Blockchain Papers

Ayushi Sharma, Shashwat Tiwari, Nitin Arora, S. C. Sharma

Blockchain is an emerging technology that can radically improve transactions security at banking, supply chain, and other transaction networks. It's estimated that Blockchain will generate $3.1 trillion in new business value by 2030. Essentially, it provides the basis for a dynamic distributed ledger that can be applied to save time when recording transactions between parties, remove costs associated with intermediaries, and reduce risks of fraud and tampering. This book explores the fundamentals and applications of Blockchain technology. Readers will learn about the decentralized peer-to-peer network, distributed ledger, and the trust model that defines Blockchain technology. They will also be introduced to the basic components of Blockchain (transaction, block, block header, and the chain), its operations (hashing, verification, validation, and consensus model), underlying algorithms, and essentials of trust (hard fork and soft fork). Private and public Blockchain networks similar to Bitcoin and Ethereum will be introduced, as will concepts of Smart Contracts, Proof of Work and Proof of Stack, and cryptocurrency including Facebook's Libra will be elucidated. Also, the book will address the relationship between Blockchain technology, Internet of Things (IoT), Artificial Intelligence (AI), Cybersecurity, Digital Transformation and Quantum Computing. Readers will understand the inner workings and applications of this disruptive technology and its potential impact on all aspects of the business world and society. A look at the future trends of Blockchain Technology will be presented in the book.

Edward Meinert, Abrar Alturkistani, Kimberley Foley, Tasnime Osama · 9 authors

BACKGROUND A blockchain is a digitized, decentralized, distributed public ledger that acts as a shared and synchronized database that records cryptocurrency transactions. Despite the shift toward digital platforms enabled by electronic medical records, demonstrating a will to reform the health care sector, health systems face issues including security, interoperability, data fragmentation, timely access to patient data, and silos. The application of health care blockchains could enable data interoperability, enhancement of precision medicine, and reduction in prescription frauds through implementing novel methods in access and patient consent. OBJECTIVE To summarize the evidence on the strategies and frameworks utilized to implement blockchains for patient data in health care to ensure privacy and improve interoperability and scalability. It is anticipated this review will assist in the development of recommendations that will assist key stakeholders in health care blockchain implementation, and we predict that the evidence generated will challenge the health care status quo, moving away from more traditional approaches and facilitating decision making of patients, health care providers, and researchers. METHODS A systematic search of MEDLINE/PubMed, Embase, Scopus, ProQuest Technology Collection and Engineering Index will be conducted. Two experienced independent reviewers will conduct titles and abstract screening followed by full-text reading to determine study eligibility. Data will then be extracted onto data extraction forms before using the Cochrane Collaboration Risk of Bias Tool to appraise the quality of included randomized studies and the Risk of Bias in nonrandomized studies of Interventions to assess the quality of nonrandomized studies. Data will then be analyzed and synthesized. RESULTS Database searches will be initiated in September 2018. We expect to complete the review in January 2019. CONCLUSIONS This review will summarize the strategies and frameworks used to implement blockchains in health care to increase data privacy, interoperability, and scalability. This review will also help clarify if the strategies and frameworks required for the operationalization of blockchains in health care ensure the privacy of patient data while enabling efficiency, interoperability, and scalability.

Flávio Codeço Coelho

Abstract Disease surveillance, especially for infectious diseases, is a complex and inefficient process. Here we propose an optimized, blockchain-based monitoring and reporting process which can achieve all the desired features of an ideal surveillance system while maintaining costs down and being transparent and robust. We describe the technical specifications of such a solution and discuss possibilities for its implementation. Finally, the impact of the adoption of distributed ledger technology for disease surveillance is discussed.

Jia Bainga Kangbai, P. Rohini Bai, Sulaiman Mandoh, Abu Bakarr Fofanah · 8 authors

Objective: In the absence of any approved therapeutics and vaccines to treat or prevent Ebola infection, managing Ebola outbreak largely depends on early case detection and surveillance, real-time communication of surveillance data, and Ebola case management. Here we assessed the possibility of uploading data obtained by Internet of Internet device that monitors cellphone company’s Call Data Records (CDR), national demographic census, national transportation system and Ebola vaccine production databases on a Blockchain platform to conduct real-time Ebola contact tracing, transmission pattern surveillance and vaccine delivery. Results: Mobility data obtained by Internet of Things (IoT) from CDR from cellphone companies, national transportation system, and census demographic data can be integrated into a Blockchain platform to provide real-time Ebola surveillance and contact-tracing. While cellphone data provides a unique opportunity to quantify human mobility, Blockchain system magnifies such opportunity by making the data accessible to many actors in real-time. By mounting data from CDR, national population census, national transport system and Ebola vaccine production database on a Blockchain platform will provide additional lens in our understanding of the role played by human population dynamics in the spread as well and containment of Ebola during outbreaks

Johannes Bleher, Thomas Dimpfl

No abstract is available for this record.

Aaron Yelowitz, Matthew W. Wilson

The anonymity of Bitcoin prevents analysis of its users. We collect Google Trends data to examine determinants of interest in Bitcoin. Based on anecdotal evidence regarding Bitcoin users, we construct proxies for four possible clientele: computer programming enthusiasts, speculative investors, Libertarians and criminals. Computer programming and illegal activity search terms are positively correlated with Bitcoin interest, while Libertarian and investment terms are not.

Mamuka Djibuti, Natia Rukhadze, David R. Hotchkiss, Thomas P. Eisele · 5 authors

No abstract is available for this record.

Jeffrey P. Cohn

In June the Office of Management and Budget proposed new, congressionally mandated guidelines to ensure the quality of the data gathered and disseminated by federal agencies. The new law augments the Paperwork Reduction Act, which already requires federal agencies to adopt processes to ensure data quality. Many scientists, however, worry that the guidelines—which require agencies to devise and implement procedures that make it possible for individuals to challenge the accuracy of agency information—could impede or prevent the flow of scientific information and undermine the peer review process. Comments submitted to OMB by 55 scientific societies and academic institutions, including the American Institute of Biological Sciences, supported the intent of the law. “As biomedical researchers whose work depends on the excellence of our own data, we are acutely aware of and sensitive to the importance of accurate data,” wrote Robert Rich, M.D., president of the Federation of American Societies for Experimental Biology (FASEB). The problem, scientists say, is not with the intent of the law but with the vagueness of the guidelines OMB proposes for implementing it. In particular, scientists argue that challengers seeking a correction of an agency's data should have expertise in the subject matter and should disclose any financial interest at stake in the outcome of the challenge. There should be a clear burden of proof on the person or group who made the initial charge to demonstrate why the data being challenged are inaccurate or wrong, added Elaine Hoagland, national executive officer for the Council on Undergraduate Research. Further, the OMB rules should contain adequate safeguards against frivolous challenges of scientific information. Those safeguards should allow government agencies to insist on the same degree of rigor and objectivity required of the original science, says Stephen Heinig, senior staff associate at the Association of American Medical Colleges (AAMC). “Scientists can fight out issues of data and methodology in the literature,” Heinig says. “That's the standard. We don't see any reason to change it.” And, noted AAMC President Jordan Cohen, the procedures mandated by the guidelines will be burdensome to agencies, whose staff—already struggling to meet core missions—will have to shoulder supervisory and reporting tasks that contribute little to the agencies' missions. Citing “errors” in Environmental Protection Agency data, as well as the sheer volume of information that EPA and other government agencies post on the Internet, Jim Tozzi explains that “we felt the need to ensure the quality of government data.” Tozzi, a former OMB official who is now a board advisor to the Center for Regulatory Effectiveness, an independent policy group that helped draft the new law, calls the debate over OMB's data quality proposals “a big hullabaloo over nothing.” Not so, say Washington's scientific and educational groups. “There is plenty of potential here for mischief,” notes Richard Harpel, director of federal relations for the National Association of State Universities and Land Grant Colleges. In part, that is because the draft guidelines are very subjective, says Joanne Carney, director of the Center for Science, Technology and Congress at the American Academy for the Advancement of Science. Robert Wells, president of the American Society for Biochemistry and Molecular Biology, expressed the views of many scientific societies when he pointed out that key terms in the guidelines are not defined: “OMB asked for comment on the definitions of the terms ‘quality,’ ‘utility,’ ‘objectivity,’ and ‘integrity’…· [but] we are unable to find any definitions of these terms in the proposed guidelines…·. It may seem to the drafters of this proposal that these terms are self-explanatory, but in fact they are not, at least as far as science and regulatory policy are concerned.” It isn't even clear who will be covered by the guidelines, which are silent on the question of applicability to federal grant recipients. “Any attempted federal restriction on dissemination of academic research would be wholly unacceptable in principle and would likely raise First Amendment considerations,” Heinig wrote. The guidelines “should specifically exclude academic and other non-federal institutions performing research under federal grants.” FASEB's Rich questioned OMB's proposal that government data “be substantially reproducible upon independent analysis.” “Who will conduct these [independent] studies and who will pay for them?” he wondered. “How can research studies [that] may have taken place over a period of years and used biological substances be ‘substantially reproduced’?” Rich also faulted OMB's proposal that federal agencies report the number and nature of complaints regarding their compliance with the guidelines. “The number of complaints received rather than the validity of the complaints could unfairly impact the reputation of an agency and//or its funded investigators,” he wrote. “A large number of complaints on a scientific matter could simply reflect a controversial issue…·rather than the excellence of the science.” The bottom line, Harpel says, is that by seeking to ensure high-quality scientific data, OMB could interrupt ongoing research and leave government agencies and their researchers open to harassment by special interests. That, he states, would “make it harder to be a scientist.”