OSOUM Framework for Trading Data Research
- URL: http://arxiv.org/abs/2103.01778v1
- Date: Thu, 18 Feb 2021 09:20:26 GMT
- Title: OSOUM Framework for Trading Data Research
- Authors: Gregory Goren, Roee Shraga, Alexander Tuisov
- Abstract summary: We supply, to the best of our knowledge, the first open source simulation platform, Open SOUrce Market Simulator (OSOUM) to analyze trading markets and specifically data markets.
We describe and implement a specific data market model, consisting of two types of agents: sellers who own various datasets available for acquisition, and buyers searching for relevant and beneficial datasets for purchase.
Although commercial frameworks, intended for handling data markets, already exist, we provide a free and extensive end-to-end research tool for simulating possible behavior for both buyers and sellers participating in (data) markets.
- Score: 79.0383470835073
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In the last decades, data have become a cornerstone component in many
business decisions, and copious resources are being poured into production and
acquisition of the high-quality data. This emerging market possesses unique
features, and thus came under the spotlight for the stakeholders and
researchers alike. In this work, we aspire to provide the community with a set
of tools for making business decisions, as well as analysis of markets behaving
according to certain rules. We supply, to the best of our knowledge, the first
open source simulation platform, termed Open SOUrce Market Simulator (OSOUM) to
analyze trading markets and specifically data markets. We also describe and
implement a specific data market model, consisting of two types of agents:
sellers who own various datasets available for acquisition, and buyers
searching for relevant and beneficial datasets for purchase. The current
simulation treats data as an infinite supply product. Yet, other market
settings may be easily implemented using OSOUM. Although commercial frameworks,
intended for handling data markets, already exist, we provide a free and
extensive end-to-end research tool for simulating possible behavior for both
buyers and sellers participating in (data) markets.
Related papers
- A Survey on Data Markets [73.07800441775814]
Growing trend of trading data for greater welfare has led to the emergence of data markets.
A data market is any mechanism whereby the exchange of data products including datasets and data derivatives takes place.
It serves as a coordinating mechanism by which several functions, including the pricing and the distribution of data, interact.
arXiv Detail & Related papers (2024-11-09T15:09:24Z) - Private, Augmentation-Robust and Task-Agnostic Data Valuation Approach for Data Marketplace [56.78396861508909]
PriArTa is an approach for computing the distance between the distribution of the buyer's existing dataset and the seller's dataset.
PriArTa is communication-efficient, enabling the buyer to evaluate datasets without needing access to the entire dataset from each seller.
arXiv Detail & Related papers (2024-11-01T17:13:14Z) - Data Measurements for Decentralized Data Markets [18.99870296998749]
Decentralized data markets can provide more equitable forms of data acquisition for machine learning.
We propose and benchmark federated data measurements to allow a data buyer to find sellers with relevant and diverse datasets.
arXiv Detail & Related papers (2024-06-06T17:03:51Z) - Data Acquisition: A New Frontier in Data-centric AI [65.90972015426274]
We first present an investigation of current data marketplaces, revealing lack of platforms offering detailed information about datasets.
We then introduce the DAM challenge, a benchmark to model the interaction between the data providers and acquirers.
Our evaluation of the submitted strategies underlines the need for effective data acquisition strategies in Machine Learning.
arXiv Detail & Related papers (2023-11-22T22:15:17Z) - Dynamic Datasets and Market Environments for Financial Reinforcement
Learning [68.11692837240756]
FinRL-Meta is a library that processes dynamic datasets from real-world markets into gym-style market environments.
We provide examples and reproduce popular research papers as stepping stones for users to design new trading strategies.
We also deploy the library on cloud platforms so that users can visualize their own results and assess the relative performance.
arXiv Detail & Related papers (2023-04-25T22:17:31Z) - A Survey of Data Pricing for Data Marketplaces [77.3189288320768]
This paper attempts to comprehensively review the state-of-the-art on existing data pricing studies.
Our key contribution lies in a new taxonomy of data pricing studies that unifies different attributes determining data prices.
arXiv Detail & Related papers (2023-03-07T04:35:56Z) - A Survey of Data Marketplaces and Their Business Models [0.0]
"Data" is becoming an indispensable production factor, just like land, infrastructure, labor or capital.
Tasks ranging from automating certain functions to facilitating decision-making in data-driven organizations increasingly benefit from acquiring data inputs from third parties.
New entities and novel business models have appeared with the aim of matching such data requirements with the right providers.
arXiv Detail & Related papers (2022-01-11T12:27:37Z) - Cross-Market Product Recommendation [22.385250578972084]
We study the problem of recommending relevant products to users in resource-scarce markets by leveraging data from similar, richer in resource auxiliary markets.
We introduce and formalize the problem of cross-market product recommendation, i.e., market adaptation.
We conduct extensive experiments studying the impact of market adaptation on different pairs of markets.
arXiv Detail & Related papers (2021-09-13T12:53:45Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.