorous testing for their contributors, anybody with a computer and an internet connection can sign up and pick up jobs on MTurk.
Clickworker is a company based in Germany that offers a wide range of data collection and annotation services. The Clickworker crowd is comprised of registered users that perform small tasks (called microjobs) on their online platform. The company is capable of creating audio, photo and video datasets using its proprietary platform. Clickworker also supports a mobile application to make it easier to collect data from their contributors.
Appen is an Australian company that collects, annotates, and evaluates a variety of machine learning data types including speech, text, image, and video. The company uses remote crowdsourcing to complete tasks for AI use cases such as social media and online search evaluation. While much of Appen’s work revolves around moderating content, they also support data collection across a large number of languages. Being a service provider, Appen does not offer collection or annotation tools. Instead, they directly provide the data that they source through their crowd.
Globalme is a Vancouver-based data collection company. While the company doesn’t offer open access to the platform, they do offer crowd management and worker sourcing. In the past, Globalme has collected voice samples for smartwatches, speaker systems, in-car speech systems and general voice assistants. Aside from data collection, Globalme also offers testing and localization services.
On the hunt for the right data collection company? If you’re developing your own machine learning model, Lionbridge has over 20 years of experience and 1M+ staff ready to help. Whether you’re looking to train a virtual assistant or OCR system, Lionbridge is your home for crowdsourced data services.