Help

Frequently uzdotie jFAQs about pethic dat pārvaldību

In this section, you will find answers to frequently asked questions about research data management, including setting up data management plans and research ethics, as well as explanations of key concepts. This information will help researchers to manage research data effectively and in line with best practice.

Research datu pārvaldībbasic concepts

What is research data?

Answer: research data is any information collected, observed or generated in the course of a research project that is used as a basis for obtaining research results and drawing conclusions. Research data can be:

• Numerical measurements, such as temperature measurements in laboratory experiments

• Text, e.g. notes on the literature analysis

• Images, such as microscopy images

• Videos, such as recordings of experiments

• Audio recordings, such as recordings of interviews

• Software codes, such as code for data analysis software

• Other data formats

What is not research data?

Answer: data that are not directly related to scientific research are not considered research data. Research data are not:

• Administrative records of the study, such as financial statements or personnel files

• Commercial or private communications, such as emails or correspondence

• Legal documents such as employment contracts or cooperation agreements

• Marketing materials such as promotional leaflets

These data do not contribute to the scientific analysis or evidence base of the research project and therefore do not qualify as research data.

What is a dataset?

Answer to: a dataset is a structured collection of data, usually arranged in tables or other structured forms, consisting of a number of data elements or values that have been collected and prepared for analysis. For example, in an epidemiological study, a dataset could include patients' age, sex, symptoms and treatment outcomes. In a sociological study, the dataset could include survey respondents' answers to various questions.

What is research data management and why is it important?

Answer to: pEthics data management (EDM) is a systematic approach that involves planning, collecting, storing, sharing and archiving data. It is essential to ensure data quality, long-term accessibility and the possibility of re-use in other studies. PDPs help to meet legal and ethical requirements and ensure compliance with the requirements of research funders.

What are the FAIR Principles?

Answer toA: The FAIR Principles are guidelines that state that research data must be made:

• Findable: data and its metadata are easily found by other researchers and systems

• Accessible: the data are available and the conditions for access are clearly stated

• Interoperable: data are compatible with other systems and datasets

• Reusable: data are prepared in such a way that they can be reused in the future

What is open data and do I always have to make my research data public?

Answer to: aThe data measured are publicly available research data that can be freely used, shared and analysed. However, research data does not always need to be made open data. Data can be protected if it contains Sensitive or personal information, or where publication could harm the participants, the authors or the public.

Are open data and FAIR data synonymous?

Answer: aweighted data and FAIR data are not synonymous as they have different approaches and objectives. Open data is freely available to everyone, while FAIR data means that data is searchable, accessible, interoperable and reusable (Findable, Accessible, Interoperable, Reusable). The FAIR principles do not impose a mandatory opening of data, but ensure that data are easily accessible and can be used as widely as possible, preserving confidentiality where necessary. This means that data can comply with the FAIR principles but not be publicly available if protected by privacy or ownership restrictions.

What is a Research Data Management Plan?

Answer: a Research Data Management Plan (RDMP) is a document that describes how the information and data created or generated by a research project will be organised, processed, stored and shared. DPPs are an essential part of modern research as they help to ensure the quality, availability and sustainability of data.

How can I start developing a data management plan?

Answer to: dA Data Management Plan (DMP) usually starts by defining what data will be collected, how it will be stored and shared, and what security and privacy requirements need to be met. It is recommended to use DPP templates provided by universities or research funders, as well as systems such as Argos or DMPonlineto help you structure your plan step by step.

How to store research data securely?

Answer to: pt is recommended to store research data in encrypted and secure locations, e.g. on cloud service access-controlled servers, university servers or specialised data repositories. It is important to make regular backups and comply with data protection requirements such as GDPR/GDPR (General Data Protection Regulation).

What are data repositories?

Answer to: drepositories are digital platforms designed to securely store, organise, share and update research data. They provide long-term data storage and access to the wider research community, while promoting good data management practices. For example, Zenodo is a well-known repository used by researchers in various fields, or GenBankwhich is a specialised repository for biological data. Multidisciplinary repository available in Latvia DatavarseLV.

How do I choose a repository to deposit my dataset?

Answer to: when choosing a repository to deposit (publish) your dataset, there are several factors to consider. In general, it is important to choose a trustworthy repository that offers metadata standards, long-term data storage and access, meets ethical and confidentiality requirements, and meets funder and institutional requirements.

It may be useful to choose a discipline-specific repository for a particular scientific discipline. For example, GenBank or Dryad repositories may be appropriate for biological data, while ICPSR, CESSDA or Figshare may be appropriate for social science data.

Where can I upload and publish my data?

Answer to: pResearch data can be placed in data repositories that are appropriate for the research sector or institution. Some of the most popular repositories are Zenodo, Figshare, or specialised repositories such as Dryad or Pangaea.

How do I make sure my data is re-usable (FAIR principles)?

Answer to: lai Ensure data re-use by including detailed and standardised metadata explaining the structure, format and context of the data. Make sure that data are published in an acceptable and widely used format, and include clear provisions on data use licences, such as, Creative Commons.

What is metadata and why is it important?

Answer to: metadata is data about data, providing information about the content, structure, origin and format of a dataset. For example, photographic metadata may include information on the date, location and camera settings of a photograph, while research data metadata may indicate the method and sources of data collection. Metadata is essential for other researchers to find, understand and use your data. Without metadata, data can be difficult to understand and use.

Do I need to develop a data management plan for all research projects?

Answer to: jIn most cases, research funders and institutions require a Data Management Plan (DMP), especially for larger studies. Even if a plan is not mandatory, by developing a DMP you can systematically plan how to manage, protect and share data, thereby improving the quality and transparency of your project.

What if my data contains sensitive information or personal data?

Answer to: ja data from the study contain sensitive information or personal data, it is necessary anonymised or pseudonymisedto protect the privacy of individuals. It is also essential to limit access to data and use secure data storage and transfer solutions. In addition, compliance with data protection regulations, such as VDAR/GDPR.

Research datu peadministration pon the ARGOS platform

1. What is ARGOS and how does it help with research data management?

Answer to: ARGOS is an online platform for developing and managing Research Data Management Plans (RDPs). It helps researchers to structure, develop and comply with funders' requirements for data management throughout the research process. ARGOS offers templates and automated processes to facilitate the creation of DPPs.

2. Is ARGOS free to use?

Answer to: jARGOS is a free tool that researchers can use to create, manage and submit research data management plans. Many universities and research funders recommend or require its use for research projects.

3. How do I create a Data Management Plan (DMP) in ARGOS?

Answer to: lto create a DPP on the platform ARGOS, and set up an account You can then select the template that meets the requirements of your funder or institution and fill in the relevant fields on data collection, storage, sharing and security. ARGOS offers guides and instructions to help you complete your plan.

4. What should I write in the section on data storage and security?

Answer to: šThis section should specify where the data will be stored, e.g. on a university server, on a cloud serviceand what security measures will be taken, such as data encryption, access control. It should also mention how data backup will be ensured and how Sensitive information to meet security requirements.

5. Does ARGOS support the requirements of different funders?

Answer to: jā, ARGOS offers templates designed to meet the requirements of different national and international funders, such as, Horizon Europe or Latvian Research Council. The templates include specific questions to help ensure compliance with these requirements.

6. How to integrate FAIR principles into a data management plan on the ARGOS platform?

Answer to: FAIR principles requires research data to be discoverable, accessible, interoperable and re-usable. When developing the DPP, make sure you describe how the data will be annotated with metadata, how access to the data will be provided and what formats will be used to ensure interoperability and reuse. ARGOS provides guidance to help integrate these principles into the data management plan.

7. What if I don't have the right data management solutions yet?

Answer to: ja You have not yet identified all the options at the time of the DPP, you can indicate that these aspects will be clarified later in the study. ARGOS provides the possibility to update the DPP at any stage of the project, so the plan can be updated or clarified as additional information becomes available.

8. Can I set up a joint DPP with colleagues?

Answer to: jā, ARGOS supports collaboration features, allowing multiple people to work on the same data management plan at the same time. You can invite colleagues or collaborators to join you in developing your plan, specifying the access rights they need.

9. How can I ensure that my data is available and shared after the project ends?

Answer toIn the data sharing section of the DPP, you need to specify where the data will be stored after the end of the study, e.g. in an institutional repository or in open data repositories. It is important to mention whether the data will be publicly available and to specify the conditions for access, such as licensing.

10. What are the most common mistakes made when drafting a DPP?

Answer to: bThe most common mistakes are insufficiently detailed description of data storage and security requirements, incorrectly defined availability of data after the end of the project, and failure to comply with FAIR principles. ARGOS provides automated guidance to help avoid these mistakes, but it is important to carefully review and accurately complete all fields.

Frequently asked questions about juridical and ethical aspects

1. What are personal and sensitive data?

Answer to: sin the GDPR/GDPR conversation, personal data means any information relating to an identified or identifiable natural person. Personal data are considered to be for sensitive under EU law protection where they concern religion, politics, health, etc.

2. I submitted my manuscript to a journal, but it was not accepted because no research ethics review. What should I do?

Answer to: rThe solution may vary depending on the case. You can contact the unit which your university responsible for research ethics to give its opinion.

3. I will work with personal data. What documents do I need to prepare before I start work?

Answer to: pIf you start working with personal data, you must draw up and submit a data management plan (DMP) describing the data protection measures and the data retention plan. You must also ensure that you have documentation in place to consent to the processing of personal data in line with GDPR requirements, e.g. obtain informed consent from participants. It is recommended to prepare a confidentiality agreement on data security for the parties involved and to set access restrictions. Finally, document the data Anonymisation or pseudonymisation methodologies to protect the privacy of participants.

4. Do I need a privacy notice if data is collected anonymously?

Answer to: jyes, it is necessary. Explain how the participants' personal data will be handled using the confidentiality notice. Even if survey data is collected anonymously, it may form an identifiable personal profile, for example using information related to occupation, age or education. Even e-mail addresses are considered personal data.

5 I want to re-use data belonging to a company, but they have concerns about sharing it with me. What should I do?

Answer to: jtions must conclude a contract with the data provider (i.e. the company) and this contract must describe issues related to data ownership, re-use, etc. Ask your university lawyer for help in drafting such an agreement.

Data kucomputer servicesme

Data curator Network provided by support for researchers on issues related to data management:

• Support for the development of a data management plan

• Supporting the implementation of FAIR principles in practice

• Advice on implementing good practices in data management

• Support for depositing datasets in a repository

Data curation services available to all researchers in Latvia – either by contacting specific university's data curation team or with data curators Higher Education and Science IT Service Sharing Centre (HSSC).