Data Producer: Sell a dataset

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Learn how toData ProducerSell a dataset

Sell a datasetHave valuable market insights? Unique survey results? Or just want to share your data with others? We've got you covered.Our intuitive and user-friendly interface will guide you through the process of uploading your dataset, setting a price per row, and reaching a wider audience of interested buyers. Get ready to monetize your data by turning it into a valuable asset and take the first step in becoming a successful data producer!We strongly suggest you read our section on Tailor your data.Preparing the saleFirst step is to upload your dataset, enter a title and upload the files you're looking to sell.

Great, now it's time to select the following: Index

IndexThis field is your primary key in the dataset, this means that every row has one unique index value, so it should never repeat.Here are a few examples:

Let's say you're looking at maximum temperatures per day.

Your index is a date, meaning that you can only have one maximum temperature per date (day).

Let's say you're looking at housing prices.

Your index is a house (house_id), meaning that a house (house_id) can only have one price.

Index TypeIndexes can be events, dates, users or clients, row numbers, receipt numbers, etc. Defining what type of index you are using in your dataset aids the buyer identify what they are ultimately paying for.It wouldn't be the same in a "Crossfit Gym" dataset to analyze activity in different dates, than it would be to analyze in different hours (throughout the day), another index could be the timestamp - which would analyze the dataset in date and time.Price Per Row (ppr)When we speak of the price per row, because an index has one unique row per time it appears, we are really speaking of the price per row of an indexed event/date/user/etc.If you know how much you're willing to sell each indexed observation (one day of activity in my instagram account is worth $__) you can just enter the amount.However, if you have a dataset and know how much you want to get for it, then you need to take the price of that dataset and divide it by the amount of indexed observations in it.For example:
Let's say you want to sell your farm's temperature recordings for the last year for $36,500. Your dataset has an average temperature per day, so it means your index is a date.
The ppr would be $3,650/365 days = 10 $/day. License

LicensingChoose the license that best fits your dataset. Listing

Listing

Public - your dataset will be listed in the data marketplace.

Private - only wallets you give access to will be able to find your dataset.

Unlisted - your dataset can only be accessed with the link we'll provide you.

Apply to buy order - your dataset will only appear in a buy order.

PaymentsThe type of payment you make available for your dataset will determine who's able to pay (or not) for your dataset.

If you choose FIAT, you'll have to connect a Stripe account (their registration is fairly simple and straightforward).

If you choose Cryptocurrency, you have to define which wallets you want to receive payments in.

Reminder: we will be handling ERC20 tokens, initially USDC on the polygon mainnet, and a stable coin for IOTA will be determined as soon as shimmer's EVM launches on their mainnet.

DescriptionThis is the most important part of your sales pitch. Here you'll be able to provide all sorts of details regarding your dataset. The objective of this section is to convince the purchaser they have been waiting for your data their whole life! Here are some of our suggestions:AboutGive a brief and informative overview of the dataset that you're selling. You should provide a concise yet descriptive summary of what the dataset contains, the time period it covers, and any unique features or variables that set it apart from other datasets. It's important to be clear and transparent about what the data represents, so that potential buyers can evaluate its relevance to their needs.SourceDetail where the data was sourced from, and any relevant information about the collection process that might be useful to potential buyers. Be specific and clear about how the data was collected, and any methodologies or tools used in the process. If the data was collected from multiple sources, be sure to list them all and describe how they were combined to create the final dataset.AcknowledgementsGive credit to any individuals or organizations that contributed to the creation of the dataset. If you relied on the work of others, or if the dataset is the result of a collaboration, make sure to acknowledge their contributions. This section also allows you to explain any limitations or potential biases in the data, and to provide context for potential buyers.Promote your dataThis is a feature for our premium members, our marketing team will help you determine your primary target and make sure your dataset offer reaches them. Interested? Talk to our sales team or reach out through Discord.StorageSubscriptionsLearning Nodes offers free storage up to 200mb.
If you need more, check out our pro and premium subscriptions.

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