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The Challenges of Intellectual Property and Data Integrity in Research

The Challenges of Intellectual Property and Data Integrity in Research Intellectual property and...

The Challenges of Intellectual Property and Data Integrity in Research

Intellectual property and data integrity are two critical issues in research. In closed environments, the promulgator has the sole discretion to control both the intellectual property at hand and the integrity of that content. In open-access environments, the Intellectual Property (IP) is controlled to varying degrees by the Creative Commons License associated with the content. However, it is solely up to the promulgator to control the integrity of that content. Added to that, open-access environments don’t offer native protection to data in such a way that the data can be accessed and utilized for Text Mining (TM), Natural Language Processing (NLP), or Machine Learning (ML).

The Open Access Movement

As the costs of for-profit promulgator’s journals have gone up, it has caused a void between research and the researcher. In response to this, the Open Access movement took root among researchers and scientists who wanted greater access to the ownership and rights of their own and others’ content. Many researchers around the world gathered in Budapest in February 2002 to decide on global access to publications free of legal and price barriers to enhance citizen science. This campaign led to issuing the declaration Budapest Open Access Initiative, the starting point for the open access movement that brought about citizen science. From there, the Open Access Movement has gained ground within the various scientific communities around the world, greatly impacting scientific publishing along the way.

The Role of Creative Commons License

The Open Access Movement then gave rise to the Creative Commons licensing strategy, allowing authors to define which control they will retain or give away for their content. The Creative Commons strategy has opened the door to allow the author to control more of their content’s usage structures.

The Federated Cloud Environment

It is our intent in this paper to lay out a third option – that of a federated cloud environment wherein all members of the federation agree upon terms for copyright protection, the integrity of the data at hand, and the use of that data for Text Mining (TM), Natural Language Processing (NLP) or Machine Learning (ML). The federated cloud environment can provide a solution to the challenges of intellectual property and data integrity in research and other purposes.

The federated cloud environment is a distributed system of cloud computing resources owned and operated by different organizations but working together as a single system. In this environment, all members of the federation agree upon terms for copyright protection, data integrity, and data utilization. The federated cloud environment can provide a solution to the challenges of intellectual property and data integrity in research and other purposes.

Benefits of the Federated Cloud Environment

The federated cloud environment offers several benefits for researchers and scientists:

Copyright Protection

The federated cloud environment provides a mechanism for copyright protection that is agreed upon by all members of the federation. This ensures that the intellectual property of the content is protected and that the content is used in a way that is consistent with the terms of the agreement.

Data Integrity

The federated cloud environment provides a mechanism for data integrity that is agreed upon by all members of the federation. This ensures that the data is accurate and reliable and that it is used in a way that is consistent with the terms of the agreement.

Data Utilization

The federated cloud environment provides a mechanism for data utilization that is agreed upon by all members of the federation. This ensures that the data is used in a way that is consistent with the terms of the agreement and that it is accessible and usable for Text Mining (TM), Natural Language Processing (NLP) or Machine Learning (ML).

Where do we go from here?

Intellectual property and data integrity are two critical issues in research. The Open Access Movement and the Creative Commons licensing strategy have provided solutions to some of these issues. However, the federated cloud environment can provide a third option for copyright protection and data integrity. Researchers and scientists must decide which option is best for their research and other purposes. The federated cloud environment offers several benefits for researchers and scientists, including copyright protection, data integrity, and data utilization.

Here’s the path we recommend:

  1. Make a license. We have worked directly with Perkins Couie to create a Federated Data License that you can fill out and download for your business. Fill it out and route it around so that you are protected!

  2. Sign up for the CCH and start learning PlantUML (a simple text-based system) to create data flow diagrams to help you understand where your data is going. To help you get started, we’ve created a diagram that walks you through questions you need to ask about your content and what you need to think about regarding your content’s usage for AI purposes. Check out the diagram.