4. Prepare the Study Description

Publication Year: 08. 04. 2017    Date of last inspection: 07. 11. 2017


In order to understand the data file and accompanying materials, a thorough description of the study is needed in order to assure secondary use of the study. The Study Description Form is based on the International Standard Study Description DDI. As in the case of preparing data, only the author himself, as the expert of the proposed study, can contribute the most to the description of bibliographical and methodological details of the study. 

The Form is divided into five basic chapters: initial study information, study content, methodology, additional study information, and contact. It is recommended to follow descriptions of already published studies in the Catalogue of the ADP (in XML formats).  

Based on the Study Description Form and other submitted materials, the ADP will prepare a metadata description of the study that will be the basis of your data publication. In case you have problems in filling in the form, do contact us.

We recommend reading the tab Help before filling in the form.

  The study description should be made in Slovenian and English!  


STUDY DESCRIPTION FORM (only in Slovenian)


Even though we recommend filling-in the Study Description form ONLINE since it makes our work on your study easier, you may alternatively download the form locally and send it to us together with other materials.


You may download the form in  doc or pdf.


Individual Any individual person, irrespective of demographic characteristics, professional, social or legal status, or affiliation.
Organization Any kind of formal administrative and functional structure - includes associations, institutions, agencies, businesses, political parties, schools, etc.
Family Two or more people related by blood, marriage (including step-relations), adoption or fostering and who may or may not live together (National Community Services Data Dictionary, Vers 3, AIHW, 2004). For example, used when researching the extent to which people provide support and assistance for their relatives.
Family: Household family A more specific term, refers only to related people who live in the same household at a point in time. If not known whether the analysis unit is "Family" or "Household family", use "Family".
Household A person or a group of persons who share the same dwelling unit and common living arrangements. These common living arrangements may include pooling some, or all, of their income and wealth, and consuming certain types of goods and services collectively, mainly housing and food (Eurostat).
Housing Unit U.S. Census: A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from the outside of the building or through a common hall.
Event/Process Any type of incident, occurrence, or activity. Events are usually one-time, individual occurrences, with a limited, or short duration. Examples: criminal offenses, riots, meetings, elections, sports competitions, terrorist attacks, natural disasters like floods, etc. Processes typically take place over time, and may include multiple "events" or gradual changes that ultimately lead, or are projected to lead, to a particular result. Examples: court trials, criminal investigations, political campaigns, medical treatments, education, athletes' training, etc.
Geographic Unit Any entity that can be spatially defined as a geographic area, with either natural (physical) or administrative boundaries.
Time Unit Any period of time: year, week, month, day, or bimonthly or quarterly periods, etc.
Text Unit Books, articles, any written piece/entity.
Group Two or more individuals assembled together or having some unifying relationship.
Object Anything material, but inanimate, that has an independent existence and may be perceived by the senses. Examples: objects of art (paintings, sculptures, etc.) or weapons, or vehicles, etc.
Other Use if the unit of analysis is known, but not found in the list.


Data consisting largely of values expressed as digits from 0 to 9 and, optionally, signs for negative values, decimal points, or letters only when intended to represent numbers (for example, A-F or a-f in hexadecimal).


Data consisting largely of text, including letters, numbers, and special characters or symbols used in writing for punctuation, abbreviation, etc. For example, interview transcriptions, narratives or essays written by study participants, newspaper articles, etc.

still image

Static images, such as graphs, drawings, photographs, diagnostic/medical images like X-rays, etc.


Geospatial data are any type of data with spatial coordinates that allow them to be mapped to the Earth's surface. They can represent physical objects, discrete areas or continuous surfaces. Discrete geospatial data are usually represented using vector data consisting of points, lines and polygons, while continuous geospatial data are usually represented by raster data, consisting of a grid of cells that each has its own value. Any number of applications in a wide range of areas produce geospatial data, such as GIS, Remote Sensing equipment, GPS units, archaeological total stations, manual mapping and computer-aided design (CAD), in a number of formats, including images, vector, text, and tabular data. Vector-based geospatial data include tables listing archaeological sites along with their coordinates, text-based files (e.g. XML) containing coordinates and topology for historic road networks, voting figures for political parties by administrative area. Raster-based geospatial data include satellite images, aerial photographs, scanned maps, and digital maps of elevations, vegetation, land-use, sea surface temperatures, air pollution, soil-types, etc.


Recorded sound, including voice, music, etc.


Moving images. May include films, animation, digital recordings, visual output from simulations, recorded television programs, etc. May be mute or may include synchronized sound.


Computer program(s) in source code (human-readable) or compiled form.

interactive resource

A resource requiring interaction from the user to be understood, executed, or experienced. For example, training modules, query/response portals, files that require action from the user, etc.


Virtual three-dimensional representations of objects, architecture, places, etc.


Use when the kind of data format is known, but not found in the list.

Longitudinal Data collected repeatedly over time to allow studying change in a population. At least some of the questions or modules are repeated over waves. Use the broad term when none of the subterms is suitable.
Longitudinal: Cohort/Event-based Data collected over time from the same cohort of respondents. The individuals in the cohort are connected in some way or have shared some significant experience within a given period. In some cases, the samples may differ between waves but are drawn from the same cohort. Examples: birth year, disease (clinical trials), common problem (intervention studies), education, employment, family formation, participation in an event.
Longitudinal: Trend/Repeated cross-section Data collected from different samples or different groups of people from the same population at several points in time, using at least partly the same set of questions/variables. Conclusions are drawn for the population. Examples: European Social Survey (ESS), national longitudinal crime surveys.
Longitudinal: Panel Data collected over time from, or about, the same sample of respondents. Differs from cohort/event-based data in that the selection of respondents is not based on their being connected in some way or having shared some significant experience.
Longitudinal: Panel: Continuous Data collected from a panel of respondents on a regular basis.
Longitudinal: Panel: Interval Data collected from a panel of respondents only when information is needed.
Time series Data collected repeatedly over time to study change in observations. These are typically "objective" measurements of phenomena that can be observed externally, as opposed to attitudes/opinions or feelings. Examples may include economic/financial indicators, natural/meteorological phenomena, vital statistics, etc.
Time series: Continuous Measurements are taken at every instant in time. Examples: lie detectors, electrocardiograms, etc.
Time series: Discrete Measurements are taken at (usually regularly) spaced intervals. Examples: macroeconomics (weekly share prices, monthly profits, sales); meteorology (hourly temperature); measurements of individuals (blood pressure, weight, height); sociology (crime figures, employment figures), etc.
Cross-section Data collected by observing subjects within the study period, without regard to changes over time. May include more than one collection event. Analysis of cross-sectional data often consists in comparing the differences and similarities among subjects.
Cross-section ad-hoc follow-up Data collected at one point in time to complete information collected in a previous cross-sectional study; the decision to collect follow-up data was not included in the original study design.
Other Use if the time method is known, but not found in the list.
Total universe/Complete enumeration All units (individuals, households, organizations, etc.) of a target population are included in the data collection. For example, if the target population is defined as the members of a trade union, all union members are invited to participate in the study. Also called "census" if the entire population of a regional unit (e.g. a country) is selected.
Probability All units (individuals, households, organizations, etc.) of a target population have a non-zero probability of being included in the sample and this probability can be accurately determined. Use this broader term if a more specific type of probability sampling is not known or is difficult to identify.
Probability: Simple random All units of a target population have an equal probability of being included in the sample. Typically, the entire population is listed in a "sample frame", and units are then chosen from this frame using a random selection method.
Probability: Systematic random A fixed selection interval is determined by dividing the population size by the desired sample size. A starting point is then randomly drawn from the sample frame, which normally covers the entire target population. From this starting point, units for the sample are chosen based on the selection interval. Also known as interval sampling. For example, a company survey seeks a sample of 1,000 employees out of 10,000 total. Beginning with a random starting number, every 10th name from the employee list of the company will be invited to participate in the study.
Probability: Stratified The target population is subdivided into separate and mutually exclusive segments (strata) that cover the entire population. Independent random samples are then drawn from each segment. For example, in a national public opinion survey the entire population is divided into two regional strata: East and West. After this, sampling units are drawn from within each region using simple or systematic random sampling. Use this broader term if the specific type of stratified sampling is not known or difficult to identify.
Probability: Stratified: Proportional The target population is subdivided into separate and mutually exclusive segments (strata) that cover the entire population. In proportional stratified sampling the number of elements chosen from each stratum is proportional to the population size of the stratum when viewed against the entire population. For example, a country is divided into two regional strata that comprise 80 percent (West) and 20 percent (East) of the total population. For a sample of 1,000 people, 800 (i.e., 80 percent) would be drawn from the West and 200 (i.e., 20 percent) from the East to accurately represent their proportion in the total population.
Probability: Stratified: Disproportional The target population is subdivided into separate and mutually exclusive segments (strata) that cover the entire population. In disproportional sampling the number of units chosen from each stratum is not proportional to the population size of the stratum when viewed against the entire population. The number of sampled units from each stratum can be equal,optimal,or can reflect the purpose of the study, like oversampling of different subgroups of the population. For example, a country is divided into two regional strata that comprise 80 percent (West) and 20 precent (East) of the country's population. If equal representation of the two regions is neededin a study, half the sample may be drawn from the Westandhalf from the East, so that each region is represented by 50 percent of the sample. If a more detailed analysis of the population from the East is needed,40 percentof the units may be drawn from the West and60 percentfrom the East, so that the East is over-represented.
Probability: Cluster The target population is divided into naturally occurring segments (clusters) and a probability sample of the clusters is selected. Data are then collected from all units within each selected cluster. Sampling is often clustered by geography, or time period. Use this broader term if a more specific type of cluster sampling is not known or is difficult to identify.
Probability: Cluster: Simple random The target population is divided into naturally occurring segments (clusters) and a simple random sampleof the clusters is selected. Data are then collected from all units within each selected cluster. For example, for a sample of students in a city, a number of schools would be chosen using the random selection method, and then all of the students from every sampled school would be included.
Probability: Cluster: Stratified random The target population is divided into naturally occurring segments (clusters); next, these are divided into mutually exclusive strata and a random sample of clusters is selected from each stratum. Data are then collected from all units within each selected cluster. For example, for a sample of students in a city, schools would be divided into two strata by school type (private vs. public); schools would be then randomly selected from each stratum, and all of the students from every sampled school would be included.
Probability: Multistage Sampling is carried out in stages using smaller and smaller units at each stage, and all stages involve a probability selection. The type of probability sampling procedure may be different at each stage. For example, for a sample of students in a city, schools are randomly selected in the first stage. A random sample of classes within each selected school is drawn in the second stage. Students are then randomly selected from each of these classes in the third stage.
Non-probability The selection of units (individuals, households, organizations, etc.) from the target population is not based on random selection. It is not possible to determine the probability of each element to be sampled. Use this broader term if the specific type of non-probability is not known, difficult to identify, or if multiple non-probability methods are being employed.
Non-probability: Availability The sample selection is based on the units' accessibility/relative ease of access. They may be easy to approach, or may themselves choose to participate in the study (self-selection). Researchers may have particular target groups in mind but they do not control the sample selection mechanism. For example, students leaving a particular building on campus may be approached, or individuals may volunteer to participate in response to invitations that do not target them specifically, but a larger group to which they may belong. Also called "convenience" or "opportunity" sampling.
Non-probability: Purposive Sample units are specifically identified, selected and contacted for the information they can provide on the researched topic. Selection is based on different characteristics of the independent and/or dependent variables under study, and relies on the researchers' judgement. The study authors, or persons authorized by them have control over the sample selection mechanism and the universe is defined in terms of the selection criteria. Also called "judgement" sampling. For example, a medical researcher may intentionally select individuals who are similar in most respects, except on the outcome of the research topic, which can be a specific disease. Some types of purposive sampling are typical/deviant case, homogeneous/maximum variation, expert, or critical case sampling.
Non-probability: Quota The target population is subdivided into separate and mutually exclusive segments according to some predefined quotation criteria. The distribution of the quotation criteria (gender/age/ethnicity ratio, or other characteristics, like religion, education, etc.) is intended to reflect the real structure of the target population or the structure of the desired study population. Non-probability samples are then drawn from each segment until a specific number of units has been reached. For example, if the target population consists of 45 percent females and 55 percent males, a proportional quota sample will have the same gender percentages, while in a non-proportional quota sample the percentages will be different, based on some study-related consideration (for instance, the need to oversample for certain under-represented segments of the population).
Non-probability: Respondent-assisted Sample units are identified from a target population with the assistance of units already selected (adapted from "Public Health Research Methods", ed. Greg Guest, Emily E. Namey, 2014). A typical case is snowball sampling, in which the researcher identifies a group of units that matches a particular criterion of eligibility. The latter are asked to recruit other members of the same population that fulfil the same criterion of eligibility (sampling of specific populations like migrants, etc.).
Mixed probability and non-probability Sample design that combines probability and non-probability sampling within the same sampling process. Different types of sampling may be used at different stages of creating the sample. For example, for a sample of minority students in a city, schools are randomly selected in the first stage. Then, a quota sample of students is selected within each school in the second stage. If separate samples are drawn from the same target population using different sampling methods, the type of sampling procedure used for each sample should be classified separately.
Other Use if the sampling procedure is known, but not found in the list.


A pre-planned communication between two (or more) people - the interviewer(s) and the interviewee(s) - in which information is obtained by the interviewer(s) from the interviewee(s).If group interaction is part of the method, use “Focus group”.

Face-to-face interview

Data collection method in which a live interviewer conducts a personal interview, presenting questions and entering the responses. Use this broader term if not CAPI or PAPI, or if not known whether CAPI/PAPI or not.

Face-to-face interview: CAPI/CAMI

Computer-assisted personal interviewing (CAPI). Data collection method in which the interviewer reads questions to the respondents from the screen of a computer, laptop, or a mobile device like tablet or smartphone, and enters the answers in the same device. The administration of the interview is managed by a specifically designed program/application.

Face-to-face interview: PAPI

Paper-and-pencil interviewing. The interviewer uses a traditional paper questionnaire to read the questions and enter the answers.

Telephone interview

Interview administered on the telephone. Use this broader term if not CATI, or if not known whether CATI or not.

Telephone interview: CATI

Computer-assisted telephone interviewing. The interviewer asks questions as directed by a computer, responses are keyed directly into the computer and the administration of the interview is managed by a specifically designed program.

E-mail interview

Interviews conducted via e-mail, usually consisting of several e-mail messages that allow the discussion to continue beyond the first set of questions and answers, or the first e-mail exchange.

Web-based interview

An interview conducted via the Internet. For example, interviews conducted within online forums or using web-based audio-visual technology that enables the interviewer(s) and interviewee(s) to communicate in real time.

Self-administered questionnaire

Data collection method in which the respondent reads or listens to the questions, and enters the responses by him/herself; no live interviewer is present, or participates in the questionnaire administration. If possible, use a narrower term. Use this broader term if the method is not described by any of the narrower terms - for example, for PDF and diskette questionnaires.

Self-administered questionnaire: e-mail

Self-administered survey in which questions are presented to the respondent in the text body of an e-mail or as an attachment to an e-mail, but not as a link to a web-based questionnaire. Responses are also sent back via e-mail, in the e-mail body or as an attachment.

Self-administered questionnaire: paper

Self-administered survey using a traditional paper questionnaire delivered and/or collected by mail (postal services), by fax, or in person by either interviewer, or respondent.

Self-administered questionnaire: SMS/MMS

Self-administered survey in which the respondents receive the questions incorporated in SMS (text messages) or MMS (messages including multimedia content) and send their replies in the same format.

Self-administered questionnaire: Web-based

Computer-assisted web interviewing (CAWI). Data are collected using a web questionnaire, produced with a program for creating web surveys. The program can customize the flow of the questionnaire based on the answers provided, and can allow for the questionnaire to contain pictures, audio and video clips, links to different web pages etc. (adapted from Wikipedia).

Self-administered questionnaire: Computer-assisted (CASI)

Computer-assisted self-interview (CASI). Respondents enter the responses into a computer (desktop, laptop, Palm/PDA, tablet, etc.) by themselves. The administration of the questionnaire is managed by a specifically designed program/application but there is no real-time data transfer as in CAWI, the answers are stored on the device used for the interview. The questionnaire may be fixed form or interactive. Includes VCASI (Video computer-assisted self-interviewing), ACASI (Audio computer-assisted self-interviewing) and TACASI (Telephone audio computer-assisted self-interviewing).

Focus group

A group discussion on a particular topic, organized for research purposes. The individuals are selected with relevance to the topic, and interaction among the participants is used as part of the method.

Face-to-face focus group

The focus group participants meet in person to conduct the discussion.

Telephone focus group

The focus group discussion is conducted over the telephone.

Online focus group

The focus group discussion is conducted over the Internet in an interactive manner.

Self-administered writings and/or diaries

Narratives, stories, diaries, and written texts created by the research subject.

Self-administered writings and/or diaries: e-mail

Narratives, stories, diaries, and written texts submitted via e-mailmessages.

Self-administered writings and/or diaries: paper

Narratives, stories, diaries, and written texts created and collected in paper form.

Self-administered writings and/or diaries: web-based

Narratives, stories, diaries, and written texts gathered from Internet sources, e.g. websites, blogs, discussion forums.


Research method that involves collecting data as they occur (for example, observing behaviors, events, development of condition or disease, etc.), without attempting to manipulate any of the independent variables.

Field observation

Observation that is conducted in a natural environment.

Participant field observation

Type of field observation in which the researcher interacts with the subjects and often plays a role in the social situation under observation.

Non-participant field observation

Observation that is conducted in a natural, non-controlled setting without any interaction between the researcher and his/her subjects.

Laboratory observation

Observation that is conducted in a controlled, artificially created setting. For example, observing children's play in a laboratory playroom.

Participant laboratory observation

Type of laboratory observation in which the researcher interacts with the subjects and often plays a role in the social situation under observation. For example, observing children's play in a laboratory playroom with the researcher taking part in the play.

Non-participant laboratory observation

Type of laboratory observation that is conducted without any interaction between the researcher and his/her subjects.

Computer-based observation

Type of observation in which data regarding computer usage are being collected by software that can be built into the computer program itself or can be a separate program. Information may be collected about the number of users, the ways in which users interact with the program(s), how much time they spend on a page, how they use specific sections of applications, how they navigate from page to page or from one application to another, etc.


Research method involving the manipulation of some or all of the independent variables included in the hypotheses.

Laboratory experiment

An experiment conducted in a controlled, artificially created physical setting, in which a researcher manipulates one or several independent variables and measures its/their effect on the dependent variable.

Field/Intervention experiment

An experiment conducted in a natural, uncontrolled setting, in which the researcher manipulates one or several independent variables. Intervention/clinical studies are one example of field experiments.

Web-based experiment

An experiment conducted in the virtual setting of the World Wide Web, in which experimental materials are programmed to implement artificial situations or events to be investigated in a distributed environment.


Registering by mechanical or electronic means, in a form that allows the information to be retrieved and/or reproduced. For example, images or sounds on disc or magnetic tape.

Content coding

As a mode of secondary data collection, content coding applies coding techniques to transform qualitative data (textual, video, audio or still-image) originally produced for other purposes into quantitative data (expressed in unit-by-variable matrices) in accordance with pre-defined categorization schemes. For example, coded party manifesto data like the "European Parliament Election Study 2009, Manifesto Study" (doi:10.4232/1.10204)".


Capturing information in writing from a different source, or from a different medium, alphabet, or form of notation, like scientific formulae, or musical notes. For transcribed interviews or observations, it is recommended to document the primary mode of collection, using one of the interview or observation terms.


Collecting and assembling data from multiple, often heterogeneous sources that have one or more reference points in common, and at least one of the sources was originally produced for other purposes. The data are incorporated in a new entity. For example, providing data on the number of universities in the last 150 years using a variety of available sources (e.g. finance documents, official statistics, university registers), combining survey data with information about geographical areas from official statistics (e.g. population density, doctors per capita, etc.), or using RSS to collect blog posts or tweets, etc.


Presentation of information in a condensed form, by reducing it to its main points. For example, abstracts of interviews or reports that are published and used as data rather than the full-length interviews or reports.


Statistics that relate to broad classes, groups, or categories. The data are averaged, totaled, or otherwise derived from individual-level data, and it is no longer possible to distinguish the characteristics of individuals within those classes, groups, or categories. For example, the number and age group of the unemployed in specific geographic regions, or national level statistics on the occurrence of specific offences, originally derived from the statistics of individual police districts.


Modeling or imitative representation of real-world processes, events, or systems, often using computer programs. For example, a program modeling household consumption responses to indirect tax changes; or a dataset on hypothetical patients and their drug exposure, background conditions, and known adverse events.

Measurements and tests

Assessing specific properties (or characteristics) of beings, things, phenomena, (and/ or processes) by applying pre-established standards and/or specialized instruments or techniques.

Educational measurements and tests

Assessment of knowledge, skills, aptitude, or educational achievement by means of specialized measures or tests.

Physical measurements and tests

Assessment of physical properties of living beings, objects, materials, or natural phenomena. For example, findings from hands-on medical examination (e.g., palpation or auscultation), clinical measurements and lab tests like blood analysis, blood pressure, heart rate, body weight and height, as well as general measurements like time, distance, mass, temperature, force, power, speed, GPS data on physical movement and other physical parameters or variables, like geospatial data.

Psychological measurements and tests

Assessment of personality traits or psychological/behavioral responses by means of specialized measures or tests. For example, objective tests like self-report measures with a restricted response format, or projective methods allowing free responses, including word association, sentence or story completion, vignettes, cartoon test, thematic apperception tests, role play, drawing tests, inkblot tests, choice ordering exercises, etc.


Use if the mode of data collection is known, but not found in the list.

Questionnaire Set of pre-determined questions presented to study participants.
Structured questionnaire Set of pre-determined questions, a great majority of which are closed-ended, although there may be a small proportion of open-ended questions.
Semi-structured questionnaire Set of pre-determined questions, a significant proportion of which are open-ended (roughly one third to two thirds), and the rest are closed-ended.
Unstructured questionnaire Set of pre-determined questions, a great majority of which are open-ended, although there may be a small proportion of close-ended questions.
Interview scheme and/or themes Themes, topics, and/or questions used in an interview. Can vary between loosely defined themes to more exactly formulated questions. There is more flexibility than in an unstructured questionnaire regarding which questions are asked of each participant and how they are conveyed.
Data collection guidelines Guidelines and directions that define the content of the data capture. Use a narrower term if possible.
Data collection guidelines: Observation guide Guidelines regarding what will be observed. Depending on the study design, an observation guide can be more or less structured, ranging from exact specifications and scales to loosely formulated ideas.
Data collection guidelines: Discussion guide Guidelines for a group discussion. Depending on the study design, a discussion guide can be more or less structured, ranging from exactly formulated questions to general ideas on what to discuss. For example, a list of topics to be discussed in a focus group, or themes formulated by a researcher to direct a blog discussion, etc.
Data collection guidelines: Self-administered writings guide Guidelines regarding the desired, or expected content of self-written personal accounts or narratives from potential participants. The instructions can be supplied as part of the writing invitation or separately. For example, a writing competition announcement asking people with a life-threatening disease to describe how the disease affects their feelings, social relations and everyday life; or a writing invitation asking people to keep a diary of books read during a period of six months and the thoughts provoked by the books.
Data collection guidelines: Secondary data collection guide Guidelines specifying what data are to be collected from previously existing sources originally created for other purposes. For example, directions on how to select and code data from qualitative sources to create a quantitative dataset.
Participant tasks A description of tasks that participants are asked to carry out as a part of the data collection process. For example, marking places on a map, taking photographs, telling a fairy tale, etc.
Technical instrument(s) Instruments used to collect objective data like measurements, images, etc. For example, chronometers, scales, speedometers, blood pressure monitors, thermometers, x-ray machines, etc.
Programming script Programming script written in a data query language that is used to extract specific data, for instance from online social networks.
Other Use when the type of instrument is known, but not found in the list.
Registers/Records/Accounts Official, formal, or semi-formal documents listing for example items, names, occurences, actions, or results, and preserved in writing or some other permanent form for later reference.
Registers/Records/Accounts: Administrative Information collected on individuals or groups as part of the routine administrative procedures of an agency, business, or institution. Such data are not usually collected with research purposes in mind, may be voluminous, and may require preparation such as coding in order to be usable by researchers. Examples: income tax forms, population registers, naturalization records, birth/death certificates, patent applications, etc.
Registers/Records/Accounts: Historical Historical records preserve information and constitute evidence about past events.They may be produced by individuals, groups, or organizations. Administrative records become historical when they are no longer retained, or actively used by the issuing agency for their original purpose. Examples include parish registers, estate records, wills, chronicles, etc.
Registers/Records/Accounts: Legal Records pertaining to law and its administration, for example records related to cases that have been brought to court or to a tribunal.
Registers/Records/Accounts: Medical/Clinical Health-related data created or collected by health care professionals about a patient. Usually include the results of medical tests or measurements, findings from consultations or clinical trial programs, etc.
Registers/Records/Accounts: Academic/Aptitude Information gathered during an evaluation process and presented as results. Examples include educational tests, IQ tests, verbal or logical reasoning tests, competence tests for professional occupations, etc.
Registers/Records/Accounts: Economic/Financial Records of the financial activities of a business, person, state institution or other organizations or entities. Examples are statements of retained earnings, cash flow, income statements, a company’s balance sheet and tax return.
Registers/Records/Accounts: Personal Records or accounts created unofficially by individuals or families for other purposes than research. Examples may include private diaries or memoirs, family record books or Bibles, collections of personal documents, photographs, etc.
Registers/Records/Accounts:Voting resultsl Details of votes cast for candidates in an election (also known as "election returns/results"),parliamentary or organizational votes on policies, motions or proposals,public referendums, etc.
Events/Interactions Events are usually one-time, individual occurrences, with a limited or short duration. An event may be listed as data source when it is directly observed or recorded for research. Interactions are events in which two or more people, groups, objects or systems act upon one another having reciprocal influence, or effect. Examples: types of gatherings (ceremonies, competitions, festivals, meetings), riots, terrorist attacks, computing events (i.e., actions or occurrences detected by computer programs), etc.
Processes Processes are sequences of occurrences, events, activities, actions or operations that take place over time and bring about changes or transformations in organisms, objects, ideas or social phenomena. For example, a business process may include receiving orders, invoicing, shipping the products, or setting a marketing budget.
Processes: Workflow(s) Sequence of steps and processes through which a piece of work passes from initiation to completion (adapted from the Oxford dictionary online: http://www.oxforddictionaries.com/us/definition/american_english/workflow). Examples from data life cycle: data collection, data processing, data analysis, data archiving, etc.
Communications Messages resulting from the act or process of using words, sounds, signs, or behaviors to convey or exchange information, ideas, thoughts, feelings, etc. (adapted from www.merriam-webster.com).
Communications: Public Communications addressed directly to a public audience, for example, in person (public gatherings, political rallies, etc.), by means of broadcast, print or Internet mass media (radio, television, print or online newspapers/journals), by means of billboards, banners or other signage placed in public view, or social media (public postings on Facebook, Twitter, and others).
Communications: Interpersonal Communications made by an individual to another individual or a private group of persons, for purposes other than research. For example emails, letters, telephone conversations, social media postings with limited access.
Research data Pre-existing data; data that have already been collected and/or used for a different research project.
Research data: Published Pre-existing data that have been made available to the general public, or sections thereof.
Research data: Unpublished Pre-existing data that have not been made available to the general public, or sections thereof.
Population group Group of individuals that can be defined by one or several common characteristics: ethnicity, race, gender, age range, geographic location or distribution, level of education, income level or economic status, professional status, state of health or medical conditions, or belonging to specific communities (e.g., special interest groups, or social media), or networks, etc.
Geographic area An area of the Earth, demarcated for the purposes of administration, politics, environment, etc. The demarcation is identifiable via coordinates or other systems used to identify position precisely.
Physical objects Natural or man-made entities with spatial locations. For instance, works of art, constructions, rock samples, machines, etc. These are considered data sources if the data describe the physical characteristics of the given object rather than any information encoded in it.
Biological samples Biological materials collected from living organisms, including, for example, biological specimens of human or animal organs, cells or tissues such as hair, muscle or tumor tissue, bodily fluids such as blood, urine, saliva, extracted material such as DNA and RNA, microorganisms, plant matter, etc. The source of the data are the samples themselves, not measurements and/or other tests applied to them.
Other Use when the data source is known, but not found in the list.

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Social Science Data Archives. YEAR. 4. Prepare the Study Description. Accessed: http://adp.fdv.uni-lj.si/eng/deli/postopek/opis_raziskave/ (DD. month year).

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ADP is part of the Social Sciences Research Institute of the Faculty of Social Sciences. The Slovenian Research Agency provides funding of the ADP within the infrastructure program "Network of Research and Infrastructural Centres" The ADP is a member of the umbrella organization of the European Social Science Data Archives CESSDA ERIC. © ADP (ISSN 2385-9415) | 1997 - 2017 | arhiv.podatkov@fdv.uni-lj.si