A Research On Collaborative Research

According to Berson and Dubov (2011), there are four typical categories of drivers that explain the need for data management: Business Development, Sales and Marketing; Customer Service; Risk, Privacy, Compliance and Control; and Operational

Data is defined as useful raw material which is intended to be useful for both the originator and for the intended receiver. Data consists largely of facts and figures ideal for communicating the intended meaning. This data can be interpreted and can be categorised as follows;

One type of scientific data is COSHH record. COSHH record stands for control of substances hazardous to health, they contain information about health and safety for hazardous substances that are used in the workplace. This health and safety process is important as it ensures awareness and health and safety for hazardous substances that are used in the workplace. The people who are involved in using, storing and ordering of the substance e.g. technicians will have access and be able to change it whenever they would like to or need to in the technicians setting e.g. the control room using IT software.

As the year draws to an end one can easily answer that collaborative anthropology, is when the anthropologist teams up with research participants or the community to help solve the related anthropological issue. By doing so they can get more accurate and precise help and it is extremely beneficial to the people who are involved to be active in the issue as well seeing how it pertains to them. Not only this, but they can not just get experience themselves, but really help the anthropologist when there are social, cultural, and language barriers that can inflict the value of research. Through the year there were a few anthropologist that used collaborative research, but two of them were Jeanette Dickerson-Putman and Larry Zimmerman.

The organisation has the right to access any sort of data on its premise without previous notice.

Data is a valuable corporate resource; it has real, measurable value. The purpose of data is to aid evidence-based decision-making. Accurate, timely data is critical to accurate, timely decisions. Most corporate assets are carefully managed and data is no exception. Data is the foundation of our decision-making, so we must also carefully manage data to ensure that we know where it is, can rely upon its accuracy, and can obtain it when and where we need it.

Copyrighted issues: collector of primary data is the owner of that information and he need not share it with other companies and competitors.

The reuse promptsof resources for requires sharing of data that is trustworthy. Some of Tthe advantages of data sharing include: a) reanalysis of data helps verify results data; b) different interpretations or approaches to existing data contribute to scientific progress, especially in an interdisciplinary setting; c) well-managed, long term, preservation helps retain data integrity; d) when data is available, (re-)collection of data is minimized. Thus optimizing use of resources; e) data availability provides safeguards against misconduct related to data fabrication and falsification; and f) replication studies serve as training tools for new generation of researchers (Tenopir et al., 2011) are well documented [1]. There are several inherent problems to reap the benefits of data sharing. One of these problems is Identifying identifying and integrating related data from disparate sources is one of the major associated problems with data sharing as data is usually stored on disparate sources. This is compounded by failure to develop and maintain clear, well-annotated research datasets (metadata), which in turn results in loss of access and understanding of the original dataset overtime. Metadata helps users decide on the credibility and trustworthiness of data it is associated with. According to data sharing practices and perceptions survey of 1329 scientists, only a quarter (26%) of them were satisfied with tools for preparing metadata

Experimental research is sometimes done with risk of harming the subjects under study. In a research study, participants could be physically and emotionally harmed. As nurses, we are advocates for our patients. Therefore, our goal is to protect them from any harm and discomfort when they participate in experimental treatment. Many dilemmas arise when trying to determine the level where an experimental treatment becomes harmful. In the past, researchers conducted unethical experiments without the subjects’ informed consent. They conducted experiments on human subjects knowing the high potential for harm. Participants received harmful substances without their knowledge and did not receive treatment (Grove, Gray, & Burns, 2015). Researchers coerced, misinformed, and forced human subjects to participate in experimental research. Groves et al. (2015) reported few events from the past that displayed a breach of the participants’ privacy, confidentiality, and freedom. Rodriguez and Garcia (2013) also reported a study where American scientists infected a specific population in Guatemala with sexually transmitted diseases such as syphilis and gonorrhea. American researchers conducted unethical experiments on human subjects without proper informed consent and clearly caused harm to mentally and socially vulnerable participants. The American researchers carefully selected a segment of the Guatemalan population based on poverty level and mental capacity. They did not inform the

Recently in the research and development industry, there has been an increased push for qualified health researchers to share individual-level data of participants in their studies with fellow researchers (Bull, Roberts & Parker, 2015). The basis for the cultivation of this culture of sharing stems from the belief that multiple benefits can be reaped from practicing data sharing. These benefits include building a large international dataset and network to allow for cross-border collaborations to generate greater potential to address significant scientific queries, improving the transparency and reliability of research trials and preventing duplication of studies to avoid wastage of resources (Bull, Roberts & Parker, 2015; Bull et al., 2015). Different stakeholders in the health industry are eager to acquire such benefits, especially funders of research who are gradually making sharing of individual-level data in a study a compulsory condition for researchers who wish to secure funding (Bull, Roberts & Parker, 2015).

Then, it is necessary to support collaboration among specialised researchers and functional managers but also among the different consortia. The different consortia must share their resources and findings and not feel that they are competing the ones against the others.

The information age is also the age of massive data collection, of databases, records, data mining and big data in all it’s empowering and destructive potential. Not only since the Snowden leaks of 2012 has the question of, who records and who is being recorded become of interest to a wide audience. Access to such data collection, the knowledge about it and the subjects’ relation to all-encompassing technology have been the basis of many influential writings of the last two decades.

The security and protection of databases and compilations have been advanced in several ways including ‘low authorship’, ‘tort-mis-appropriation’ model and ‘Nordic sui generis. It precluded the adoption of data.[ ]

Publishing research data in articles could make it available for public to access. In this article, the authors have discussed about sharing the research data by letting public access it leads to a challenge of reusing the data. There are various questions that might arise in the researchers’ minds including queries about the legal rights, the owner of the rights, and rights for permission to share the data that leads to productive utilization of the data.

Data owner encrypts all the statistics earlier than uploading them to the cloud such that the encrypted data can be retrieved and decrypted by those who have the decryption keys. data owner executes algorithms namely setup and encrypt.