Data and metadata sharing is are crucial for both research and educational data. Educational data, in particular student-success initiatives, both funded and unfunded, often operate in isolation with little interaction outside of the department or college, and they are rarely connected to broader institutional efforts. Lack of knowledge sharing concerning initiative effectiveness and lessons learned makes it difficult to learn about promising and best practices and institutionalize them. This paper presents a framework for sharing metadata, enumerates various considerations of technologies and infrastructure that needs to be accounted for while building such a framework along with a thorough review of the related technologies and …show more content…
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
This document will be created at the beginning of the study and will be a “working” document until the completion of the study. This plan will include information relating to the nature of the project such as its title, a summary of the project, and the collaborators. The DMP will also outline who has access to the data, how it is shared, the retention requirements of the data, and how the data will be managed both during and after the completion of the study. Any processes outlined in this document will align with Swinburne’s Research Data Management Guidelines (Karick, 2014). An example of this is the storage of working versions of research data on personal computer hard drives, with the master copy uploaded onto a secure and personal file storage solution such as Cloudstor+. Cloudstor+ is an online storage repository provided within Australian by the Australia’s Academic and Research Network. As the data will be held on servers within Australia, compliance with the relevant Australian laws is made easier. The data for the study will be stored on Cloudstor+ for a minimum period of five years, as per the National Statement (NHMRC,
In order to maintain consistency throughout the study, each of the six subjects will utilise the same source for data collection. Due to the fact that sites vary in precision (number of decimal places), activity format and number of trials, this particular measure will assist in ensuring that the evidence used to address the claim is both accurate and reliable.
Replication, external review, and data recording and sharing, are important to the scientific method because it helps support the hypothesis even more. By replicating the experiment and sharing the data, it increases the validity of the experiment. Semmelweis included these concepts in his experiment by repeating the experiment multiple times, he showed a third party (other scientists) his experiment, and he shared his data and results to multiple sources, but scientists dismissed it.
This provides a guideline that ensures that researchers minimize the amount of risk a study may impose to a participant. When planning a study, it is also important that each of the participants are provided with a sense of security and not placed at a disadvantage. When participants enter into a study, a level of trust is established, and their identities and the information they provide must be protected and never be used against them or exploited for any reason.
* This phenomenon is best referred to as a “cumulative collaboration of evidence” (Pepper 49).
Tool validity is an extremely important aspect when gathering information used in research. There are many different tools that can be used depending on what is being researched. “Trustworthiness of the data can only be as good as the instruments or tests used to collect the data” (Boswell & Cannon, 2014). Many healthcare providers use research to increase their knowledge to help make decisions for changes in policy and procedures and in ways to care for patients.
Continued progress is very much dependent on community cooperation and vision. Barriers we anticipate include: realistic concerns about privacy law (HIPAA and FERPA). National standards and regulations for the exchange of health information are more developed than for educational records. Resistance of clinical, educational and social service professionals to change practice patterns to be able to effectively utilize cross-sector data. Significant change management and partnership development will be needed to implement new protocols to leverage an increasingly rich, yet potentially overwhelming, store of health, education and social service information (The strategic community plan for Miami Childrens Initiative,
Scientific merit is considered as a way to examine if our research study represents good science. Therefore, we will need to make sure that any research we are working on, clearly states the research questions and its overall objectives. The research should also include the contextual data that will also have peer-reviewed literature to support why the research is needed. We also should make sure that if human beings are being used as participants, that their privacy and safety will be respected, and if there is any possibility of harm, no matter how small it is, and the benefit and risks whether indirect or direct for the partakers in the study needs to be very clear in the research proposal. According to Gonzales (2013, para. 2, p. 1), the data collection, recruitment, and analysis should align with the research questions, as well as the monitoring, safe storage, and how the data will be destroyed should also be specified.
The article discusses the increasing trend of conducting replications, as opposed to novel idea studies Additionally, the article highlights that replications are becoming more common and can lead to debunking and discrediting another’s work. Unfortunately, with the focus being on replication, the time spent conducting and exploring new knowledge is consequently reduced. However, it is also suggested that replications provide accountability for scientists to ensure their work is of high quality. Questions to discuss in class: What do we think is the ultimate goal of conducting a replication versus an original study? How can scientists ensure that as a field, the
Through Validity, Bias and usefulness, we are able to determine how well the source can aid the research. The usefulness of
According to D.B. Resnik (2011), public trust is a common theme in the scientific field. Unfortunately, Resnik believes public trust in research has been used so extensively that its meaning has been diminished. The idea of public trust is important but its meaning may be too broad. Resnik's essay was written to help confine the term when discussing scientific research.
The need to educate the scientific community on scholarly integrity necessarily moves the issue beyond the individual. It is in first instance, research institutions that must provide students, faculty, and staff with guidelines and codes of practice on scholarly integrity, endorse appreciation for the diversity of views that may be brought to bear on issues, and inform about the institutional rules and government regulations that apply to research.
Researchers recognize reproducibility as the core of science and the path to cumulative knowledge (Freedman et al., 2015,2,3. Reproducibility reflects the fundamental
Bearing in mind that novices and experts provide data with the same level of accuracy, the richer dataset that will be provided by less knowledgeable contributors will afford the following: (1) Data that is more amenable to verification using the other non-diagnostic information provided by the contributor to verify it’s plausibility whereas, for expert contributors, we must take their word for it if they do not provide supporting information (Reason, 2000). (2) Data that can be repurposed for other previously anticipated and unanticipated uses(Parsons & Wand, 2014). (3) Richer datasets have a higher propensity for novel insights (Lukyanenko, Parsons, & Wiersma, 2014; Parsons, Lukyanenko, & Wiersma, 2011).
‘The Ultimate protection against research error and bias is supposed to come from the way scientists constantly test and retest each others results’ – To What extent would you agree with this claim in the natural and human sciences.