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Consistency means that the same rules are used for every single piece of data. For example, if you decide that names should be recorded by first and last initials, make sure that every piece of data about names is recorded in this way.

Logic means that there is a recognizable pattern to the naming and recording rules. Another person should be able to figure out why you have named or recorded your data in this particular way. For example, your team might decide to label each piece of budget data with the name of the department that the expense belongs to.

Anonymity means that you are taking appropriate measures to protect the privacy and identity of those whose data you have collected. Data privacy rules can be very strict and vary based on location and circumstance. Pieces of data that could be used to identify an individual such as names, dates of birth, or address should be very tightly controlled.

One way to ensure anonymity is to replace identifiable information with anonymous identification codes. This process is known as de-identification.

For example, imagine that your group is working with a group of individuals who have contracted the HIV virus. If this list of individuals was released, your participants could suffer from social stigma or worse. So, instead of recording names in your data, you assign a unique identification number to each participant. Wherever you would record a participant’s name, you instead record their unique identification number. This way, if data is stolen or accidentally leaked, it would be much more difficult to identify your participants.

Data is stored so that in short term or long term that data might be used.
The system that is being used being analogy or digital should be easily accessed by authorized users. Make should the data is filed properly so that user should not struggle to find it. For the data that will be used for more years that data need to be archive. so that after some years this data can still be accessed

Data can be uploaded and downloaded from nearly anywhere. Any person with the right software, hardware and account permissions can add new data or access existing data.
Data can be easily accessed. Unlike data on a sheet of paper, the same data can be accessed by multiple people simultaneously.
Data can be reorganized. All database solutions, whether they are a simple Excel spreadsheet or more complex software, allow you to sort and organize your data easily.
Data can be prepared for data analysis. Some data storage and management systems allow you to do data visualization and analysis directly in the software. Others make it easy to export data to data analysis software.
However, digital data management can also be expensive, complicated and can, if not implemented well, risk the security of your data. You will need to pay for software, hardware, updates and fixes. If your organization does not have several people on the team who are comfortable using this technology, you should consider starting with a simple, physical data management system.

Deciding on how your data is stored and accessed is an important aspect in data management.

This helps to ensure that only people with the right permission accesses data so as to maintain high levels of confidentiality

Data Management System follows series of procedures, ranging from collection to Presentation. You cannot manage data if you collected nothing. What are you going to store? Therefore, all steps must be followed.
Digital systems are mainly used to access, organize and archive data, with set guidelines. All guidelines must be adhered to, with the organization of ownership having absolute control over the data, but apply ethical principles as well.

Hi everyone! My name is Yeko Isaac from Uganda, East Africa. I am very excited to have enrolled in this course having completed and received a certificate of achievement in Planning for Monitoring and Evaluation and From data collection to data use.

The experience was amazing and that explains why i have decided to enrol in this course.

I am looking forward to learning new skills in this topic and i believe that this will make a difference in my organization.

Thanks everyone in this team.

Data access and archival
Data archiving is the process of storing structured and unstructured data for long-term preservation so that it can be accessed at any time when needed by an organization to be used for: Strategic analysis. Historical reference. Compliance requirements

Data archiving is the practice of identifying data that is no longer active and moving it out of production systems into long-term storage systems. Archival data is stored so that at any time it can be brought back into service.

What is archival access?
Access is a set of activities that links primary source materials to the public. Archivists should be able to answer questions about specific collections, such as their sizes, date ranges, the existence of correspondence by individuals, research restrictions, and copyright status, among other issue

You can not just leave it open for the public to access data you have collected. Ethically, You will be breaching the Do No harm and beneficiaries of a specific project might be at risk of being following the information that might get leaked. Also, remember to be confidential about this information and allow access to those who can be trusted. Also, you are to set an aunthetication process for data access. Archiving data is important as information might be required later even if the project phases out. However, make sure the data is organized that it can be easily found when queried

Wow, this is complex 😂😂😂😂😂😂

From the notes, I understand that effective data management involves several key aspects: data format, data naming, data storage and recording using uniform rules and methods to ensure clarity and consistency, and data security using access magnetic archiving procedures. We need to take into account what data will be needed, the level of this data’s accessibility, and how to store and search the data in the future. Ethical aspects must not be overlooked while emphasising on the securing of data to protect privacy as well as create barriers against possible harms.

Acesso a Dados:
Segurança da Informação: Garantir que apenas usuários autorizados tenham acesso aos dados, geralmente por meio de autenticação e controle de acesso baseado em funções.

Políticas de Acesso: Estabelecer políticas claras sobre quem pode acessar quais tipos de dados e em que circunstâncias.

Criptografia: Proteger dados sensíveis através de técnicas de criptografia para garantir que mesmo que os dados sejam interceptados, eles não possam ser lidos sem a chave correta.

Monitoramento de Acesso: Implementar sistemas para monitorar quem acessa os dados e o que eles fazem com esses dados, a fim de detectar atividades suspeitas.

Acesso Remoto: Assegurar que os dados possam ser acessados de forma segura a partir de locais remotos, sem comprometer a segurança.

Arquivamento de Dados:
Políticas de Retenção de Dados: Estabelecer políticas para determinar por quanto tempo os dados devem ser mantidos com base em requisitos legais, regulatórios e operacionais.

Backup Regular: Realizar backups regulares dos dados para protegê-los contra perda devido a falhas de hardware, erro humano, desastres naturais ou cibernéticos.

Gerenciamento de Espaço de Armazenamento: Implementar práticas para gerenciar eficientemente o espaço de armazenamento, como compressão de dados, deduplicação e arquivamento de dados menos utilizados.

Indexação e Organização: Indexar e organizar os dados de forma que possam ser facilmente encontrados quando necessário.

Migração de Dados: Periodicamente migrar dados para novos sistemas ou formatos para garantir sua acessibilidade a longo prazo, especialmente em face da obsolescência de tecnologia.

Conformidade Regulatória: Garantir que o arquivamento de dados esteja em conformidade com regulamentações relevantes, como o Regulamento Geral de Proteção de Dados (GDPR) na União Europeia ou a Lei de Privacidade do Consumidor da Califórnia (CCPA) nos Estados Unidos

Data access and archival are critical components of data management that ensure data is accessible when needed and securely stored for future reference.

Data access and archival are critical components of data management that ensure data is accessible when needed and securely stored for future reference.

Applied in all data process that support for data quality management

There are three key Principles to consider in Data recording:

• Consistency

• Logic

• Confidentiality
  Data infrastructure is a collection of tools and systems
  Data Security is a process and system for ensuring that data can only be accessed . changed, or deleted by those with permission.

Do no harm

Hi! my name is Ruot Gach i am very glad to join this is topic. the data access and data archive are the usefull terms for data management. Data access talk about the security and the privacy of controlling the data of individual not to share them with unauthorized person. The data can be access only by person with permission. The archive is way of storing and organizing the data in the safe place for longtime use. the data need to be stored by creating folders and the sub folders which will prevent the data loss and make easy to access data when needed. sometime for files the cabinet should locked with lockpad and it safe the accessibility of the data by any one.

Data Access and Archival: The Cornerstone of Effective M&E
Data access and archival are fundamental components of a robust Monitoring and Evaluation (M&E) system. They ensure the information collected serves its purpose of program improvement, fosters transparency, and allows for future analysis. Here's why data access and archival are crucial for M&E:

Benefits of Accessible Data:

Improved Program Management: Easy access to data empowers program managers to track progress, identify areas for improvement, and make data-driven decisions to optimize program effectiveness.
Enhanced Collaboration: Accessible data allows for collaboration among stakeholders, including donors, researchers, and implementing partners. This fosters knowledge sharing and facilitates the development of more impactful programs.
Increased Transparency and Accountability: Accessible data promotes transparency by allowing stakeholders to see how programs are performing and how resources are being used. This builds trust and accountability.
Importance of Data Archival:

Long-Term Analysis: Archiving data allows for future analysis, even after program completion. This can be valuable for identifying long-term trends, evaluating program sustainability, and informing future program design.
Meeting Donor Requirements: Many donors require data to be archived for a specific period. This ensures access for audits or future evaluations.
Ethical Considerations: Data archival safeguards important information, especially when dealing with sensitive data. Proper archiving ensures responsible data management and protects participant privacy.
Challenges and Considerations:

Data Security: Data access should be controlled to ensure only authorized users can access sensitive information. Robust security measures are crucial for preventing data breaches.
Data Storage Capacity: Long-term data storage requires adequate storage capacity and data management systems.
Data Quality: Data archived for future use should be well-documented and cleaned to ensure its accuracy and interpretability for future analysts.
Best Practices for Data Access and Archival:

Develop Data Access Protocols: Establish clear guidelines on who can access data, under what circumstances, and what level of access is granted based on user roles.
Invest in Data Archiving Solutions: Choose secure and reliable data storage solutions that meet your program's specific needs and comply with data privacy regulations.
Data Documentation: Document your data collection process thoroughly, including data definitions, coding schemes, and any data cleaning procedures used. This ensures future users can understand the data and replicate analyses if needed.
Regular Backups: Implement regular data backup protocols to prevent data loss in case of technical failures.

Access Permissions:

Who should be able to access the data? This may include the M&E team, management team, specific staff members, or external stakeholders.
Should certain people have access only to specific data? For instance, staff from different programs may require access to data relevant to their program area.
Should different types of users have different levels of access? Some individuals may have permission to view data, while others have permission to edit or modify it.
Data Security:

How will data security be ensured to prevent unauthorized access? This could involve implementing measures such as user authentication, encryption, and access controls.
What mechanisms will be in place to safeguard confidential or sensitive data? Protecting the privacy and confidentiality of individuals or groups described in the data is paramount.
Search and Retrieval:

How will data be searched and retrieved? This may involve utilizing search or query functions within data management software or maintaining a well-organized filing system with clear directories.
Accessibility and ease of retrieval are crucial for efficient data management and decision-making processes.
Archiving and Storage:

When should data be archived and moved into long-term storage? Establishing guidelines for archiving data ensures that valuable information is retained for future reference and compliance with donor requirements.
Considerations for long-term storage include the duration data should be retained, the format in which it should be stored, and provisions for data backup and disaster recovery.
Ethical Considerations:

Recognizing the ethical implications of data management is essential, particularly regarding the confidentiality and security of sensitive information.
Ensuring that only authorized individuals have access to confidential data helps mitigate the risk of compromising the safety and privacy of individuals or groups described in the data.
By addressing these questions and implementing appropriate policies, procedures, and technological solutions, organizations can effectively manage and safeguard their data, ensuring its accessibility, integrity, and security over time.

In an organization, it is very important to structure how data might be access and being stored mostly for a longer term. On data access, this is how to manage the people how needs to access the data and with the restrictions. In some cases, Others can be permitted to be viewer, editor or view and commentator depending on their roles and other cannot have either option for access. For example you cannot give a messenger or a guard to access the database and be an editor. Access and restrictions goes mostly in the same direction.

On data archival, the organization need to make decisions for how long a particular set of data will be useful. for example in government agencies, some data is needed forever of which it can be a reference for other activities in future. In other dataset might be needed for a short period of time, for example project data of which its needed for the project life time and when it phase out it is kept for only few years and later it can be deleted if its allowed.

All in all data access and archival are good components to look at as far as data management is needed within the organization Monitoring and Evaluation team