Core Concept


Modern day science has been a collective effort of different researchers and research groups. The collective intellectual power gathered by the scientific ecosystem is akin to the group intelligence (the “wisdom of crowds”) where a wise crowd is generally more intelligent compared to individual members in the group. The additional gain in intelligence is primarily dependent on the efficient flow of value (capital, information, etc.) among the members. The scientific community is still dependent on the rudimentary system for value flow, which is highly centralized, opaque, and redundant. Thereby it suffers from several problems: funding agencies are controlled by a small number of people, majority of scientists’ time is consumed by grant application writing with small success rates, a slow publication process, institutional biases, underpaid researchers, irreproducible publications, high subscription fees for journals, and a general focus on quantity of scientific publications over quality. These problems can be solved and the overall efficiency of the scientific community can be improved by creating an open and decentralized scientific ecosystem based on blockchain technology (or its variants). Open Science Organization (OSO) will be a decentralized community that will create an open and democratic self-sustaining scientific ecosystem.


GIP

Generalized Idea Protcol (GIP) will allow us to track the evolution of ideas over time as well as quantify the similarity of two ideas. GIP will facilitate the efficient sharing of the ideas and prevent the community from reinventing wheels, thereby accelerating the pace of the scientific research.

Quantification of expertise

The level of expertise or e-value of an entity (general individual, researcher, research group, organization, etc.) in a research domain D will be computed using e-function.

Open and Democratic funding

In OSO funding mechanism, there will be two voting stages: 1) Direction vote: the first voting stage decides the funding distribution to different research domains and projects, 2) Matching vote: the second stage decides the matching of the funded projects to the funding applicants.

Open and Democratic Review

The review process will be open to the public. It will consist of two stages: initial review and perpetual review.

 

Unique Researcher Identity(URI)


This project envisions the solution to the problem of unique researcher identity(URL). Our team is working on creating a unique research idenity which can be stored, tracked, shared and audited levaraging the block chain technologies. This would include the complex mapping of researcher's profile with his/her ideas, publications and activities. Following is the visaulization of how URI can be realized through the combination of existing solutions.


Find more about how we are progressing on this project through our github .

Generalized Idea Protocol(GIP)


GIP is a protocol that defines an idea and the relationship between two or more ideas. The relationship between two ideas will define:

  • the association strength between the ideas
  • the agreement between the owners of the ideas
  • the idea flow between them
  • the value flow between them.
If an idea B which is dependent on idea A generates value of $100, how is this value shared to the idea A? and how does the value shared to idea A (let's say $5) is shared to the ideas it was based upon? In other words, how does the value flow back?
With GIP, each unique idea can be identified and its evolution over the time can be tracked. In addition, it will give us a framework to evaluate the relationship between two different ideas. One way of modeling GIP would be by a directed acyclic graph (DAG) that grows over time. Each node of the DAG will be an GIP object representing a unique idea. An GIP object will contain all the information required to represent a unique idea. If there is a publication or data (stored as an IPFS object) related to an idea, its GIP object will contain the cryptographic hash of the IPFS object.
GIP will allow us to track the evolution of ideas over time as well as quantify the similarity of two ideas. The similarity score can be a hybrid of the market-driven score (decided by the scientific community via voting) and the algorithmic score generated from the GIP protocol. GIP will facilitate the efficient sharing of the ideas and prevent the community from reinventing wheels, thereby accelerating the pace of the scientific research. In addition, a good visualization of GIP objects will help the scientific community to identify the pain points of scientific research. Similarly, it can be used to find the optimal distribution of available resources (e.g. fund allocation) required in order to maximize scientific throughput. Loosely speaking, GIP will store the collective thought process of the whole scientific community.
Find more about how we are progressing on this project through our github .

Researcher Index(RR-Index)


Researcher Index (RR-index), as its name suggests is a ranking mechanism for the researchers. This project aims to quanity the research impact of the research/project ideas using the existing block chain technologies. RR-index will be a data driven domain independent metric to compute the values created by the ideas and researchers in OSO ecosystem. This technology will not only help to improve the quality of research contributions but will also set a benchmark for researchers away from our domain as well. RR-index will employ various methods like author-level metric, statistical model, machine learnings and blockchain technology to establish unbaised and robust indexing mechanism.

Find more about how we are progressing on this project through our github .

Storage


The final block of the OSO platform is the storage. The storage itself has to be smart enough to support human readable queries. The existing decetralization file storage, Interplanetery File System (IPFS) only allows look-ups for the files using its hash generated while storing in the IPFS network. OSO's storage and query layer atops IPFS to support smart queries.

Find more about how we are progressing on this project through our github .

The team


Gajendra Jung Katuwal

Gajen J. Katuwal

Member (Vision, Research)
Scientist (Machine Learning + Blockchain), Philips Innovations Lab
PhD in Imaging Science (Machine Learning), Rochester Institute of Technology
Keith Smith

Keith Smith

Member (Developer, Research)
Solutions Architect, Cloudera
M.A. in Economics, University of Arizona
Kirk Gosik

Kirk Gosik

Member (Research)
Computational Biologist Post Doc, Broad Institute
PhD in Biostatistics (Statistical Genetics), Penn State University
Bikos

Bikrant Gautam

Member (Developer)
Front-end Developer, Corvex Connected
M.S. in Computer Science and Information Security, St. Cloud State University
Abinash Koirala

Abinash Koirala

Member (Developer)
Software Engineer, Move Inc.
M.S. in Information Technology, Rensselaer Polytechnic Institute
Robert Chen

Robert Chen

Member (Developer)
Data Scientist, Flatiron Health
Ph.D. Computer Science (Machine Learning), Georgia Tech
B.S. Mathematics, Computer Science, Massachusetts Institute of Technology
Eric Gagnon

Eric Gagnon

Member (Developer)
Data Scientist, Penn State Health
M.S. Applied Statistics, Penn State University
Joseph Netti

Joseph Netti

Member (Developer)
Blockchain Researcher, Draper
President, RIT Blockchain Club
Can Jin

Zheng Liu

Member (Research)
Associate Professor, The University of British Columbia
Can Jin

Can Jin

Member (Developer)
Engineer/Scientist, Apple
PhD in Imaging Science, Rochester Institute of Technology

Advisors


Stanislaw Radziszowski

Stanislaw Radziszowski

Prof. of Computer Science, Rochester Institute of Technology
Mathematician and computer scientist, best known for his work in Ramsey theory.
Prof. Stefi Baum

Prof. Stefi Baum

Dean, Faculty of Science at University of Manitoba
Helped to develop the Hubble telescope.

Contributors


Sujan Khadka
Software Engineer at Uber ATG
Kevin A Lyons
EECS @ MIT Full Stack Developer at Nodal
Oaponbc
Editor at a reputed scientific journal
Andrew Kang
Healthcare Consultant, ZS Associates
James Ding
Forward Deployed Engineer, Palantir
Enbo Zhao
PhD candidate in Material Science and Engineering, Georgia Tech (5th year)
Neha Mittoor Changappa
Entrepreneur (https://www.digitallisto.com/), Full Stack Web Developer, Blockchain Technology Enthusiast
Noman Land

FAQ


Modern day science has been a collective effort of different researchers and research groups. The collective intellectual power gathered by the scientific ecosystem is akin to the group intelligence (the “wisdom of crowds”) where a wise crowd is generally more intelligent compared to individual members in the group. The additional gain in intelligence is primarily dependent on the efficient flow of value (capital, information, etc.) among the members. The scientific community is still dependent on the rudimentary system for value flow, which is highly centralized, opaque, and redundant. Thereby it suffers from several problems like funding agencies are controlled by a small number of people, majority of scientists’ time is consumed by grant application writing with small success rates, a slow publication process, institutional biases, underpaid researchers, irreproducible publications, high subscription fees for journals, and a general focus on quantity of scientific publications over quality. These problems can be solved and the overall efficiency of the scientific community can be improved by creating an open and decentralized scientific ecosystem based on blockchain technology (or its variants). Open Science Organization (OSO) will be a decentralized community that will create an open and democratic self-sustaining scientific ecosystem.

Inter Planetery Idea System (IPIS) will allow us to track the evolution of ideas over time as well as quantify the similarity of two ideas. IPIS will facilitate the efficient sharing of the ideas and prevent the community from reinventing wheels, thereby accelerating the pace of the scientific research.

Contact us


contact@oso.network

#osoNetwork

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OpenScienceOrg

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