This document discusses ethics in data warehousing and data mining. It notes that data mining can discover new patterns and relationships but also raises ethical issues when used to discriminate against groups for things like loans or special offers. The project manager is responsible for ensuring ethical use of data and establishing access controls and qualifications for users. Small data sets can also raise ethical concerns if users learn information they should not. The project manager must decide what public data is integrated and ensure end users, testing practices, and data mining applications comply with ethical standards and legal regulations.
Data Collection Tool Used For Information About IndividualsChristy Hunt
The document discusses surveys as a data collection tool used to gather information about individuals. Surveys can be conducted in various ways such as printed questionnaires, telephone interviews, mail, in-person interviews, online, etc. However, standardized procedures are used to ensure every participant is asked the same questions in the same way to make the results reliable and generalizable. The document then discusses some questions and concerns about survey length, question types, and methodology.
Practical and Actionable Threat Intelligence CollectionSeamus Tuohy
A great deal of the existing human rights reporting and analysis aggregate and strip away contextual information in order to produce “quantified knowledge” that is technically reliable and useful for governmental decision making. The results produced often end up too delayed, partial, distorted, and misleading to be used by local actors and human rights defenders to directly respond to the threats that they face. Those who could benefit most from the human rights knowledge being collected and shared in the digital world are those that existing repositories of information serve the least.
In this presentation I will provide concrete guidance on approaches for adopting data-rich, practical, and actionable threat information collection. In this content heavy 1.5 hour talk I will discuss a range of tools and techniques for seeking out sources of actionable information, distinguishing valuable information from useless but interesting information, and streamlining your information collection and analysis process to allow you to focus on your real work.
This talk WON’T be focused on collecting or sharing threat intelligence and/or human rights research aimed at evidence creation or changing the public dialogue. It WILL be focused on helping you identify, collect, and use publicly available sources of information to respond to your changing threat landscape.
This document discusses case based reasoning and its application in data mining and databases. Case based reasoning involves solving current problems by adapting solutions from similar past problems. The author defines case based reasoning and describes the typical four step structure of a case base database used in case based reasoning: 1) retrieval of similar past cases, 2) reuse of solutions from these similar cases, 3) revision of these solutions if needed, and 4) retention of the revised solutions as new cases. The article examines how case based reasoning, data mining techniques, and databases can be used together across various industries.
The document discusses how government agencies can use data analytics to address challenges and improve services. It provides examples of how the State of Indiana is using data analytics to combat the opioid epidemic, how the US Patent and Trademark Office made patent data more searchable, and how the Government Accountability Office tracks Medicare fraud. The document also discusses descriptive, diagnostic, predictive, and prescriptive analytics and how real-time and forensic analyses drive value. Overall, the document promotes how data analytics can help government agencies deliver better outcomes.
INSIDER'S PERSPECTIVE: Three Trends That Will Define the Next Horizon in Lega...LexisNexis
In a recent Information Today article, Sean Fitzpatrick of LexisNexis discusses trends that will define the future of legal research as we know it.
Humans create 2.5 quintillion bytes of data each day, and the cost of storing and maintaining each byte of data is declining. In fact, the growth of stored data is outpacing the ability of most people to manage it.
Powerful tools, such as natural language processing and machine learning, are helping professionals bridge the gap between information overload and the ability to harvest the power of Big Data.
Millennials now make up nearly one-third of the U.S. workforce and they are our most educated generation.
This document provides an overview of predictive analytics and its growing importance. It discusses how advances in technologies like cloud computing and the internet of things are enabling businesses to gather and analyze vast amounts of data. While descriptive and diagnostic analytics describe what happened in the past, predictive analytics uses statistical techniques to create models that forecast future outcomes. The document outlines several key drivers that are pushing predictive analytics towards mainstream adoption over the next few years, including easier-to-use tools, open source software, innovation from startups, and the availability of cloud-based solutions. It concludes that the combination of big data and predictive analytics will continue to accelerate innovation across industries.
This document discusses ethics in data warehousing and data mining. It notes that data mining can discover new patterns and relationships but also raises ethical issues when used to discriminate against groups for things like loans or special offers. The project manager is responsible for ensuring ethical use of data and establishing access controls and qualifications for users. Small data sets can also raise ethical concerns if users learn information they should not. The project manager must decide what public data is integrated and ensure end users, testing practices, and data mining applications comply with ethical standards and legal regulations.
Data Collection Tool Used For Information About IndividualsChristy Hunt
The document discusses surveys as a data collection tool used to gather information about individuals. Surveys can be conducted in various ways such as printed questionnaires, telephone interviews, mail, in-person interviews, online, etc. However, standardized procedures are used to ensure every participant is asked the same questions in the same way to make the results reliable and generalizable. The document then discusses some questions and concerns about survey length, question types, and methodology.
Practical and Actionable Threat Intelligence CollectionSeamus Tuohy
A great deal of the existing human rights reporting and analysis aggregate and strip away contextual information in order to produce “quantified knowledge” that is technically reliable and useful for governmental decision making. The results produced often end up too delayed, partial, distorted, and misleading to be used by local actors and human rights defenders to directly respond to the threats that they face. Those who could benefit most from the human rights knowledge being collected and shared in the digital world are those that existing repositories of information serve the least.
In this presentation I will provide concrete guidance on approaches for adopting data-rich, practical, and actionable threat information collection. In this content heavy 1.5 hour talk I will discuss a range of tools and techniques for seeking out sources of actionable information, distinguishing valuable information from useless but interesting information, and streamlining your information collection and analysis process to allow you to focus on your real work.
This talk WON’T be focused on collecting or sharing threat intelligence and/or human rights research aimed at evidence creation or changing the public dialogue. It WILL be focused on helping you identify, collect, and use publicly available sources of information to respond to your changing threat landscape.
This document discusses case based reasoning and its application in data mining and databases. Case based reasoning involves solving current problems by adapting solutions from similar past problems. The author defines case based reasoning and describes the typical four step structure of a case base database used in case based reasoning: 1) retrieval of similar past cases, 2) reuse of solutions from these similar cases, 3) revision of these solutions if needed, and 4) retention of the revised solutions as new cases. The article examines how case based reasoning, data mining techniques, and databases can be used together across various industries.
The document discusses how government agencies can use data analytics to address challenges and improve services. It provides examples of how the State of Indiana is using data analytics to combat the opioid epidemic, how the US Patent and Trademark Office made patent data more searchable, and how the Government Accountability Office tracks Medicare fraud. The document also discusses descriptive, diagnostic, predictive, and prescriptive analytics and how real-time and forensic analyses drive value. Overall, the document promotes how data analytics can help government agencies deliver better outcomes.
INSIDER'S PERSPECTIVE: Three Trends That Will Define the Next Horizon in Lega...LexisNexis
In a recent Information Today article, Sean Fitzpatrick of LexisNexis discusses trends that will define the future of legal research as we know it.
Humans create 2.5 quintillion bytes of data each day, and the cost of storing and maintaining each byte of data is declining. In fact, the growth of stored data is outpacing the ability of most people to manage it.
Powerful tools, such as natural language processing and machine learning, are helping professionals bridge the gap between information overload and the ability to harvest the power of Big Data.
Millennials now make up nearly one-third of the U.S. workforce and they are our most educated generation.
This document provides an overview of predictive analytics and its growing importance. It discusses how advances in technologies like cloud computing and the internet of things are enabling businesses to gather and analyze vast amounts of data. While descriptive and diagnostic analytics describe what happened in the past, predictive analytics uses statistical techniques to create models that forecast future outcomes. The document outlines several key drivers that are pushing predictive analytics towards mainstream adoption over the next few years, including easier-to-use tools, open source software, innovation from startups, and the availability of cloud-based solutions. It concludes that the combination of big data and predictive analytics will continue to accelerate innovation across industries.
This document summarizes four knowledge management processes used by Defence Research & Development Canada (DRDC): monitoring the environment, producing intelligence, mobilizing knowledge, and integration. It describes DRDC's environmental monitoring process which involves acquiring external data through 10 pathways, including monitoring cyberspace, media, research, literature, conferences, communities of practice, soliciting practitioners, reviewing experiences, individual discovery, and receiving unsolicited information. Each pathway requires different support services to filter and analyze the acquired information and detect patterns of interest.
Human Trafficking-A Perspective from Computer Science and Organizational Lead...Turner Sparks
This document discusses using an interdisciplinary approach to address the issue of human trafficking. It focuses on how perspectives from computer science and organizational leadership can help law enforcement utilize surveillance and tracking software. The author conducted a literature review and found that better software for facial recognition and human tracking could be developed. However, current technology works best in controlled environments and laws need to regulate privacy issues related to increased video surveillance. Overall, the document argues that further advancing surveillance technology and providing more training to law enforcement on human trafficking should be priorities to help solve this problem.
Running head CRIME ANALYSIS TECHNOLOGY .docxhealdkathaleen
This document discusses crime analysis technology and its role in fighting crimes. It provides background on crime analysis and how the use of technology has helped law enforcement more effectively solve and prevent crimes. Specifically, it discusses how predictive policing software using data from past crimes can help predict future severe crimes in an area. It also notes that 9 out of 10 law enforcement officials believe technology has helped agencies solve crimes by identifying links and trends. Additionally, the document proposes implementing crime analysis technology initiatives at the FBI to strengthen its ability to deal with terrorism and threats.
Running head CRIME ANALYSIS TECHNOLOGY .docxtodd271
Running head: CRIME ANALYSIS TECHNOLOGY 1
CRIME ANALYSIS TECHNOLOGY 9
Crime Analysis Technology
Student’s Name
Institutional Affiliation
Crime Analysis Technology
Peer-Reviewed Article Analysis
Technology has evolved over the years in various sectors, with new technological innovations being developed. One of the areas that has witnessed great applications of technological evolution is in the detection and prevention of crime. This article will analyze the various technologies that are used to prevent and detect crime.
Byrne and Marx (2011) in their article reviews the topic in detail and gives insight in the role of technology in combating crime.
The key data that will be used in this research is secondary data from various peer-reviewed sources that review the topic of Crime Analysis Technology from various perspectives. Byrne and Marx (2011) presents various data on crime and the use of Information Technology in crime detection and prevention. For instance, it highlights that the percentage of schools in the United States that deploy metal detectors is approximately 2%. The article also approximates that as of 2006, one million CCTV cameras had been deployed in the United States, although the article does not provide current estimates on the same.
The article plays a great role in my final research. It gives a highlight of the various technological applications for crime prevention and detection. This can provide a background for further research, especially the technological innovations that are currently being developed. The article also presents figures about various elements of technology in crime prevention and detection such as the number of CCTV cameras, the crime rates such as the registered sex offenders, among others. Projections can therefore be made to the future.
The article mentions several significant facts. First, it classifies technological innovations in criminal justice as hard technology versus soft technology. Hard technology innovations include hardware and materials while soft technology innovations include information systems and computer software. Examples of hard technology is the CCTV cameras, metal detectors, and security systems at homes and schools. Examples of soft technology include predictive policing technology, crime analysis techniques, software, and data sharing techniques, among others. Both of the two categories of technological innovations are important in criminal justice. Another fact is the new technology of policing. The article identifies hard policing technological tools such as non-lethal weaponry and technologies for officer safety. It highlights soft policing technologies such as data-driven policies in policing and information sharing. Another important fact that the article mentions is the issues that should be con.
Blockchain for Health Research - HHS PCOR ManionSean Manion PhD
Blockchain for Health Research presentation by Sean Manion on 16 Dec 2019 for the U.S. Dept of Health and Human Services Asst Secretary for Programs & Evaluation, Patient Centered Outcomes Research Trust Fund Webinar
Computer Forensics
Discussion 1
"Forensics Certifications" Please respond to the following:
· Determine whether or not you believe certifications in systems forensics are necessary and explain why you believe this to be the case. Compare and contrast certifications and on-the-job training and identify which you believe is more useful for a system forensics professional. Provide a rationale with your response.
· Suppose you are the hiring manager looking to hire a new system forensics specialist. Specify at least five (5) credentials you would expect an ample candidate to possess. Determine which of these credentials you believe to be the most important and provide a reason for your decision.
Discussion 2
"System Forensics Organizations" Please respond to the following:
· Use the Internet or the Library to research and select one (1) reputable system forensics organization. Provide a brief overview of the organization you chose, including what it provides for its members, and how one can join the organization. Indicate why, in your opinion, this particular organization would be the best choice for a system forensics professional to join and why you believe this way.
· Examine what you believe to be the most important reason for a systems forensic professional to be a member of a forensics organization and how this could further one’s career in the industry.
Cyber Security
Discussion 1
"Leading Through Effective Strategic Management" Please respond to the following:
· Propose three ways to ensure that cooperation occurs across security functions when developing a strategic plan. Select what you believe is the most effective way to promote collaboration and explain why.
· Explain what may happen if working cultures are overlooked when developing a strategy. Recommend one way to prevent working cultures from being overlooked.
Discussion 2
"Installing Security with System and Application Development" Please respond to the following:
· Provide three examples that demonstrate how security can be instilled within the Systems Development Life Cycle (SDLC). Provide two examples on what users may experience with software products if they are released with minimal security planning.
· Suggest three ways that application security can be monitored and evaluated for effectiveness. Choose what you believe to be the most effective way and discuss why.
Computer Security
Discussion 1
"Current Events and Future Trends" Please respond to the following:
· How can we create a national security culture where all are more cognizant of security threats and involved to help prevent potential incidents? How do we balance the need for this security culture with the rights guaranteed to us by our Bill of Rights?
Research Topics (Choose 1 Topic)
Terrorism
· Terrorism remains one of the major concerns in the wake of the 9-11 events. Research into terrorism as it pertains to homeland security is conducted by corporations like the RAND Corporation, which is.
The document discusses several key topics related to data privacy in the digital economy:
- Challenges of safeguarding privacy rights with the rise of technology and data collection.
- Assessing privacy maturity based on generally accepted privacy principles.
- Implementing privacy enhancing technologies and practices like privacy by design.
- Understanding consumer concerns about privacy and gaining their consent for data use.
During the research process, it was discovered that law enforcement has implemented some tracking surveillance software but they were not reliable enough for real world use. Developing better video sensors and tracking algorithms through an interdisciplinary approach with computer science and organizational leadership could help create more effective surveillance systems to track human trafficking suspects and victims. Future work should focus on overcoming obstacles like sensors not differentiating objects in varied lighting and software not handling large amounts of video data.
Data for Impact Fellowship - SocialCops CareersSocialCops
The Data for Impact Fellowship is a unique opportunity where fellows partner with leaders in government, bilateral organizations, foundations and nonprofits — ranging from Ministers, CEOs and District Collectors — to implement a scalable data intelligence solution. The Fellowship seeks to bring together young, enterprising future leaders with experienced leaders in the development sphere to use the power of data to solve some of India's most critical problems.
For more details about the Fellowship and to get started on your application, visit http://soco.ps/2BHK6Ba!
Data mining and privacy preserving in data miningNeeda Multani
Data mining involves analyzing data from different perspectives to discover useful patterns and relationships not previously known. It can be used to increase profits, reduce costs, and more. Privacy preservation in data mining aims to protect individual privacy while still providing valid mining results, using techniques like cryptographic protocols to run algorithms on joined databases without revealing unnecessary information. Data mining has various applications like fraud detection, credit risk assessment, customer profiling, and more.
The document provides an overview of an event on emerging trends in data science given by Dr. Joanne Luciano. It discusses the data science workflow and various processes involved. Some key trends highlighted include increased use of AI and machine learning in data management and reporting, growth of natural language processing, advances in deep learning, emphasis on data privacy and ethics. The document also promotes the new minor in data science offered at University of the Virgin Islands, covering required courses and examples of course sequences for different disciplines.
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
The document provides background on a research project investigating the data breach at the U.S. Office of Personnel Management in 2015. The project aims to interview OPM executives to understand the breach and analyze the relationship between cyber attacks and upgrades to the agency's technology. The researcher plans to enter the OPM for 3 weeks to conduct interviews and examine how often software/hardware patches are implemented each year.
Guidance for Incorporating Big Data into Humanitarian Operations - 2015 - web...Katie Whipkey
This document provides guidance on incorporating big data into humanitarian operations. It defines big data as large, complex datasets that exceed traditional data analysis capabilities. Big data is characterized by its volume, variety, velocity and value. The document outlines the history of big data and provides an overview of different big data types. It also discusses benefits and challenges, as well as important considerations around policy, acquisition, use, and timeline for humanitarian organizations looking to utilize big data.
TrialIO aims to empower patients and researchers by providing better access and analysis of clinical trial data. It reimagines the data from ClinicalTrials.gov as a spreadsheet in the cloud, allowing users to more easily identify trends in clinical trial activity over time for specific diseases, locations, investigators, and sponsors. This could help improve patient-researcher matching and support various stakeholders in planning and conducting clinical trials. The tool is envisioned as both a web application and syndicated web service to promote wider dissemination and use of clinical trial data.
Required TextbooksJennings, M. (2016). Business Its Legal,.docxkellet1
Required Textbooks:
Jennings, M. (2016). Business: Its Legal, Ethical, and Global Environment,
11thed. (Standard Volume).
Southwestern: Cengage Learning.
Course name:
Legal, Ethical, and Global Environment
David, Fred R. & David, Forest R. (2017).
Strategic Management
:
A competitive advantage approach
, 16th. Pearson.
Course name: Strategic Decision Making
Pinto, J. K. (2019). Project management: Achieving competitive advantage (5th ed.). Boston, MA Pearson.
Course name: Planning the Project
It is now time for students to reflect on the knowledge obtained in their course(s) and determine the effectiveness of incorporating real-world experience into our academic curriculum.
Students should;
Be able to apply knowledge and theory gained in their courses of study within current workplace or in their future employment.
Be able demonstrate the application of theory to workplace in written form.
Be able to identify the benefits of incorporating real-world experience into an academic program.
Write 600 words text each course 200 words.
.
Required to submit a 1000-word (4 full pages) paper. Read the descri.docxkellet1
Required to submit a 1000-word (4 full pages) paper. Read the description below. It's not an essay so, work cited is not needed. Plagiarism will not be accepted.
Cultural Reflection: The student will discuss how his/her culture has shaped his/her identity and world view. Cultural Comparison: The student will compare his or her culture to a different culture.
Cultural Accommodation: The student will consider how an individual can adjust his/her actions to successfully interact with someone from another culture.
Civic Responsibility: The student will discuss his/her civic responsibilities as a member of a particular community. The student should also describe the degree to which he/she meets those responsibilities. What steps could be taken to improve civic engagement nationwide?
Culture and Civic Responsibility: What is the relationship between culture and civic responsibility. How can civic responsibility improve intercultural interactions?
Philosophical Engagement: Somewhere in the course of this paper, the student should incorporate significant references to at least two thinkers we’ve discussed this semester
.
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This document summarizes four knowledge management processes used by Defence Research & Development Canada (DRDC): monitoring the environment, producing intelligence, mobilizing knowledge, and integration. It describes DRDC's environmental monitoring process which involves acquiring external data through 10 pathways, including monitoring cyberspace, media, research, literature, conferences, communities of practice, soliciting practitioners, reviewing experiences, individual discovery, and receiving unsolicited information. Each pathway requires different support services to filter and analyze the acquired information and detect patterns of interest.
Human Trafficking-A Perspective from Computer Science and Organizational Lead...Turner Sparks
This document discusses using an interdisciplinary approach to address the issue of human trafficking. It focuses on how perspectives from computer science and organizational leadership can help law enforcement utilize surveillance and tracking software. The author conducted a literature review and found that better software for facial recognition and human tracking could be developed. However, current technology works best in controlled environments and laws need to regulate privacy issues related to increased video surveillance. Overall, the document argues that further advancing surveillance technology and providing more training to law enforcement on human trafficking should be priorities to help solve this problem.
Running head CRIME ANALYSIS TECHNOLOGY .docxhealdkathaleen
This document discusses crime analysis technology and its role in fighting crimes. It provides background on crime analysis and how the use of technology has helped law enforcement more effectively solve and prevent crimes. Specifically, it discusses how predictive policing software using data from past crimes can help predict future severe crimes in an area. It also notes that 9 out of 10 law enforcement officials believe technology has helped agencies solve crimes by identifying links and trends. Additionally, the document proposes implementing crime analysis technology initiatives at the FBI to strengthen its ability to deal with terrorism and threats.
Running head CRIME ANALYSIS TECHNOLOGY .docxtodd271
Running head: CRIME ANALYSIS TECHNOLOGY 1
CRIME ANALYSIS TECHNOLOGY 9
Crime Analysis Technology
Student’s Name
Institutional Affiliation
Crime Analysis Technology
Peer-Reviewed Article Analysis
Technology has evolved over the years in various sectors, with new technological innovations being developed. One of the areas that has witnessed great applications of technological evolution is in the detection and prevention of crime. This article will analyze the various technologies that are used to prevent and detect crime.
Byrne and Marx (2011) in their article reviews the topic in detail and gives insight in the role of technology in combating crime.
The key data that will be used in this research is secondary data from various peer-reviewed sources that review the topic of Crime Analysis Technology from various perspectives. Byrne and Marx (2011) presents various data on crime and the use of Information Technology in crime detection and prevention. For instance, it highlights that the percentage of schools in the United States that deploy metal detectors is approximately 2%. The article also approximates that as of 2006, one million CCTV cameras had been deployed in the United States, although the article does not provide current estimates on the same.
The article plays a great role in my final research. It gives a highlight of the various technological applications for crime prevention and detection. This can provide a background for further research, especially the technological innovations that are currently being developed. The article also presents figures about various elements of technology in crime prevention and detection such as the number of CCTV cameras, the crime rates such as the registered sex offenders, among others. Projections can therefore be made to the future.
The article mentions several significant facts. First, it classifies technological innovations in criminal justice as hard technology versus soft technology. Hard technology innovations include hardware and materials while soft technology innovations include information systems and computer software. Examples of hard technology is the CCTV cameras, metal detectors, and security systems at homes and schools. Examples of soft technology include predictive policing technology, crime analysis techniques, software, and data sharing techniques, among others. Both of the two categories of technological innovations are important in criminal justice. Another fact is the new technology of policing. The article identifies hard policing technological tools such as non-lethal weaponry and technologies for officer safety. It highlights soft policing technologies such as data-driven policies in policing and information sharing. Another important fact that the article mentions is the issues that should be con.
Blockchain for Health Research - HHS PCOR ManionSean Manion PhD
Blockchain for Health Research presentation by Sean Manion on 16 Dec 2019 for the U.S. Dept of Health and Human Services Asst Secretary for Programs & Evaluation, Patient Centered Outcomes Research Trust Fund Webinar
Computer Forensics
Discussion 1
"Forensics Certifications" Please respond to the following:
· Determine whether or not you believe certifications in systems forensics are necessary and explain why you believe this to be the case. Compare and contrast certifications and on-the-job training and identify which you believe is more useful for a system forensics professional. Provide a rationale with your response.
· Suppose you are the hiring manager looking to hire a new system forensics specialist. Specify at least five (5) credentials you would expect an ample candidate to possess. Determine which of these credentials you believe to be the most important and provide a reason for your decision.
Discussion 2
"System Forensics Organizations" Please respond to the following:
· Use the Internet or the Library to research and select one (1) reputable system forensics organization. Provide a brief overview of the organization you chose, including what it provides for its members, and how one can join the organization. Indicate why, in your opinion, this particular organization would be the best choice for a system forensics professional to join and why you believe this way.
· Examine what you believe to be the most important reason for a systems forensic professional to be a member of a forensics organization and how this could further one’s career in the industry.
Cyber Security
Discussion 1
"Leading Through Effective Strategic Management" Please respond to the following:
· Propose three ways to ensure that cooperation occurs across security functions when developing a strategic plan. Select what you believe is the most effective way to promote collaboration and explain why.
· Explain what may happen if working cultures are overlooked when developing a strategy. Recommend one way to prevent working cultures from being overlooked.
Discussion 2
"Installing Security with System and Application Development" Please respond to the following:
· Provide three examples that demonstrate how security can be instilled within the Systems Development Life Cycle (SDLC). Provide two examples on what users may experience with software products if they are released with minimal security planning.
· Suggest three ways that application security can be monitored and evaluated for effectiveness. Choose what you believe to be the most effective way and discuss why.
Computer Security
Discussion 1
"Current Events and Future Trends" Please respond to the following:
· How can we create a national security culture where all are more cognizant of security threats and involved to help prevent potential incidents? How do we balance the need for this security culture with the rights guaranteed to us by our Bill of Rights?
Research Topics (Choose 1 Topic)
Terrorism
· Terrorism remains one of the major concerns in the wake of the 9-11 events. Research into terrorism as it pertains to homeland security is conducted by corporations like the RAND Corporation, which is.
The document discusses several key topics related to data privacy in the digital economy:
- Challenges of safeguarding privacy rights with the rise of technology and data collection.
- Assessing privacy maturity based on generally accepted privacy principles.
- Implementing privacy enhancing technologies and practices like privacy by design.
- Understanding consumer concerns about privacy and gaining their consent for data use.
During the research process, it was discovered that law enforcement has implemented some tracking surveillance software but they were not reliable enough for real world use. Developing better video sensors and tracking algorithms through an interdisciplinary approach with computer science and organizational leadership could help create more effective surveillance systems to track human trafficking suspects and victims. Future work should focus on overcoming obstacles like sensors not differentiating objects in varied lighting and software not handling large amounts of video data.
Data for Impact Fellowship - SocialCops CareersSocialCops
The Data for Impact Fellowship is a unique opportunity where fellows partner with leaders in government, bilateral organizations, foundations and nonprofits — ranging from Ministers, CEOs and District Collectors — to implement a scalable data intelligence solution. The Fellowship seeks to bring together young, enterprising future leaders with experienced leaders in the development sphere to use the power of data to solve some of India's most critical problems.
For more details about the Fellowship and to get started on your application, visit http://soco.ps/2BHK6Ba!
Data mining and privacy preserving in data miningNeeda Multani
Data mining involves analyzing data from different perspectives to discover useful patterns and relationships not previously known. It can be used to increase profits, reduce costs, and more. Privacy preservation in data mining aims to protect individual privacy while still providing valid mining results, using techniques like cryptographic protocols to run algorithms on joined databases without revealing unnecessary information. Data mining has various applications like fraud detection, credit risk assessment, customer profiling, and more.
The document provides an overview of an event on emerging trends in data science given by Dr. Joanne Luciano. It discusses the data science workflow and various processes involved. Some key trends highlighted include increased use of AI and machine learning in data management and reporting, growth of natural language processing, advances in deep learning, emphasis on data privacy and ethics. The document also promotes the new minor in data science offered at University of the Virgin Islands, covering required courses and examples of course sequences for different disciplines.
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
The document provides background on a research project investigating the data breach at the U.S. Office of Personnel Management in 2015. The project aims to interview OPM executives to understand the breach and analyze the relationship between cyber attacks and upgrades to the agency's technology. The researcher plans to enter the OPM for 3 weeks to conduct interviews and examine how often software/hardware patches are implemented each year.
Guidance for Incorporating Big Data into Humanitarian Operations - 2015 - web...Katie Whipkey
This document provides guidance on incorporating big data into humanitarian operations. It defines big data as large, complex datasets that exceed traditional data analysis capabilities. Big data is characterized by its volume, variety, velocity and value. The document outlines the history of big data and provides an overview of different big data types. It also discusses benefits and challenges, as well as important considerations around policy, acquisition, use, and timeline for humanitarian organizations looking to utilize big data.
TrialIO aims to empower patients and researchers by providing better access and analysis of clinical trial data. It reimagines the data from ClinicalTrials.gov as a spreadsheet in the cloud, allowing users to more easily identify trends in clinical trial activity over time for specific diseases, locations, investigators, and sponsors. This could help improve patient-researcher matching and support various stakeholders in planning and conducting clinical trials. The tool is envisioned as both a web application and syndicated web service to promote wider dissemination and use of clinical trial data.
Required TextbooksJennings, M. (2016). Business Its Legal,.docxkellet1
Required Textbooks:
Jennings, M. (2016). Business: Its Legal, Ethical, and Global Environment,
11thed. (Standard Volume).
Southwestern: Cengage Learning.
Course name:
Legal, Ethical, and Global Environment
David, Fred R. & David, Forest R. (2017).
Strategic Management
:
A competitive advantage approach
, 16th. Pearson.
Course name: Strategic Decision Making
Pinto, J. K. (2019). Project management: Achieving competitive advantage (5th ed.). Boston, MA Pearson.
Course name: Planning the Project
It is now time for students to reflect on the knowledge obtained in their course(s) and determine the effectiveness of incorporating real-world experience into our academic curriculum.
Students should;
Be able to apply knowledge and theory gained in their courses of study within current workplace or in their future employment.
Be able demonstrate the application of theory to workplace in written form.
Be able to identify the benefits of incorporating real-world experience into an academic program.
Write 600 words text each course 200 words.
.
Required to submit a 1000-word (4 full pages) paper. Read the descri.docxkellet1
Required to submit a 1000-word (4 full pages) paper. Read the description below. It's not an essay so, work cited is not needed. Plagiarism will not be accepted.
Cultural Reflection: The student will discuss how his/her culture has shaped his/her identity and world view. Cultural Comparison: The student will compare his or her culture to a different culture.
Cultural Accommodation: The student will consider how an individual can adjust his/her actions to successfully interact with someone from another culture.
Civic Responsibility: The student will discuss his/her civic responsibilities as a member of a particular community. The student should also describe the degree to which he/she meets those responsibilities. What steps could be taken to improve civic engagement nationwide?
Culture and Civic Responsibility: What is the relationship between culture and civic responsibility. How can civic responsibility improve intercultural interactions?
Philosophical Engagement: Somewhere in the course of this paper, the student should incorporate significant references to at least two thinkers we’ve discussed this semester
.
Required to read one current scholarly article on the topic of art a.docxkellet1
Required to read one current scholarly article on the topic of art and global diversity, and write a 500-word critical response. Should be prepared identify, communicate and analyze the following: (1) identify the author’s key argument and approach, and analyze influences and biases; (2) support their claims with informed, historical/critical examples and ideas taken from the article itself, and draw on concepts, terms and approaches learned in class. Should not generalize, use subjective descriptions or make general, unsupported claims. The reading is Derek Conrad Murray, “Mickalene Thomas: Afro-Kitsch and the Queering of Blackness.”
.
Required to do a 10-15 minute PowerPoint presentation on a case stud.docxkellet1
Required to do a 10-15 minute PowerPoint presentation on a case study based on one of the disorders discussed in the textbook.
The task is to present a comprehensive analysis of the case which includes identifying information, symptoms and problems, hypotheses regarding the presenting problem, a multi-axial diagnosis (along with disorders that were ruled-out), the type of treatment (therapy and/or medication) the client should receive, and relevant cultural considerations. In addition, the presenters should include a slide that lists additional questions that would help to treat the client and/or that would provide clarity regarding the presenting problem.
Students will be graded on correct diagnosis(es) for each axis, including principle, deferred and/or differential, whether each diagnosis or lack of a diagnosis was clearly justified based on clinical criteria, and if important features of the client’s symptoms/behaviors were clearly identified and insightfully analyzed. The presentation will also be graded for content, quality of presentation, presentation skills (e.g., level of comfort, knowledge of subject, etc.), and number of errors in mechanics, usage, grammar, and spelling. Breakdown of points as follows:
40 Points – Analysis of case
30 Points – Clarity, organization, and comprehensiveness
30 Points – Grammar, punctuation, and spelling
Differential diagnosis
refers to all of the diagnostic categories that you seriously considered during the diagnostic process. Because the symptoms present in the case study suggest the possibility of several disorders, a thorough discussion of disorders that you excluded is warranted. In other words, you should discuss why you assigned the diagnoses that you did and why you ruled out others.
Multi-axial Diagnosis Format
You can have multiple diagnoses on any axis. It is also possible that there is no diagnosis on an axis. List every diagnosis for which the diagnostic criteria are met. When no diagnosis exists for a particular axis, “No Diagnosis” is entered on the line. The first diagnosis listed on Axis I is assumed to be the principal diagnosis unless otherwise specified. If the principal diagnosis is a Personality Disorder or Mental Retardation, it should be listed on Axis II, labeled as the “Principal Diagnosis” in parentheses.
Axis I:
Includes all of the disorders we will cover in class, with the exception of Personality Disorders and Mental Retardation.
Axis II:
Includes only Personality Disorders and Mental Retardation
Axis III:
Includes general medical conditions that are relevant to Axis I and Axis II diagnoses.
Axis IV:
Includes a listing of any relevant psychosocial and environmental problems or stressors.
Axis V:
Includes a numerical rating of current functioning, and occasionally highest functioning over the past year, on a scale of 0 to 100. (Use chart below)
Use this sample as a reference for your presentation:
Axis I:
Major Depressive Disorder (Principle Diagn.
Required TextThe World’s Religions, By Huston Smith, HarperSan F.docxkellet1
Required Text:
The World’s Religions, By Huston Smith, Harper/San Francisco, 1991
ISBN:0-062-50811-3
GOALS:
The purpose of the course is introducing the student to the world’s major
religions: Christianity, Judaism, Islam, Buddhism, Taoism, Confucianism and the
“primal religions”.
Write a 3-5-page review of each to the following two movies: Little Buddha,
Gandhi. Please do not just describe the plot of the movie. Try to write about
the religious ideas that you have been learning about from the Smith
textbook. You should be able to find these videos at a video store such as
Hollywood Video.
.
Required TextMalec, T. & Newman, M. (2013). Research methods Bu.docxkellet1
This document discusses research methods and provides an example of formatting a research proposal. It includes sections on writing a research proposal, formatting the proposal with headings in APA style, and content that should be included in the introduction, literature review, and other sections. Key points covered include outlining the standard sections and order of a research proposal, using different heading levels, and providing guidance on the level of detail and analysis required for the literature review.
Required Textbook Managing Criminal Justice Organizations An I.docxkellet1
Required Textbook: Managing Criminal Justice Organizations: An Introduction to Theory and Practice, by Richard R.E. Kania and Richards P. Davis.
Chapter 12 Questions to be answered in APA format. No plagiarism.
1. Name and describe three patterns for change.
2. Identify the seven most common patterns of ethical failures occurring across the criminal justice system.
3. Discuss the 12 principles for dealing with the mass communications media that a criminal justice manager should consider.
4. Discuss what future challenges you predict for criminal justice.
.
REQUIRED TEXTBOOK Human Relations Job-Oriented Interpersonal Skill.docxkellet1
REQUIRED TEXTBOOK: Human Relations: Job-Oriented Interpersonal Skills, 11/en, by Andrew DuBrin (Be sure to get the eleventh edition!).
ISBN-10: 0135109418
ISBN-13: 9780135109410
1.
Mention the four key factor of emotional intelligence.
2.
Mention steps in the communications process.
3.
Mention
6 Positive Interpersonal Skills While Using Cell Phones.
4.
Mention
5 advantages and 5 disadvantages of teams and teamwork.
.
Required Textbook Hagan, Frank E., Research Methods in Criminal.docxkellet1
Required Textbook: Hagan, Frank E., Research Methods in Criminal Justice and Criminology, Pearson Education,Inc., 2014. ISBN: 978-0-13-300861-6.
Review Questions
1. What is the UCR? What are its major components? What are the major components of the crime index? The calculation of crime rate? What have been some major identified shortcomings of the UCR?
2. Given the identified shortcomings of the UCR, read and then discuss how features of the redesigned UCR may eliminate some of these shortcomings.
3. Discuss the National Incident-Based Reporting System. What are some of its principal features as well as advantages over the traditional UCR?
4. What are some possible explanations for the crime dip of the 1990s?
5. Discuss the various types of sampling and when it would be most appropriate to use each one.
6. For what is weighting used in disproportionate stratified sampling, and why would samples be disproportionately drawn in the first place?
Use APA Formatting
No Plagiarism
.
Required Text The World’s Religions, By Huston Smith, HarperSa.docxkellet1
Required Text:
The World’s Religions, By Huston Smith, Harper/San Francisco, 1991
ISBN:0-062-50811-3
GOALS:
The purpose of the course is introducing the student to the world’s major religions: Christianity, Judaism, Islam, Buddhism, Taoism, Confucianism and the “primal religions”.
Read the course textbook and write a 3-5 page typewritten summary of the important points from each chapter.
.
Required ResourcesTextKorgen, K. O., & Atkinson M. P. (201.docxkellet1
Families have changed significantly over time in response to broader social and economic changes. Early families emphasized cooperation and alliance building between kin groups. With agriculture, marriage became more strategic and concerned with controlling resources and status. In colonial America, families were economically self-sufficient and Calvinist values emphasized the nuclear family. The rise of slavery disrupted African American families by allowing the separation of family members. Industrialization separated home and work life, and the middle class idealized the male breadwinner nuclear family model in the postwar period. However, families have always been diverse in practice.
Required Resources
Text
Read Commonsense Talent Management:
· Chapter 10: Improving the World through Strategic HR 349
Articles
Gould, W. I. (2010). Labor law beyond U.S. borders: does what happens outside of America stay outside of America?Stanford Law & Policy Review, (3), 401. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=edsgao&AN=edsgcl.237533046&site=eds-live
Kuddo, A. (2009, November 1). Labor laws in Eastern European and Central Asian countries: minimum norms and practices (Links to an external site.). Worldbank.org. Retrieved October 8, 2015. From-http://siteresources.worldbank.org/SOCIALPROTECTION/Resources/SP-Discussion-papers/Labor-Market-DP/0920.pdf
Discussion 1
BFOQ
Research the term BFOQ. Explain its importance and relevance to HRM. How might not appropriately incorporating well defined BFOQs lead to difficulties for the organization? How would the concept of BFOQ be linked to “disparate treatment” and/or “disparate impact” in respect to staffing? What is the link between the ADA (1990) and BFOQs? Present your views in 200 words or more in your discussion post.
Discussion 2
Foreign Restrictions on Termination
Research the topic of restrictions on termination of employment in European countries. Assess the different requirements and consider risks, operational requirements for MNCs, modified HRM policies, and any other conditions or restrictions facing a firm operating in such environments. Present your views in 200 words or more in your discussion post.
Week 6 - Final Project
Mark as done
Final Project
You work for a HR consulting company and an organization (the same company you have been writing about during this course) has hired your firm to conduct an HRM analysis and make recommendations to better align HR practices to the key business initiatives of the company. In order to accomplish the goal:
· Analyze the organization and develop a set of HRM practices that help align HR practices to the firm’s strategy. (Keep in mind the firm’s overall strategy in regards to Porter and Snow and White’s theories) Develop a 3200-3500 word research paper (not including the title and reference pages). Your paper should also:
· Identify the firm’s history, strategy, market position, and specific area of alignment.
· Provide job pricing and compensation package for 3-4 key positions in the organization.
· Describe and analyze the current and targeted HR work processes as well as the respective knowledge, skills, and abilities (KSAs) required to achieve the organization’s objectives.
· Incorporate a discussion of relevant technology considerations to achieve work output in the context of the organization’s goals.
· Provide a discussion of the labor market and the appropriate labor law context. Identification of companies that are preparing to address any legal or regulatory changes..
· Prescribe a set of HRM recommendations, specifically tailored for the selected firm. Insert a table with deliverables, acc.
Required ResourcesTextHansen-Turton, T. & Mortell, M . (2014)..docxkellet1
Required Resources
Text
Hansen-Turton, T. & Mortell, M . (2014). Making strategy count in health and human services sector. New York, NY: Spring Publishing Company.
· Chapter 3: Forces Shaping the Human Services Sector in the Early 21st Century
· Chapter 7: Using Data to Drive Change and Achieve Impact
Recommended Resources
Websites
Behavioral health. (Links to an external site.)Links to an external site. (2014). Retrieved from http://www.healthit.gov/policy-researchers-implementers/behavioral-health
· This webpage and its associated links addresses the significance of information technology and how it is being used to address outcomes related to behavioral health, and is a recommended resource for this week’s second discussion forum.
HHS A to Z index. (Links to an external site.)Links to an external site. (2014). Retrieved from http://www.hhs.gov/az
· This index identifies potential topic areas/issues to address and may be used by students in the completion of the written assignment.
· Accessibility Statement (Links to an external site.)Links to an external site.
· Privacy Policy (Links to an external site.)Links to an external site.
Homeless management information system. (Links to an external site.)Links to an external site. (2014). Retrieved from https://www.hudexchange.info/programs/hmis/
· This HUD webpage and its associated links offers an example information systems use in the area of homelessness, and is a recommended resource for this week’s second discussion forum.
Information systems and data. (Links to an external site.)Links to an external site. (n.d.). Retrieved from https://www.childwelfare.gov/topics/management/info-systems/
· This webpage and its associated links discuss the use of information systems in the field of child welfare, and is a recommended resource for this week’s second discussion forum. This site is housed within the parent website, Children’s Bureau, where you can find additional resources that may be of interest to you.
Required Resourc
es
Text
Hansen
-
Turton, T. & Mortell, M . (2014).
Making strategy count in health and human services
sector
. New York, NY: Spring Publishing Company.
·
Chapter 3: Forces Shaping the Human Services Sector in the Early 21st Century
·
Chapter 7: Using Data to Drive Change and Achieve Impact
Recommended Resources
Websites
Behavioral health.
(Links to an external site.)Links to an external site.
(2014). Retrieved from
http://www.healthit.gov/policy
-
researchers
-
implementers/behavioral
-
health
·
This webpage and its associated links addresses the significance of i
nformation
technology and how it is being used to address outcomes related to behavioral health, and
is a recommended resource for this week’s second discussion forum.
HHS A to Z index.
(Links to an externa
l site.)Links to an external site.
(2014). Retrieved from
http://www.hhs.gov/az
·
This index identifies potential topic areas/issues to address and may be used by students
in the c.
Required ResourcesTextCottrell, R. R., Girvan, J. T., McKenzie.docxkellet1
Required Resources
Text
Cottrell, R. R., Girvan, J. T., McKenzie, J. F., & Seabert, D. (2014). Principles and foundations of health promotion and education (6th ed.). Boston, MA: Pearson Education, Inc.
· Chapter 6: The Health Education Specialist: Roles, Responsibilities, Certifications, and and Advanced Study
· This chapter defines credentialing and describes the major responsibilities of a health education specialist.
· Chapter 7: The Settings for Health Education/Promotion
· This chapter describes the four main settings in which health educators tend to conduct health education programs.
Recommended Resources
Articles
Gonyea, J. (n.d.). Career planning step-by-step (Links to an external site.)Links to an external site.. Retrieved from http://career-advice.monster.com/job-search/getting-started/career-planning-step-by-step/article.aspx
· This article will help students understand the importance of developing a clear career plan.
National Commission for Health Education Credentialing, Inc. (2010). Areas of responsibilities, competencies, and sub-competencies for the health education specialists 2010 (Links to an external site.)Links to an external site.. Retrieved from http://www.nchec.org/assets/2251/areas_of_responsibilities_and_competencies.pdf
· The NCHEC lists the key areas of responsibility for all health educators in the United States.
Multimedia
Resources for developing an effective career plan [Webinar]. Retrieved from http://bpiedu.adobeconnect.com/p8bxdwvd704/
· In this recorded webinar students will be provided general advice from Ashford career specialists from different disciplines.
Website
National Commission for Health Education Credentialing, Inc (Links to an external site.)Links to an external site.
· Link to NCHEC homepage. By utilizing this website students will be able to see the requirements needed to sit for a CHES/MCHES examine and what some of the benefits of being a Certified Health Education Specialist may be in their career search.
Supplemental Materials
Roadmap to Success (Links to an external site.)Links to an external site.
· This resource offers guidance regarding additional ideas and steps students may want to include in their career plans.
Required Resources
Text
Cottrell, R. R., Girvan, J. T., McKenzie, J. F., & Seabert, D. (2014).
Principles and foundations
of health prom
otion and education
(6th ed.). Boston, MA: Pearson Education, Inc.
·
Chapter 6: The Health Education Specialist: Roles, Responsibilities, Certifications, and
and Advanced Study
o
This chapter defines credentialing and describes the major responsibilities of a
health education specialist.
·
Chapter 7: The Settings for Health Education/Promotion
o
This chapter describes the four main settings in which health educators tend to
conduct health education programs.
Recommended Resources
Articles
Gonyea, J. (n.d.).
Career planning step
-
by
-
step
(Links to an external site.)Links to an external
site.
. Retrieved fr.
Required ResourcesTextbook Chapter 15Minimum of 1 scholar.docxkellet1
Required Resources
Textbook: Chapter 15
Minimum of 1 scholarly source
For this assignment, choose a work of art that made an impression on you during this course. Then, address the following:
Include an image of or link to the work.
Identify the artist, the title, date completed, and the medium.
Explain how learning about the work will help you in your life and career. Consider the context in which the work was created and the meaning of the work.
Explain how one or more specific disciplines (literature, drama, philosophy, art, music) influenced you.
Examine the effect that you think this class could have on your career and personal life.
Writing Requirements (APA format)
Length: 2-2.5 pages (not including title page or references page)
1-inch margins
Double spaced
12-point Times New Roman font
Title page
References page (minimum of 1 scholarly source)
Due Date: By 11:59 p.m. MT on Saturday
.
Required ResourcesTextbook Chapters 4, 5Minimum of 1 scho.docxkellet1
The document provides instructions for an assignment requiring an initial post and follow up post discussing the pros and cons of vague language in the US Constitution. The initial post must cite at least one scholarly source in addition to assigned readings, and pick a vague portion of the Constitution to analyze regarding whether the vagueness has been problematic or helpful using historical examples. The follow up post must respond to a peer or instructor, further the discussion with more information and a citation, which can include assigned readings or an additional scholarly source. Both posts are due by Tuesday night and must follow APA format.
Required ResourcesTextBlanchard, P. N., & Thacker, J. W. (2013.docxkellet1
Required Resources
Text
Blanchard, P. N., & Thacker, J. W. (2013). Effective training: Systems, strategies, and practices (5th ed). Upper Saddle River, NJ: Pearson Education, Inc.
· Chapter 5: Training Design
· Chapter 6: Traditional Training Methods
· Chapter 7: Computer-Based Training Methods
Articles
Cherry, K. (2014). What is emotional intelligence? Definitions, history, and measures (Links to an external site.). About.com Psychology. Retrieved from http://psychology.about.com/od/personalitydevelopment/a/emotionalintell.htm
Clark, D. (2014). Why instructional system design and ADDIE? (Links to an external site.) Retrieved from http://www.nwlink.com/~donclark/hrd/sat1.html
Learning styles (Links to an external site.). (n.d.). Retrieved from http://www.mindtools.com/mnemlsty.html
DISCUSSION 1 WEEK 3 Replies Needed
Training Design
For this discussion, imagine that you are designing a 4-hour leadership development training session. Identify specific learning objectives for your training session. Conduct an Internet search to identify the types of games and business simulations that are available. Select one game or business simulation appropriate for your audience and learning objectives. Provide a brief description, detailed rationale, and thorough analysis of the game or business simulation as it pertains to your specific audience and learning objectives. Do not simply cut and paste from the Internet source.
Your initial post should be 250 to 300 words. Use this week’s lecture as a foundation for your initial post. In addition to the Blanchard and Thacker (2013) text, use at least one additional scholarly source to support your discussion.
Respond to two other posts regarding items you found to be compelling and enlightening. To help you with your reply, please consider the following questions:
· What did you learn from the posting?
· What additional questions do you have after reading the posting?
· What clarification do you need regarding the posting?
· What differences or similarities do you see between your initial discussion thread and your classmates' postings?
· Ask each other questions about why the specific game or simulation was selected.
· How does the chosen game or simulation apply to other situations?
· What are the differences or similarities in the specific game or simulation you selected compared to those identified by others?
· Analyze your classmates' chosen game or simulation. Do you agree or disagree with the choice? Why or why not? Provide examples where possible.
· What are the differences or similarities in the learning content objectives for your training session compared to those identified by others?
Your reply posts should be a minimum of 150-250 words each.
Reply to Paul Strange post
When design a leadership program there needs to be a competitive strategy, as this relates to the training of that organization you need to know what the organization needs first then you may be able to develop. The training proc.
Required ResourcesRequired TextRead from the course text, St.docxkellet1
Required Resources
Required Text
Read from the course text, Strategic management in healthcare organizations:
· Chapter 3: Strategic Thinking
· Chapter 4: External Environmental Analysis
Articles
1. Beaman, C. D. Jr. (2008). Caring for the uninsured. Healthcare Executive, 23(1), 46-47. Retrieved from the ProQuest database.
2. Galvin, R.S. (2008). Still in the game: Harnessing employer inventiveness in U.S. health care reform. The New England Journal of Medicine 359 (14), 1421-1423. Retrieved from the ProQuest database.
Multimedia
National Public Radio. (2013, April 29). Looking ahead: The future of health care policy (Links to an external site.)Links to an external site. [Podcast file]. Retrieved from http://www.npr.org/2013/04/29/179851904/looking-ahead-the-future- of-health-care-policy
Recommended Resource
Article
Hayes, H., Parchman, M., & Howard, R. (2011). A logic model framework for evaluation and planning in a primary care practice-based research network (PBRN) (Links to an external site.)Links to an external site.. The Journal of the American Board of Family Medicine, 24, 576-582. Retrieved from http://pbrn.ahrq.gov/pbrn-literature/logic-model-framework-evaluation-and-planning-primary-care-practice-based-research
Required Resources
Required Text
Read from the course text,
Strategic mana
gement in healthcare organizations
:
o
Chapter 3: Strategic Thinking
o
Chapter 4: External Environmental
Analysis
Articles
1.
Beaman, C. D. Jr. (2008). Caring for the uninsured.
Healthcare Executive, 23
(1), 46
-
47.
Retrieved from the ProQuest database.
2.
Galvin,
R.S. (2008). Still in the game: Harnessing employer inventiveness in U.S. health
care reform.
The New England Journal of Medicine 359
(14), 1421
-
1423. Retrieved from
the ProQuest database.
Multimedia
National Public Radio. (2013, April 29).
Looking ahead: The future of health care policy
(Links
to an external site.)Links to an external site.
[Podcast file].
Retrieved from
http://www.np
r.org/2013/04/29/179851904/looking
-
ahead
-
the
-
future
-
of
-
health
-
care
-
policy
Recommended Resource
Article
Hayes, H., Parchman, M., & Howard, R. (2011).
A logic model framework for evaluation and
planning in a primary care practice
-
based research network (PBRN)
(Links to an external
site.)Links to an external site.
.
The Jo
urnal of the American Board of Family Medicine, 24
, 576
-
582. Retrieved from http://pbrn.ahrq.gov/pbrn
-
literature/logic
-
model
-
framework
-
evaluation
-
and
-
planning
-
primary
-
care
-
practice
-
based
-
research
Required Resources
Required Text
Read from the course text, Strategic management in healthcare organizations:
o Chapter 3: Strategic Thinking
o Chapter 4: External Environmental Analysis
Articles
1. Beaman, C. D. Jr. (2008). Caring for the uninsured. Healthcare Executive, 23(1), 46-47.
Retrieved from the ProQuest database.
2. Galvin, R.S. (2008). Still in the game: Harnessin.
Required ResourcesRequired Text1. Cleverley, W. O., Song, P. H.docxkellet1
Required Resources
Required Text
1. Cleverley, W. O., Song, P. H., & Cleverley, J. O. (2011). Essentials of health care finance (7th ed). Sudbury, MA: Jones & Bartlett Learning.
· Chapter 19: Capital Project Analysis
· This chapter focuses on capital investment decision process including who should be involved, four stages of the decision process and information needed for decision making. The concepts of NPV, discount rate and weighted average cost of capital are examined.
· Chapter 20: Consolidations and Mergers
· This chapter discusses the basic theories in the field of consolidations, mergers and acquisitions. The common methods for valuation of a potential target firm are also explained.
· Chapter 21: Capital Formation
· This chapter focuses on the differences between debt and equity financing. The factors that influence the desirability of alternative sources of financing are also examined.
· Chapter 22: Working Capital and Cash Management
· This chapter focuses on the concepts of cash management and working capital. The activities covered in the cash budget affecting working capital are examined.
· Chapter 23: Developing the Cash Budget
· This chapter discusses the importance of cash budget and focuses on how to prepare a cash budget.
Recommended Resources
Article
1. Prepare a cash budget (Links to an external site.)Links to an external site.. Retrieved from http://www.va-interactive.com/inbusiness/editorial/finance/ibt/cash_bud.html
· This article uses examples to demonstrate the process of preparing a cash budget.
Textbook Powerpoint Presentations
1. Chapter 19 Capital Project Analysis
2. Chapter 20 Consolidations and Mergers
3. Chapter 21 Capital Formation
4. Chapter 22 Working Capital and Cash Management
5. Chapter 23 Developing the Cash Budget
6. HFMA PowerPoint Presentation Disbursements
7. HFMA PowerPoint Presentation Contract Management
.
Required ResourcesReadreview the following resources forTex.docxkellet1
This document provides instructions for a weekly assignment. Students are asked to analyze three sample slides based on what works well and needs improvement. They must write a two-paragraph analysis for each slide. Students are also asked to submit an outline rough draft for their PowerPoint presentation. The outline should include a title page, topic and thesis statement, three main points with two subpoints each, and a references page with at least four scholarly sources in APA format. The assignment is 3 pages not including the title page or references page and is due this week as part of an ongoing PowerPoint project.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
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This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
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14 LAW ENFORCEMENT TECHNOLOGY FEBRUARY
2018 www.officer.com
You
wouldn’t
want to
meet it in a
dark alley.
3. the results to anticipate, prevent and
respond more effectively to future crime.”
Using data to anticipate trends isn’t new.
In fact, many law enforcement agen-
cies, most notably in larger urban areas,
have been using predictive analytics and
accompanying software for close to a
decade—and the usage is slowly growing.
“I think more and more agencies are
looking at predictive analytics,” says Scott
Landau, senior business development
manager, public sector at Panasonic.
“There is a really big influence of wanting
to do smart policing and intelligence-led
policing and the move towards predictive
analytics supports that.”
Analyzing data allows agencies to
confirm what they already know and
discover new information. In many cases
it has become a critical tool in the abil-
ity to anticipate crime and has created
efficiencies. “Predictive policing never
tells you exactly what’s going to happen,
but it tells you there is a high likelihood
of an incident based on prior events,” says
Landau. “So what agencies are doing is
using predictive analytics and positioning
their resources, keeping the community
safer by having police in an area where
they are needed in a time when they are
needed.” In the age of technology and
information-sharing, fusion centers and
real-time crime centers have emerged
4. nationwide serving multi-agency policing
needs. These centers, in a simple sense,
can gather information from many data-
bases and analyze trends based on that
data. In fact, your department may be
one utilizing one such center right now.
But what about smaller agencies that
don’t have the resources to handle all of
the big data? Technology is emerging to
help even the smallest department man-
age data in a usable way.
Big data at the patrol level
Landau reports that today’s agencies are
looking for their technology to do more.
“Now that there is technology to cap-
ture fingerprints and facial recognition,
officers are asking, ‘How do we take that
to the edge?’ he says. “They can take an
image from a fixed camera and do facial
recognition in a real-time crime center
but they are asking for the ability to do
some of that information right at the
scene, at the field level.”
Smaller agencies need help turning
data into actionable intelligence. Landau
believes that as information-sharing
and partnerships continue to increase
in the future, solutions will emerge to
get big data at the patrol level. “Imagine
being in your patrol car, responding to a
domestic,” he says. “Now imagine hav-
ing the ability to use the technology on
the laptop or tablet, already available
in your car, to look across a half-dozen
5. databases to build a profile of the situ-
ation before you even get there.” In this
example, Landau notes that an officer
may be able to find a DMV photo, learn
if there are any registered firearms,
know if there is a restraining order or
look at mental health. In the time that
the officer is responding, they gathered
a profile in one place. Using data at the
patrol level may help officers better
anticipate a situation.
Technology is constantly changing
and improving, and predictive analytics
is just one way law enforcement can do
their jobs better with less resources.
LET_14-15_Panasonic0218_F.indd 14 1/24/18 7:09 AM
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without permission.
6. Reproduced with permission of the copyright owner. Further
reproduction prohibited without
permission.
Reproduced with permission of the copyright owner. Further
reproduction prohibited without
permission.
PERSPECTIVE
Ten Simple Rules for Creating a Good Data
Management Plan
William K. Michener*
College of University Libraries & Learning Sciences, University
of New Mexico, Albuquerque, New Mexico,
United States of America
* [email protected]
Introduction
Research papers and data products are key outcomes of the
science enterprise. Governmental,
nongovernmental, and private foundation sponsors of research
are increasingly recognizing
7. the value of research data. As a result, most funders now require
that sufficiently detailed data
management plans be submitted as part of a research proposal.
A data management plan
(DMP) is a document that describes how you will treat your
data during a project and what
happens with the data after the project ends. Such plans
typically cover all or portions of the
data life cycle—from data discovery, collection, and
organization (e.g., spreadsheets, data-
bases), through quality assurance/quality control,
documentation (e.g., data types, laboratory
methods) and use of the data, to data preservation and sharing
with others (e.g., data policies
and dissemination approaches). Fig 1 illustrates the relationship
between hypothetical research
and data life cycles and highlights the links to the rules
presented in this paper. The DMP
undergoes peer review and is used in part to evaluate a project’s
merit. Plans also document the
data management activities associated with funded projects and
may be revisited during per-
formance reviews.
Earlier articles in the Ten Simple Rules series of PLOS
Computational Biology provided
guidance on getting grants [1], writing research papers [2],
presenting research findings [3],
and caring for scientific data [4]. Here, I present ten simple
rules that can help guide the pro-
cess of creating an effective plan for managing research data—
the basis for the project’s find-
ings, research papers, and data products. I focus on the
principles and practices that will result
in a DMP that can be easily understood by others and put to use
by your research team. More-
8. over, following the ten simple rules will help ensure that your
data are safe and sharable and
that your project maximizes the funder’s return on investment.
Rule 1: Determine the Research Sponsor Requirements
Research communities typically develop their own standard
methods and approaches for man-
aging and disseminating data. Likewise, research sponsors often
have very specific DMP expec-
tations. For instance, the Wellcome Trust, the Gordon and Betty
Moore Foundation (GBMF),
the United States National Institutes of Health (NIH), and the
US National Science Foundation
(NSF) all fund computational biology research but differ
markedly in their DMP requirements.
The GBMF, for instance, requires that potential grantees
develop a comprehensive DMP in
conjunction with their program officer that answers dozens of
specific questions. In contrast,
NIH requirements are much less detailed and primarily ask that
potential grantees explain how
data will be shared or provide reasons as to why the data cannot
be shared. Furthermore, a
PLOS Computational Biology |
DOI:10.1371/journal.pcbi.1004525 October 22, 2015 1 / 9
OPEN ACCESS
Citation: Michener WK (2015) Ten Simple Rules for
Creating a Good Data Management Plan. PLoS
Comput Biol 11(10): e1004525. doi:10.1371/journal.
pcbi.1004525
Editor: Philip E. Bourne, National Institutes of Health,
UNITED STATES
10. guidance.htm).
Significant time and effort can be saved by first understanding
the requirements set forth by
the organization to which you are submitting a proposal.
Research sponsors normally provide
DMP requirements in either the public request for proposals
(RFP) or in an online grant pro-
posal guide. The DMPTool (https://dmptool.org/) and
DMPonline (https://dmponline.dcc.ac.
Fig 1. Relationship of the research life cycle (A) to the data life
cycle (B); note: highlighted circles
refer to the rules that are most closely linked to the steps of the
data life cycle. As part of the research
life cycle (A), many researchers (1) test ideas and hypotheses
by (2) acquiring data that are (3) incorporated
into various analyses and visualizations, leading to
interpretations that are then (4) published in the literature
and disseminated via other mechanisms (e.g., conference
presentations, blogs, tweets), and that often lead
back to (1) new ideas and hypotheses. During the data life cycle
(B), researchers typically (1) develop a plan
for how data will be managed during and after the project; (2)
discover and acquire existing data and (3)
collect and organize new data; (4) assure the quality of the data;
(5) describe the data (i.e., ascribe
metadata); (6) use the data in analyses, models, visualizations,
etc.; and (7) preserve and (8) share the data
with others (e.g., researchers, students, decision makers),
possibly leading to new ideas and hypotheses.
doi:10.1371/journal.pcbi.1004525.g001
PLOS Computational Biology |
DOI:10.1371/journal.pcbi.1004525 October 22, 2015 2 / 9
11. http://grants.nih.gov/grants/policy/data_sharing/data_sharing_g
uidance.htm
http://grants.nih.gov/grants/policy/data_sharing/data_sharing_g
uidance.htm
https://dmptool.org/
https://dmponline.dcc.ac.uk/
uk/) websites are also extremely valuable resources that provide
updated funding agency plan
requirements (for the US and United Kingdom, respectively) in
the form of templates that are
usually accompanied with annotated advice for filling in the
template. The DMPTool website
also includes numerous example plans that have been published
by DMPTool users. Such
examples provide an indication of the depth and breadth of
detail that are normally included
in a plan and often lead to new ideas that can be incorporated in
your plan.
Regardless of whether you have previously submitted proposals
to a particular funding pro-
gram, it is always important to check the latest RFP, as well as
the research sponsor’s website,
to verify whether requirements have recently changed and how.
Furthermore, don’t hesitate to
contact the responsible program officer(s) that are listed in a
specific solicitation to discuss
sponsor requirements or to address specific questions that arise
as you are creating a DMP for
your proposed project. Keep in mind that the principle objective
should be to create a plan that
will be useful for your project. Thus, good data management
plans can and often do contain
12. more information than is minimally required by the research
sponsor. Note, though, that some
sponsors constrain the length of DMPs (e.g., two-page limit); in
such cases, a synopsis of your
more comprehensive plan can be provided, and it may be
permissible to include an appendix,
supplementary file, or link.
Rule 2: Identify the Data to Be Collected
Every component of the DMP depends upon knowing how much
and what types of data will
be collected. Data volume is clearly important, as it normally
costs more in terms of infrastruc-
ture and personnel time to manage 10 terabytes of data than 10
megabytes. But, other charac-
teristics of the data also affect costs as well as metadata, data
quality assurance and
preservation strategies, and even data policies. A good plan will
include information that is suf-
ficient to understand the nature of the data that is collected,
including:
• Types. A good first step is to list the various types of data that
you expect to collect or create.
This may include text, spreadsheets, software and algorithms,
models, images and movies,
audio files, and patient records. Note that many research
sponsors define data broadly to
include physical collections, software and code, and curriculum
materials.
• Sources. Data may come from direct human observation,
laboratory and field instruments,
experiments, simulations, and compilations of data from other
studies. Reviewers and spon-
sors may be particularly interested in understanding if data are
13. proprietary, are being com-
piled from other studies, pertain to human subjects, or are
otherwise subject to restrictions in
their use or redistribution.
• Volume. Both the total volume of data and the total number of
files that are expected to be
collected can affect all other data management activities.
• Data and file formats. Technology changes and formats that
are acceptable today may soon
be obsolete. Good choices include those formats that are
nonproprietary, based upon open
standards, and widely adopted and preferred by the scientific
community (e.g., Comma Sepa-
rated Values [CSV] over Excel [.xls, xlsx]). Data are more
likely to be accessible for the long
term if they are uncompressed, unencrypted, and stored using
standard character encodings
such as UTF-16.
The precise types, sources, volume, and formats of data may not
be known beforehand,
depending on the nature and uniqueness of the research. In such
case, the solution is to itera-
tively update the plan (see Rule 9).
PLOS Computational Biology |
DOI:10.1371/journal.pcbi.1004525 October 22, 2015 3 / 9
https://dmponline.dcc.ac.uk/
Rule 3: Define How the Data Will Be Organized
Once there is an understanding of the volume and types of data
to be collected, a next obvious
14. step is to define how the data will be organized and managed.
For many projects, a small num-
ber of data tables will be generated that can be effectively
managed with commercial or open
source spreadsheet programs like Excel and OpenOffice Calc.
Larger data volumes and usage
constraints may require the use of relational database
management systems (RDBMS) for
linked data tables like ORACLE or mySQL, or a Geographic
Information System (GIS) for
geospatial data layers like ArcGIS, GRASS, or QGIS.
The details about how the data will be organized and managed
could fill many pages of text
and, in fact, should be recorded as the project evolves.
However, in drafting a DMP, it is most
helpful to initially focus on the types and, possibly, names of
the products that will be used.
The software tools that are employed in a project should be
amenable to the anticipated tasks.
A spreadsheet program, for example, would be insufficient for a
project in which terabytes of
data are expected to be generated, and a sophisticated RDMBS
may be overkill for a project in
which only a few small data tables will be created. Furthermore,
projects dependent upon a GIS
or RDBMS may entail considerable software costs and design
and programming effort that
should be planned and budgeted for upfront (see Rules 9 and
10). Depending on sponsor
requirements and space constraints, it may also be useful to
specify conventions for file nam-
ing, persistent unique identifiers (e.g., Digital Object Identifiers
[DOIs]), and versioning con-
trol (for both software and data products).
15. Rule 4: Explain How the Data Will Be Documented
Rows and columns of numbers and characters have little to no
meaning unless they are docu-
mented in some fashion. Metadata—the details about what,
where, when, why, and how the
data were collected, processed, and interpreted—provide the
information that enables data and
files to be discovered, used, and properly cited. Metadata
include descriptions of how data and
files are named, physically structured, and stored as well as
details about the experiments, ana-
lytical methods, and research context. It is generally the case
that the utility and longevity of
data relate directly to how complete and comprehensive the
metadata are. The amount of effort
devoted to creating comprehensive metadata may vary
substantially based on the complexity,
types, and volume of data.
A sound documentation strategy can be based on three steps.
First, identify the types of
information that should be captured to enable a researcher like
you to discover, access, inter-
pret, use, and cite your data. Second, determine whether there is
a community-based metadata
schema or standard (i.e., preferred sets of metadata elements)
that can be adopted. As exam-
ples, variations of the Dublin Core Metadata Initiative Abstract
Model are used for many types
of data and other resources, ISO (International Organization for
Standardization) 19115 is
used for geospatial data, ISA-Tab file format is used for
experimental metadata, and Ecological
Metadata Language (EML) is used for many types of
environmental data. In many cases, a spe-
cific metadata content standard will be recommended by a target
16. data repository, archive, or
domain professional organization. Third, identify software tools
that can be employed to create
and manage metadata content (e.g., Metavist, Morpho). In lieu
of existing tools, text files (e.g.,
readme.txt) that include the relevant metadata can be included
as headers to the data files.
A best practice is to assign a responsible person to maintain an
electronic lab notebook, in
which all project details are maintained. The notebook should
ideally be routinely reviewed
and revised by another team member, as well as duplicated (see
Rules 6 and 9). The metadata
recorded in the notebook provide the basis for the metadata that
will be associated with data
products that are to be stored, reused, and shared.
PLOS Computational Biology |
DOI:10.1371/journal.pcbi.1004525 October 22, 2015 4 / 9
Rule 5: Describe How Data Quality Will Be Assured
Quality assurance and quality control (QA/QC) refer to the
processes that are employed to
measure, assess, and improve the quality of products (e.g., data,
software, etc.). It may be neces-
sary to follow specific QA/QC guidelines depending on the
nature of a study and research
sponsorship; such requirements, if they exist, are normally
stated in the RFP. Regardless, it is
good practice to describe the QA/QC measures that you plan to
employ in your project. Such
measures may encompass training activities, instrument
calibration and verification tests, dou-
17. ble-blind data entry, and statistical and visualization approaches
to error detection. Simple
graphical data exploration approaches (e.g., scatterplots,
mapping) can be invaluable for detect-
ing anomalies and errors.
Rule 6: Present a Sound Data Storage and Preservation Strategy
A common mistake of inexperienced (and even many
experienced) researchers is to assume
that their personal computer and website will live forever. They
fail to routinely duplicate their
data during the course of the project and do not see the benefit
of archiving data in a secure
location for the long term. Inevitably, though, papers get lost,
hard disks crash, URLs break,
and tapes and other media degrade, with the result that the data
become unavailable for use by
both the originators and others. Thus, data storage and
preservation are central to any good
data management plan. Give careful consideration to three
questions:
1. How long will the data be accessible?
2. How will data be stored and protected over the duration of
the project?
3. How will data be preserved and made available for future
use?
The answer to the first question depends on several factors.
First, determine whether the
research sponsor or your home institution have any specific
requirements. Usually, all data do
not need to be retained, and those that do need not be retained
forever. Second, consider the
18. intrinsic value of the data. Observations of phenomena that
cannot be repeated (e.g., astronom-
ical and environmental events) may need to be stored
indefinitely. Data from easily repeatable
experiments may only need to be stored for a short period.
Simulations may only need to have
the source code, initial conditions, and verification data stored.
In addition to explaining how
data will be selected for short-term storage and long-term
preservation, remember to also high-
light your plans for the accompanying metadata and related
code and algorithms that will
allow others to interpret and use the data (see Rule 4).
Develop a sound plan for storing and protecting data over the
life of the project. A good
approach is to store at least three copies in at least two
geographically distributed locations
(e.g., original location such as a desktop computer, an external
hard drive, and one or more
remote sites) and to adopt a regular schedule for duplicating the
data (i.e., backup). Remote
locations may include an offsite collaborator’s laboratory, an
institutional repository (e.g., your
departmental, university, or organization’s repository if located
in a different building), or a
commercial service, such as those offered by Amazon, Dropbox,
Google, and Microsoft. The
backup schedule should also include testing to ensure that
stored data files can be retrieved.
Your best bet for being able to access the data 20 years beyond
the life of the project will
likely require a more robust solution (i.e., question 3 above).
Seek advice from colleagues and
librarians to identify an appropriate data repository for your
19. research domain. Many disci-
plines maintain specific repositories such as GenBank for
nucleotide sequence data and the
Protein Data Bank for protein sequences. Likewise, many
universities and organizations also
host institutional repositories, and there are numerous general
science data repositories such as
PLOS Computational Biology |
DOI:10.1371/journal.pcbi.1004525 October 22, 2015 5 / 9
Dryad (http://datadryad.org/), figshare (http://figshare.com/),
and Zenodo (http://zenodo.org/
). Alternatively, one can easily search for discipline-specific
and general-use repositories via
online catalogs such as http://www.re3data.org/ (i.e., REgistry
of REsearch data REpositories)
and http://www.biosharing.org (i.e., BioSharing). It is often
considered good practice to deposit
code in a host repository like GitHub that specializes in source
code management as well as
some types of data like large files and tabular data (see
https://github.com/). Make note of any
repository-specific policies (e.g., data privacy and security,
requirements to submit associated
code) and costs for data submission, curation, and backup that
should be included in the DMP
and the proposal budget.
Rule 7: Define the Project’s Data Policies
Despite what may be a natural proclivity to avoid policy and
legal matters, researchers cannot
afford to do so when it comes to data. Research sponsors,
institutions that host research, and
20. scientists all have a role in and obligation for promoting
responsible and ethical behavior. Con-
sequently, many research sponsors require that DMPs include
explicit policy statements about
how data will be managed and shared. Such policies include:
• licensing or sharing arrangements that pertain to the use of
preexisting materials;
• plans for retaining, licensing, sharing, and embargoing (i.e.,
limiting use by others for a
period of time) data, code, and other materials; and
• legal and ethical restrictions on access and use of human
subject and other sensitive data.
Unfortunately, policies and laws often appear or are, in fact,
confusing or contradictory.
Furthermore, policies that apply within a single organization or
in a given country may not
apply elsewhere. When in doubt, consult your institution’s
office of sponsored research, the rel-
evant Institutional Review Board, or the program officer(s)
assigned to the program to which
you are applying for support.
Despite these caveats, it is usually possible to develop a sound
policy by following a few sim-
ple steps. First, if preexisting materials, such as data and code,
are being used, identify and
include a description of the relevant licensing and sharing
arrangements in your DMP. Explain
how third party software or libraries are used in the creation and
release of new software. Note
that proprietary and intellectual property rights (IPR) laws and
export control regulations may
21. limit the extent to which code and software can be shared.
Second, explain how and when the data and other research
products will be made available.
Be sure to explain any embargo periods or delays such as
publication or patent reasons. A com-
mon practice is to make data broadly available at the time of
publication, or in the case of grad-
uate students, at the time the graduate degree is awarded.
Whenever possible, apply standard
rights waivers or licenses, such as those established by Open
Data Commons (ODC) and Crea-
tive Commons (CC), that guide subsequent use of data and other
intellectual products (see
http://creativecommons.org/ and
http://opendatacommons.org/licenses/pddl/summary/). The
CC0 license and the ODC Public Domain Dedication and
License, for example, promote unre-
stricted sharing and data use. Nonstandard licenses and waivers
can be a significant barrier to
reuse.
Third, explain how human subject and other sensitive data will
be treated (e.g., see http://
privacyruleandresearch.nih.gov/ for information pertaining to
human health research regula-
tions set forth in the US Health Insurance Portability and
Accountability Act). Many research
sponsors require that investigators engaged in human subject
research approaches seek or
receive prior approval from the appropriate Institutional Review
Board before a grant proposal
PLOS Computational Biology |
DOI:10.1371/journal.pcbi.1004525 October 22, 2015 6 / 9
22. http://datadryad.org/
http://figshare.com/
http://zenodo.org/
http://www.re3data.org/
http://www.biosharing.org/
https://github.com/
http://creativecommons.org/
http://opendatacommons.org/licenses/pddl/summary/
http://privacyruleandresearch.nih.gov/
http://privacyruleandresearch.nih.gov/
is submitted and, certainly, receive approval before the actual
research is undertaken. Approv-
als may require that informed consent be granted, that data are
anonymized, or that use is
restricted in some fashion.
Rule 8: Describe How the Data Will Be Disseminated
The best-laid preservation plans and data sharing policies do not
necessarily mean that a proj-
ect’s data will see the light of day. Reviewers and research
sponsors will be reassured that this
will not be the case if you have spelled out how and when the
data products will be dissemi-
nated to others, especially people outside your research group.
There are passive and active
ways to disseminate data. Passive approaches include posting
data on a project or personal
website or mailing or emailing data upon request, although the
latter can be problematic when
dealing with large data and bandwidth constraints. More active,
robust, and preferred
approaches include: (1) publishing the data in an open
repository or archive (see Rule 6); (2)
submitting the data (or subsets thereof) as appendices or
23. supplements to journal articles, such
as is commonly done with the PLOS family of journals; and (3)
publishing the data, metadata,
and relevant code as a “data paper” [5]. Data papers can be
published in various journals,
including Scientific Data (from Nature Publishing Group), the
GeoScience Data Journal (a
Wiley publication on behalf of the Royal Meteorological
Society), and GigaScience (a joint
BioMed Central and Springer publication that supports big data
from many biology and life
science disciplines).
A good dissemination plan includes a few concise statements.
State when, how, and what
data products will be made available. Generally, making data
available to the greatest extent
and with the fewest possible restrictions at the time of
publication or project completion is
encouraged. The more proactive approaches described above are
greatly preferred over mailing
or emailing data and will likely save significant time and money
in the long run, as the data
curation and sharing will be supported by the appropriate
journals and repositories or archives.
Furthermore, many journals and repositories provide guidelines
and mechanisms for how oth-
ers can appropriately cite your data, including digital object
identifiers, and recommended cita-
tion formats; this helps ensure that you receive credit for the
data products you create. Keep in
mind that the data will be more usable and interpretable by you
and others if the data are dis-
seminated using standard, nonproprietary approaches and if the
data are accompanied by
metadata and associated code that is used for data processing.
24. Rule 9: Assign Roles and Responsibilities
A comprehensive DMP clearly articulates the roles and
responsibilities of every named individ-
ual and organization associated with the project. Roles may
include data collection, data entry,
QA/QC, metadata creation and management, backup, data
preparation and submission to an
archive, and systems administration. Consider time allocations
and levels of expertise needed
by staff. For small to medium size projects, a single student or
postdoctoral associate who is
collecting and processing the data may easily assume most or
all of the data management tasks.
In contrast, large, multi-investigator projects may benefit from
having a dedicated staff person
(s) assigned to data management.
Treat your DMP as a living document and revisit it frequently
(e.g., quarterly basis). Assign
a project team member to revise the plan, reflecting any new
changes in protocols and policies.
It is good practice to track any changes in a revision history that
lists the dates that any changes
were made to the plan along with the details about those
changes, including who made them.
Reviewers and sponsors may be especially interested in
knowing how adherence to the data
management plan will be assessed and demonstrated, as well as
how, and by whom, data will
PLOS Computational Biology |
DOI:10.1371/journal.pcbi.1004525 October 22, 2015 7 / 9
25. be managed and made available after the project concludes.
With respect to the latter, it is
often sufficient to include a pointer to the policies and
procedures that are followed by the
repository where you plan to deposit your data. Be sure to note
any contributions by nonpro-
ject staff, such as any repository, systems administration,
backup, training, or high-perfor-
mance computing support provided by your institution.
Rule 10: Prepare a Realistic Budget
Creating, managing, publishing, and sharing high-quality data is
as much a part of the 21st
century research enterprise as is publishing the results. Data
management is not new—rather,
it is something that all researchers already do. Nonetheless, a
common mistake in developing a
DMP is forgetting to budget for the activities. Data management
takes time and costs money in
terms of software, hardware, and personnel. Review your plan
and make sure that there are
lines in the budget to support the people that manage the data
(see Rule 9) as well as pay for
the requisite hardware, software, and services. Check with the
preferred data repository (see
Rule 6) so that requisite fees and services are budgeted
appropriately. As space allows, facilitate
reviewers by pointing to specific lines or sections in the budget
and budget justification pages.
Experienced reviewers will be on the lookout for unfunded
components, but they will also rec-
ognize that greater or lesser investments in data management
depend upon the nature of the
research and the types of data.
26. Conclusion
A data management plan should provide you and others with an
easy-to-follow road map that
will guide and explain how data are treated throughout the life
of the project and after the proj-
ect is completed. The ten simple rules presented here are
designed to aid you in writing a good
plan that is logical and comprehensive, that will pass muster
with reviewers and research spon-
sors, and that you can put into practice should your project be
funded. A DMP provides a vehi-
cle for conveying information to and setting expectations for
your project team during both
the proposal and project planning stages, as well as during
project team meetings later, when
the project is underway. That said, no plan is perfect. Plans do
become better through use. The
best plans are “living documents” that are periodically reviewed
and revised as necessary
according to needs and any changes in protocols (e.g., metadata,
QA/QC, storage), policy, tech-
nology, and staff, as well as reused, in that the most successful
parts of the plan are incorpo-
rated into subsequent projects. A public, machine-readable, and
openly licensed DMP is much
more likely to be incorporated into future projects and to have
higher impact; such increased
transparency in the research funding process (e.g., publication
of proposals and DMPs) can
assist researchers and sponsors in discovering data and potential
collaborators, educating
about data management, …