PREPARING RESEARCH DATA FOR OPEN ACCESS 
Guide for data producers 
Janez Štebe, Sonja Bezjak, Irena Vipavc Brvar 
PREPARING RESEARCH DATA FOR OPEN ACCESS 
Guide for data producers 
Janez Štebe, Sonja Bezjak, Irena Vipavc Brvar 
Arhiv družboslovnih podatkov 


Janez Štebe, Sonja Bezjak, Irena Vipavc Brvar 

Preparing research data for open access 
Guide for data producers 

Publisher: Faculty of Social Sciences, Založba FDV 

Ljubljana 2015 


Copyright ©
This work of the following authors Janez Štebe, Sonja Bezjak, Irena Vipavc Brvar 
is licensed under a Creative Commons Attribution 4.0 International License. 


Prepared by: Arhiv družboslovnih podatkov 


(Social Science Data Archives) 
Language editing: Stuart MacdonaldBook editing: Medium Žirovnica 
Access mode (URL): http://knjigarna.fdv.si 
URN:NBN:SI:doc-G0DPXMZ1 

CIP - Kataložni zapis o publikaciji 
Narodna in univerzitetna knjižnica, Ljubljana 

001.891:004.6(0.034.2) 

ŠTEBE, Janez 

 Preparing research data for open access [Elektronski vir] : guide for data 
producers / Janez Štebe, Sonja Bezjak, Irena Vipavc Brvar. - El. knjiga. - Ljubljana 
: Faculty of Social Sciences, Založba FDV, 2015 

ISBN 978-961-235-722-1 (pdf) 

1. Bezjak, Sonja 2. Vipavc Brvar, Irena 
Releasing this guide was financially supported by the FOSTER project. 


TABLE OF CONTENT 

1 Reasons for open access 1 

1.1 Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 
1. 2 Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 
2 How to participate in the open access 3 

2.1 Managing research data 
at the planning and creation stage . . . . . . . . . . . . . . . 3 
2.1.1 Quality of study . . . . . . . . . . . . . . . . . . . . . . . . . 4 
2.1.2 Ethical obligations . . . . . . . . . . . . . . . . . . . . . . . 4 
2.1.3 Digital curation . . . . . . . . . . . . . . . . . . . . . . . . . 6 
2.1.4 Supporting research 
data management planning . . . . . . . . . . . . . . . . 7 
2.2 Depositing data with a data centre for preservation . . . 8 
2.2.1 WHERE: selection of data centre . . . . . . . . . . . . . 8 
2.2.2 WHY choose ADP? . . . . . . . . . . . . . . . . . . . . . . 9 
2.2.3 HOW to deposit research data . . . . . . . . . . . . . . 10 
2.2.4 Research data acquisition stage. . . . . . . . . . . . . 11 
2.3 Data publication . . . . . . . . . . . . . . . . . . . . . . . . . . 12 
2.3.1 Access to research data . . . . . . . . . . . . . . . . . . . 12 
2.3.2 Advantages of acknowledging 
data as a scientific publication. . . . . . . . . . . . . . 13 
2.3.3 How to participate in promoting data use . . . . . . 15 
3 Further support 16 
Appendix: The DSA Guidelines 2014-2015 17 


1 In exceptional cases e.g. to protect 
the identity of human subjects, 
special or more restricted access 
conditions are set. 

2 Štebe, Janez, Sonja Bezjak and 
Sanja Lužar (2013): Odprti podatki. 
Načrt za vzpostavitev sistema 
odprtega dostopa do raziskovalnih 
podatkov v Sloveniji [OPEN DATA – 
Action Plan for the Establishment 
of a System of Open Access to 
Publicly Funded Research Data 
in Slovenia]. Ljubljana: Fakulteta 
za družbene vede, Založba FDV. 
[http://www.adp.fdv.uni-lj.si/o_arhivu/
publikacije/odprti_podatki_
zakljucno_porocilo/], p. 20. 

3 It is difficult to predict all potential 
motives for future reuse 
of data. Taking into account the 
whole spectrum of possible research 
problems, use of data could 
include anything from practical, 

1 REASONS FOR OPEN ACCESS 

1 1 Principles 

Open access to research data means that by default1 data can be accessed on equal terms and used with minimal 
restrictions for academic research and teaching purposes and beyond. Research data constitute primary 
sources that underpin scientific research and enable derivation of theoretical or applied findings. Data should 
be prepared for open access in a form which would enable future users to assess and understand them for the 
purposes of reuse.2 

There are a number of benefits for supporting open access to research data, the main one being their value to 
other researchers beyond the original purpose of creation. 

Value and importance of data 

• Are the data unique? Can the study or experiment be repeated? Does it rep-
could be evaluated by the follow-
resent an observation in time that cannot be recollected and reproduced, or 

ing criteria: 

does it have historical or cultural value? 

• 
Is creating data costly or time consuming? Are procedures, knowledge and 
instruments used of limited availability or do they represent a rare implementation 
and therefore have greater re-usability for future research? 
• 
Are data accompanied by research publications and are thus important to 
verify and reproduce the research process and methodologies? 
Establishing whether data are 
useful for somebody else means 
evaluating their applicability for 
solving a certain problem. This 
recognition represents the practical 
basis of information literacy 
and as such we ask the following: 
• Is there a potential problem or set of problems which could be solved by 
using the research data? Is there any data demand expected? 3 
• Could data be located and accessed in a way that a certain problem could be 
solved? 
• Are data properly documented so that users are able to use them appropriately? 
• Are the data available in a preservation format that will enable reuse by 
software and processing tools? 
applied to theoretical or indeed 
serendipitous research. 


1 2 Benefits 

The benefits of open access to research data can be divided into the following: 

Benefits for 

• Future reuse of data by data creators themselves is made easier if data are properly documented 
data creators: 
and preserved. 

• Indirect benefits for data creator’s academic reputation and career development include: increased 
citation counts and wider dissemination of their research findings; data may be formally 
assessed for scientific excellence and form part of researcher’s bibliography thus adding points to 
the score of scientific excellence. 

Benefits for 
the scientific 
community: 
• New research findings which can only be achieved by using and combining available data from 
multiple sources, e.g. studies of trends or international comparative research, studies of rare or 
small populations, meta-analysis. 
• More robust research findings can be derived as a result of validating and through further analysis 
based on data related to publication. 
• Increasing the number of findings by enhancing the number of users of the same data, with efficiencies 
gained through removal of duplication of effort and/or the need to repeat raw data collection 
due to a shortage of funds and time. 
• Training of future scientists, using research data for teaching purposes. 
Benefits for 

• Research findings based on existing data on certain topics can improve quality of life; in Social 
the public: 

Sciences gaining a better understanding of the community is important, including building collective 
identity and eliminating prejudice, discrimination, inequality etc. 

• Open access to data also introduces savings relating to public spending on research and education. 
An increasing number of research funders, representatives of the scientific community, and the public recognise 
the importance and benefits of open access to data. They have in common the principle that research data 
produced by publicly-funded research are a public good.4 

When we think about depositing data for open access, the aforementioned benefits should be taken into account. 
It is also important to consider whether open access is required by the research funder 5, or if there are 
ethical obligations, disciplinary codes of practice, institutional policies or a requirement of journal publishers to 
make available those data associated with the published article.6 

4 OECD (2007): OECD Principles 
and Guidelines for Access 
to Research Data from Public 
Funding. [http://www.oecd.org/ 
sti/scienceandtechnologypolicy/ 
oecdprinciplesandguidelinesforaccesstoresearchdatafrompublicfunding.
htm]. 

Research Councils UK: RCUK 
Common Principles on Data Policy. 
[http://www.rcuk.ac.uk/research/ 
datapolicy/, 21. 1. 2015]. 

LERU Research Data Working 
Group (2013): LERU Roadmap for 
Research Data. Advice paper, no. 

14. [http://www.leru.org/files/ 
publications/AP14_LERU_Roadmap_
for_Research_data_final.pdf]. 
Science Europe: Working Group 
on Research Data. [http://www. 
scienceeurope.org/policy/working-
groups/Research-Data, 21. 1. 
2015]. 

5 Usually one of the incentives 
for open access is also respecting 
funder’s policies. 

6 Scientific journals increasingly 
require open access to data. It has 
value as a version of data, cited by 
the article – for the purposes of 
verification or replication of results. 


7 Corti, Louise (2012): Evaluating 
Research Data. On: Managing 
the Material: Tackling Visual Arts 
as Research Data. [http://www. 
data-archive.ac.uk/media/369163/ 
managing_research_data14sept2012b.
pdf]. 

2 HOW TO PARTICIPATE IN THE OPEN ACCESS 

In terms of facilitating open access from the beginning of a project, the basic strategy of research data management 
planning and actual research data construction is to actively address two objectives. Firstly, to assure and 
enhance the usability of data for the purposes of the original project, while having in mind the perspective of 
further reuse, and secondly attending to the enhanced usability for a wider set of purposes and possible users. 
A study could be of high quality, yet the further reuse potential of resulting data may be low.7 In the case of 
quantitative data, a dataset may include a narrow set of variables which would limit a theoretical set of possible 
analysis. A multi-thematic study for example with a more diverse conceptualization and with an emphasis on 
high quality would be better value and have greater research potential for more users. 
For the purpose of providing access to high quality data to the wider research community, it is necessary to 
start proper research data management planning early to avoid significant problems later in the data creation 
phase. This includes care for quality of conceptualization, sampling and establishing a protocol for data collection, 
care during collection and creation of data, and finally the preparation of data for analysis. It is important 
to take care with on-going and final contextual documentation of data as well as preparation of metadata for 
deposition in a domain data centre, archive or data repository. Furthermore, ethical obligations, selection and 
appraisal of data with long-term value for preservation should be taken into account. Such efforts result in an 
enhanced data publication, available in a data centre, citeable as a scientific reference by users in future papers 
and publications. 

2 1 Managing research data at the planning and creation stage 

A basic assurance of data quality and future usability is planning and creating research data according to disciplinary 
standards and good practices, as well as respecting ethical and legal obligations. Research data creators 
have to ask themselves about what can be done to assure usability of the data even after the end of the project. 


2.1.1 Quality of study 
One of the main objectives of the researcher should be the generation of high quality data throughout the entire 
research process.8 This includes: 

Care for quality of 
conceptualization, 
measurement, sampling 
and creation of a data 
collection protocol 

Care for documentation 
of data and preparation 
of metadata for deposition 
in a data centre, 
archive or repository 

Using well-accepted disciplinary concepts and methodologies with references in publications, 
a standardised approach to measuring individual concepts, applying higher number of 
indicators and a wide set of socio-demographic questions. Introduction of random sampling 
covering the whole population, attention to sample size, adoption of measures to achieve high 
response rates. Use of existing survey questions, standard classifications, and a good practice 
to pretest a questionnaire.9 

Preparing metadata according to the DDI11 standard or appropriate structured documentation 
which would enable transformation to DDI Codebook - including descriptions of the study, 
variables, files and related materials such as questionnaires or qualitative interview protocols, 
data entry forms, codebooks, study reports etc. 

Care for collection, creation 
and preparation of 
data for analysis 
Using procedures for data collection, follow instructions and forms, e.g. computer assisted 
interviewing with conditional routes, range of values and logical coherency checks. Verification 
and cleaning of data, error correction, adding variable descriptions and value labels which are 
coherent with the questionnaire, verification of qualitative interview transcript entries etc. 
Writing notes and field work control, collecting information about reasons for non-response, 
calculating response rates, collecting paradata.10 
8 See e.g. Arnež, Marta et. all (2012): 
Smernice za zagotavljanje kakovosti 
[Quality Guidelines for Official 
Statistics]. Metodološki priročniki, 
no. 2. Ljubljana: Statistični urad 
Republike Slovenije. [http://www. 
stat.si/doc/pub/Smernice.pdf]. 

9 Hoffmeyer-Zlotnik, Jürgen H. P. 
and Uwe Warner (2012): Demographic 
Standards for Surveys 
and Polls in Germany and Poland: 
National and European Dimension. 
Köln: GESIS - Leibniz-Institut 
für Sozialwissenschaften. 
[http://nbn-resolving.de/urn:nbn:
de:0168-ssoar-371202]. 

10 UKDA: Create and Manage Data: 
Formatting Your Data: Quality 
assurance. [http://www.data-archive.
ac.uk/create-manage/format/ 
quality, 20. 1. 2015]. 

DASISH: Publications and presentations. 
[http://dasish.eu/publications/
presentations/, 20. 1. 2015]. 

2.1.2 Ethical obligations 
Social Sciences deal primarily with data about individuals and other potentially sensitive or disclosive data. As 
part of responsible research practice we need to think about how to protect the privacy of research subjects 
throughout the whole research lifecycle, starting with planning and ending with publishing data in an open access 
environment. Researchers are obliged to work in accordance with the Personal Data Protection Act,12 as well 
as respecting research community codes.13 Ethical codes recommend to protect participants against possible 
harm or distress, assuring participation by obtaining informed consent, and respecting disciplinary methodological 
standards. 

11 DDI is a metadata specification 
for Social Sciences. See: DDI Alliance 
[http://www.ddialliance.org/, 

20. 1. 2015]. 
12 Ministry of Justice of the Republic 
of Slovenia (2013): Personal 
Data protection act of the Republic 
of Slovenia. [https://www.ip-rs.si/ 
fileadmin/user_upload/doc/ZVOP1_
in_ZVOP-1a__English_/Personal_
Data_Protection_Act_of_Slovenia_
status_2013_final_eng.doc]. 

13 › 


5Before the start of any research 
project the following 
need to be considered: 
How the collected data will be used? 
How the results will be presented? 
Who will have the access to the data? 
How the research data will be managed after the project is complete? 
Any participant in a research project has to agree to participate. Consent could be given in a written or a verbal 
form. Special attention should be paid to the preparation of the informed consent form and accompanying information 
sheet when conducting qualitative interviews, creating audio- and video content, or when research 
involves sensitive subjects and groups e.g. children, medical studies, crime and workplace studies. 
A participant has to be 
informed about the following: 
General information about the project. 
Participation is voluntary and that the participant may withdraw their consent at any time. 
Measures taken to maintain confidentiality including use of pseudonyms, indirect identifiers, 
data anonymization, disclosure control etc. 
Potential uses of any collected data. 
It is important from the perspective of open access to data that the participants are informed about the planned 
dissemination, storage and sharing of data.14 
We could use phrases 
such as: 
I agree that the data deposited will be preserved and made accessible in the Social Science 
Data Archives. 
I understand that other (secondary) users could use the data in their analysis and publications, 
if they agreed to preserve the confidentiality of individuals and institutions recorded 
in the materials. 
Efficient and carefully prepared information about responsible management of data throughout the whole 
data lifecycle could enhance the trust of participants. They would perceive the research having rigour and integrity 
and perhaps be more motivated to participate. 
13 Univerza v Ljubljani (2014): 
Etični kodeks za raziskovalce 
Univerze v Ljubljani [Code of Ethics 
for Researchers at University of 
Ljubljana]. [http://www.uni-lj.si/ 
mma/Etični kodeks za_raziskovalce 
UL/20141211104120/]. 
European Science Foundation, 
ALLEA (2011): The European Code 
of Conduct for Research Integrity 
[http://www.esf.org/fileadmin/ 
Public_documents/Publications/ 
Code_Conduct_ResearchIntegrity. 
pdf]. 
Slovensko sociološko društvo 
(1992): Kodeks profesionalne etike 
SSD [Code of Professional Ethics of 
Slovene Sociological Association]. 
[http://www.sociolosko-drustvo. 
si/wp-content/uploads/2012/09/ 
Kodeks_profesionalne_etike_SSD19921.
pdf]. 
Statistično društvo Slovenije 
(1991): Deklaracija poklicne etike 
Statističnega društva Slovenije 
[Declaration on Professional Ethics 
of Statistical Society of Slovenia. 
[http://www.stat-d.si/images/files/ 
etika.doc]. 
14 ICPSR: Recommended Informed 
Consent Language for Data Sharing. 
[http://www.icpsr.umich.edu/ 
icpsrweb/content/datamanagement/
confientiality/conf-language. 
html, 21. 1. 2015]. 
5Before the start of any research 
project the following 
need to be considered: 
How the collected data will be used? 
How the results will be presented? 
Who will have the access to the data? 
How the research data will be managed after the project is complete? 
Any participant in a research project has to agree to participate. Consent could be given in a written or a verbal 
form. Special attention should be paid to the preparation of the informed consent form and accompanying information 
sheet when conducting qualitative interviews, creating audio- and video content, or when research 
involves sensitive subjects and groups e.g. children, medical studies, crime and workplace studies. 
A participant has to be 
informed about the following: 
General information about the project. 
Participation is voluntary and that the participant may withdraw their consent at any time. 
Measures taken to maintain confidentiality including use of pseudonyms, indirect identifiers, 
data anonymization, disclosure control etc. 
Potential uses of any collected data. 
It is important from the perspective of open access to data that the participants are informed about the planned 
dissemination, storage and sharing of data.14 
We could use phrases 
such as: 
I agree that the data deposited will be preserved and made accessible in the Social Science 
Data Archives. 
I understand that other (secondary) users could use the data in their analysis and publications, 
if they agreed to preserve the confidentiality of individuals and institutions recorded 
in the materials. 
Efficient and carefully prepared information about responsible management of data throughout the whole 
data lifecycle could enhance the trust of participants. They would perceive the research having rigour and integrity 
and perhaps be more motivated to participate. 
13 Univerza v Ljubljani (2014): 
Etični kodeks za raziskovalce 
Univerze v Ljubljani [Code of Ethics 
for Researchers at University of 
Ljubljana]. [http://www.uni-lj.si/ 
mma/Etični kodeks za_raziskovalce 
UL/20141211104120/]. 
European Science Foundation, 
ALLEA (2011): The European Code 
of Conduct for Research Integrity 
[http://www.esf.org/fileadmin/ 
Public_documents/Publications/ 
Code_Conduct_ResearchIntegrity. 
pdf]. 
Slovensko sociološko društvo 
(1992): Kodeks profesionalne etike 
SSD [Code of Professional Ethics of 
Slovene Sociological Association]. 
[http://www.sociolosko-drustvo. 
si/wp-content/uploads/2012/09/ 
Kodeks_profesionalne_etike_SSD19921.
pdf]. 
Statistično društvo Slovenije 
(1991): Deklaracija poklicne etike 
Statističnega društva Slovenije 
[Declaration on Professional Ethics 
of Statistical Society of Slovenia. 
[http://www.stat-d.si/images/files/ 
etika.doc]. 
14 ICPSR: Recommended Informed 
Consent Language for Data Sharing. 
[http://www.icpsr.umich.edu/ 
icpsrweb/content/datamanagement/
confientiality/conf-language. 
html, 21. 1. 2015]. 

6In general, to decrease the 
disclosure risk, data should 
be processed in the following 
ways: 
Direct identifiers should be removed (e.g. names, addresses, telephone numbers and other 
personal identifiers such as personal identification number). 
Indirect identifiers should be statistically protected (such as detailed geographic location, 
detailed description of work place, precise dates). 
By following the aforementioned safeguards both user and participant can be confident that data is not disclosive 
whilst still remaining useful for the majority of research purposes. If needed, the researcher could prepare 
two data files: one with a lower level of data protection to be used for advanced scientific use and available to 
registered researchers under more strict use conditions; and the second one with a higher level of protection, 
suitable for a wider range of users. 
2.1.3 Digital curation 
Digital curation represents a challenge for data creators to preserve the authenticity and provenance of research 
data during the project and after it ends. That is to assure permanent usability of data and transparency of the 
data generation process. Some practical recommendations for responsible data management throughout the 
project are presented below: 
Thinking 
about appropriate 
organization 
of materials: 
Systematic and intuitive naming and re-naming of files and variables. 
Data formats and software used. 
File transfers, file sharing and remote access. 
File version control. 
Actions: 
Manage backups. 
Prepare contextual documentation and metadata. 
Define access conditions for digital materials. 
Make appropriate provisions to prevent unauthorized access.15 
15 UK Data Service (2014): Benefits 
of managing and sharing research 
data. Colchester: University of 
Essex. [http://ukdataservice.ac.uk/ 
media/440285/whysharedata.pdf]. 
6In general, to decrease the 
disclosure risk, data should 
be processed in the following 
ways: 
Direct identifiers should be removed (e.g. names, addresses, telephone numbers and other 
personal identifiers such as personal identification number). 
Indirect identifiers should be statistically protected (such as detailed geographic location, 
detailed description of work place, precise dates). 
By following the aforementioned safeguards both user and participant can be confident that data is not disclosive 
whilst still remaining useful for the majority of research purposes. If needed, the researcher could prepare 
two data files: one with a lower level of data protection to be used for advanced scientific use and available to 
registered researchers under more strict use conditions; and the second one with a higher level of protection, 
suitable for a wider range of users. 
2.1.3 Digital curation 
Digital curation represents a challenge for data creators to preserve the authenticity and provenance of research 
data during the project and after it ends. That is to assure permanent usability of data and transparency of the 
data generation process. Some practical recommendations for responsible data management throughout the 
project are presented below: 
Thinking 
about appropriate 
organization 
of materials: 
Systematic and intuitive naming and re-naming of files and variables. 
Data formats and software used. 
File transfers, file sharing and remote access. 
File version control. 
Actions: 
Manage backups. 
Prepare contextual documentation and metadata. 
Define access conditions for digital materials. 
Make appropriate provisions to prevent unauthorized access.15 
15 UK Data Service (2014): Benefits 
of managing and sharing research 
data. Colchester: University of 
Essex. [http://ukdataservice.ac.uk/ 
media/440285/whysharedata.pdf]. 

16 Central specialised information 
centres: Research infrastructure. 
[https://www.arrs.gov.si/en/infra/ 
osic/predstavitev.asp, 21. 1. 2015]. 

17 Slovenian Current Research 
Information System. [http:// 
www.sicris.si/public/jqm/cris. 
aspx?lang=eng&opdescr=home, 

21. 1. 2015]. 
18 DCC: Overview of funders’ 
data policies. [http://www.dcc. 
ac.uk/resources/policy-and-legal/ 
overview-funders-data-policies, 

21. 1. 2015]. 
European Commision (2013): 
Guidelines on Data Management 
in Horizon 2020. [http://ec.europa.
eu/research/participants/ 
data/ref/h2020/grants_manual/ 
hi/oa_pilot/h2020-hi-oa-datamgt_
en.pdf]. 

2.1.4 Supporting research data management planning 
Planning and preparing data for open access consists of a range of research data management processes as 
detailed above to maximise data quality, working in accordance to ethical requirements and effective digital 
curation procedures. Data management plans (DMP) are fast becoming established as the formal obligation in 
response to funder or research institution requirements. They aim to deal with all aspects in relation to research 
data throughout the project and their eventual deposition in open access solutions at the end of the project. 
Support services are available to help design the DMP and to implement it. The primary reference point for 
support would be the domain data centre, archive or data repository, supplemented with support from a range 
of stakeholders including: 

Research 

• Assures and manages internal open access policies and designs procedures to help research pro-
institution: 
jects with the preparation and implementation of DMPs. 

• Manages expert training for researchers and support staff. 
• Provides infrastructure in the form of technological and advisory services to provide digital preservation 
for data throughout the lifecycle (research offices, libraries, CSIC,16 SICRIS,17 operating data 
centre and service networks). 
• Provides common services and tools to support research groups. 
Library: • Provides information about the availability of existing data sources. 
• Provides information about options to deposit data in a data centre or data archive. 
• Helps select an appropriate or recommended data centre or data archive. 
• Provides information about open access conditions and advantages. 
• Supports preparation of formal DMPs. 
• Provides support with preparation of basic study metadata and documentation, author’s rights, 
and explains other deposition requirements. 
Funder: 

• Manages national/disciplinary policies which require the preparation of DMPs as part of the research 
project application process, based on the principles of open access to research data financed 
by public funds, perceived as being a public good. 18 
• Acknowledges costs for open access data and metadata preparation and provides funds to cover 
them. 
• Monitors implementation of open access obligations. 

2 2 Depositing data with a data centre for preservation 
82 2 Depositing data with a data centre for preservation 
2.2.1 WHERE: selection of data centre 
The decision about choosing which data centre or archive to use for the deposit and future availability of research 
data should be made in the planning phase. It makes sense to contact a data centre at the beginning 
of the project and to become familiar with the requirements that need to be met for acquisition. Formal DMP 
forms, required by most funders, include an item about the place of deposit. Some funders have the recommended 
place of deposit already set in their policies. Usually this is the national disciplinary data centre.19 Projects 
funded by Horizon 2020 also encourage participants of the Open Research Data Pilot to offer their data to 
an established research data centre.20 
When choosing an appropriate 
data centre the acquisition policy, 
requirements of the chosen 
data service provider, and the 
advantages of depositing data 
should be understood. Attention 
should be paid to the following 
detail: 
• How is the mission of the data centre specified? How is the user community 
specified? 
• What kind of data are acquired? 
• Is the centre actively involved in digital curation and does it provide data access 
to a specified user community? 
• What are the criteria for selection and how is the selection and acquisition 
process specified? What are the technical characteristic requirements? 
• How do they solve legal and ethical issues related to privacy protection and 
Intellectual property rights? 
19 E.g. ESRC from Great Britain 
recommends UK DS, which is a 
partner organization to the Slovenian 
ADP. 
Economic & Social Research 
Council (2013): ESRC Research Data 
Policy. [http://www.esrc.ac.uk/_images/
Research_Data_Policy_2010_ 
tcm8-4595.pdf], p. 6. 
20 E.g. catalogues of the following 
data centres could be of some 
help: Registry of Research Data 
Repositories [http://www.re3data. 
org/, 21. 1. 2015] and Databib 
[http://databib.org/, 21. 1. 2015]. 

2.2.2 WHY choose ADP? 
The disciplinary data centre services for Social Sciences are in Slovenia provided by the Social Science Data Archives 
(ADP – Arhiv družboslovnih podatkov). The advantages of depositing data to the ADP are, among others, 
the following: 

ADP evaluates the importance of 

Acquired data are acknowledged as a scientific publication in their own right 
research data for science and their 


and represent a basis for quantitative assessments of scientific excellence in 
long-term usability. 


accordance to the criteria of the Slovenian Research Agency.21 

Adopts an acknowledged digital 
curation approach. 
ADP follows the approach of data centres in the field of long-term preservation 
of data, in accordance with the international reference model OAIS22 and principles 
of DSA.23 
21 ARRS (2014): Rules on the Procedures 
of the (co)financing and 
Monitoring of Research Activities 
Implementation. [https://www. 
arrs.gov.si/en/akti/prav-sof-ocensprem-
razisk-dej-sept-11.asp]. 

22 OAIS is an ISO-standard which 
provides a functional frame for 
preserving digital objects in data 
centres. See: OAIS-Based Processes 
[http://www.icpsr.umich.edu/icpsrweb/
content/datamanagement/ 
lifecycle/oais.html, 21. 1. 2015]. 

23 Data Seal of Approval: The 
Guidelines 2014 – 2015. [http:// 
www.datasealofapproval.org/ 
en/information/guidelines/, 21. 

1. 2015]. 
Provides access to data and enables 

ADP provides advice and training to their users. Data made available in the 

searching and browsing through 

catalogue represent a basis for citation in reference lists. Registered users are 

standard data descriptions for the 

obliged to make reference to the data in their publication. Users are instructed 

purposes of discovery. 

about how to cite data at the point of access. 

Offers support with data management 
planning and preparation of 
data for open access. 
ADP is actively involved both nationally and internationally in the field of 
opening up research data. Based on the experience and demands, ADP offers 
RDM counselling and assists users with preparing data for open access. 

2.2.3 HOW to deposit research data 
Depositing research data with ADP is not necessarily a singular activity, but normally involves the mutual exchange 
of information through negotiation about those details required to fulfil the data acquisition process. 
ADP provides counselling, instructions and tools which make data preparation and deposition processes easier. 
Researchers who want to store their research data in the ADP should follow the steps listed below: 

1) Make sure that the 

• 
The richness of content in terms of adequacy of conceptualization, suitability and potendata 
satisfy the criteria 

tial for use, and thematic broadening of the ADP catalogue should be evaluated. 
for acquisition.24 

• 
It is important that methodologies are transparent and of the highest quality, accompanied 
by complete and valid data and documentation to enable further analysis. 
• 
The depositor, as a copyright owner, is willing to deposit data with ADP for dissemination. 
2) Researchers can 
propose data for deposition 
using the »Acquisition 
Proposal«.25 
The entry form is available for short descriptions of study content and its methodological 
characteristics. The information provided enables an assessment of the quality of data and 
their suitability for the acquisition. 
24 ADP: ADP study classification 
by relevance. [http://www.adp. 
fdv.uni-lj.si/eng/za_uporabnike/
o_arhiviranju/klasifikacija_ 
adp_pomembnosti/, 21. 1. 2015]. 

25 ADP: Acquisition Proposal. 
[http://www.adp.fdv.uni-lj.si/eng/ 
evidentiranje, 21. 1. 2015]. 

26 ADP: License Agreement. 
[http://www.adp.fdv.uni-lj.si/eng/ 
za_dajalce/izjava_o_izrocitvi/, 

21. 1. 2015]. 
3) The depositor fills 
in the »Licence Agreement
«,26 in which deposited 
materials are 
listed and data access 
conditions specified. 

• 
The researcher who has author’s rights to the data approves the deposition with the Archives, 
devolving future responsible management of data and their onward distribution. 
• 
He/she guarantees the authenticity and the legal rights of the data (i.e. intellectual property 
rights, privacy protection). 
• 
By default ADP gives the depositor an option to choose between two licenses: Creative 
Commons Attribution alone (CC BY) and Creative Commons Attribution + Non-commercial 
(CC BY-NC). 
• 
The depositor specifies any exceptions in access conditions (certain research data could 
have limited or controlled access, e.g. sensitive data, restricting access for a certain reasonable 
period of time). 
4) The researchers fill 
in the »Study Description 
Form«27 with the 
following information: 
• Data creation and data collector. 
• Funder of the project (public or private, including project or grant ID number). 
• Detailed description of the research including methodology (sample, population, data 
collection time frame, response rate etc.). 
27 Study description could be 
prepared in a common text 
editor or using a special tool. For 
that purpose ADP suggests using 
Nesstar Publisher tool using the 
pre-prepared template. 

ADP: Study Description Form. 
[http://www.adp.fdv.uni-lj.si/ 
eng/o_arhivu/interaktivno/ 
obrazec_opis_raziskave/, 21. 1. 
2015]. 

Nesstar Publisher [http://www. 
nesstar.com/software/publisher. 
html, 21. 1. 2015]. 

ADP: ADP’s template for Nesstar 
Publisher. Training. [http://www. 
adp.fdv.uni-lj.si/za_uporabnike/ 
usposabljanje/, 21. 1. 2015]. 


115) The researcher prepares 
clear and concise 
documentation and 
any other ancillary 
materials about the 
data for deposition in 
the Archive. 
• The data should be provided in electronic form accompanied by descriptive information 
such as file size, format, number of variables and units, code definitions etc.28 
• The materials should be prepared respecting archival instructions and addressing recommendations 
about formats. 
• The depositor should guarantee provisions have been taken to protect personal data. All 
direct identifiers should be removed. 
• Materials which help understand and verify the content of data should also be attached: 
e.g. codebooks, frequency files, instructions for interviewers, information about the 
implementation of the study, links to study reports or their copies if not being publically 
available. Both electronic and printed versions of the questionnaire in the original form 
should be attached. 
2.2.4 Research data acquisition stage 
Based on information provided and a review of offered materials ADP will evaluate and assess if data are suitable 
for acquisition. Emphasis will be placed on their scientific value as well as the future usability for different purposes 
and potential users. 
The following 
is of 
crucial importance: 
• Topical relevance, completeness of data, high number of variables, quality of methodology. 
• Study as a part of series, international comparability, potential of linking with other data and the 
existence of harmonized standard demographic variables. 
• In addition, both depth and exhaustiveness of interviews are important in the case of qualitative data. 
No single criterion is decisive. The evaluation of fitness for further use is crucial and is also based on the rarity of 
either data type or topic in the existing catalogue of a data centre. Formal criteria such as formats, appropriate 
data documentation etc. are obvious preconditions for data re-usage, without which data could be useless for 
future users. Completeness of data, supporting documentation and provenance, and any recorded changes are 
important for continuity of digital preservation which is taken over by an archive.29 
In the case of a positive evaluation, ADP and the depositor agree on the acquisition and then make necessary provisions 
for distribution. This includes editing documentation and data in accordance with international standards, 
and preparing the final version of the dataset and the study description. As a final step, the researcher approves 
that the data and accompanying material is valid before it is published in the catalogue. 
28 Lužar, Sanja, Maja Ojsteršek in 
Irena Vipavc Brvar (2012): Priporočila 
za urejanje podatkovne 
datoteke [Guidelines for editing 
data file]. ADP. [http://www.adp. 
fdv.uni-lj.si/blog/wp-content/ 
uploads/2012/11/PriporocilaZaPodatkovnoDatoteko2.
pdf]. 
29 Compare with: NERC Data 
Value Checklist. [http://www. 
nerc.ac.uk/research/sites/data/ 
policy/data-value-checklist.pdf, 
21. 1. 2015]. 
115) The researcher prepares 
clear and concise 
documentation and 
any other ancillary 
materials about the 
data for deposition in 
the Archive. 
• The data should be provided in electronic form accompanied by descriptive information 
such as file size, format, number of variables and units, code definitions etc.28 
• The materials should be prepared respecting archival instructions and addressing recommendations 
about formats. 
• The depositor should guarantee provisions have been taken to protect personal data. All 
direct identifiers should be removed. 
• Materials which help understand and verify the content of data should also be attached: 
e.g. codebooks, frequency files, instructions for interviewers, information about the 
implementation of the study, links to study reports or their copies if not being publically 
available. Both electronic and printed versions of the questionnaire in the original form 
should be attached. 
2.2.4 Research data acquisition stage 
Based on information provided and a review of offered materials ADP will evaluate and assess if data are suitable 
for acquisition. Emphasis will be placed on their scientific value as well as the future usability for different purposes 
and potential users. 
The following 
is of 
crucial importance: 
• Topical relevance, completeness of data, high number of variables, quality of methodology. 
• Study as a part of series, international comparability, potential of linking with other data and the 
existence of harmonized standard demographic variables. 
• In addition, both depth and exhaustiveness of interviews are important in the case of qualitative data. 
No single criterion is decisive. The evaluation of fitness for further use is crucial and is also based on the rarity of 
either data type or topic in the existing catalogue of a data centre. Formal criteria such as formats, appropriate 
data documentation etc. are obvious preconditions for data re-usage, without which data could be useless for 
future users. Completeness of data, supporting documentation and provenance, and any recorded changes are 
important for continuity of digital preservation which is taken over by an archive.29 
In the case of a positive evaluation, ADP and the depositor agree on the acquisition and then make necessary provisions 
for distribution. This includes editing documentation and data in accordance with international standards, 
and preparing the final version of the dataset and the study description. As a final step, the researcher approves 
that the data and accompanying material is valid before it is published in the catalogue. 
28 Lužar, Sanja, Maja Ojsteršek in 
Irena Vipavc Brvar (2012): Priporočila 
za urejanje podatkovne 
datoteke [Guidelines for editing 
data file]. ADP. [http://www.adp. 
fdv.uni-lj.si/blog/wp-content/ 
uploads/2012/11/PriporocilaZaPodatkovnoDatoteko2.
pdf]. 
29 Compare with: NERC Data 
Value Checklist. [http://www. 
nerc.ac.uk/research/sites/data/ 
policy/data-value-checklist.pdf, 
21. 1. 2015]. 

2 3 Data publication 
122 3 Data publication 
2.3.1 Access to research data 
Data centres and archives process deposited research data, prepare them for long-term preservation, publish 
them in the catalogue together with metadata and documentation, thus making the data both findable and 
accessible. Researchers and other users can familiarize with the content of data and their generation process 
through the “Study description” document which accompanies data publication. They are also provided with 
the information about the access conditions. 
Users are provided with the following services while accessing data: 
Options to search and familiarize 
ADP publishes data in a list 
of studies30 on the website, 
where it is possible to: 
• Browse through topics, series, authors etc. 
• Access shorter study descriptions, datasets, question texts and related materials. 
• Find a link to access data. 
Parallel to the publication 
on the website, information 
about the data as well as the 
microdata themselves are 
available in the Nesstar catalogue 
of ADP. Additionally, it 
provides: 
• Full study descriptions using the DDI metadata standard. 
• Simple or advanced searching through individual elements of study descriptions 
including question texts, and searching for comparable data across studies for the 
purpose of longitudinal research. 
• Online analysis of data. 
• Access to microdata for download and further analysis. 
Metadata about studies are 
included in catalogue aggregators: 
• Information about data publication can be entered into the shared catalogue of 
Slovenian libraries – COBIB.SI and the Open Science national portal.31 
• When a study is entered into the COBIB.SI system, it is displayed in the researcher’s 
bibliography and thus contributing points to the scoring of scientific excellence as a 
recognised scientific data publication. 
• It is also possible to search the CESSDA Data Catalogue, which is a common catalogue 
of European Social Science Data Archives.32 
30 ADP: The list of studies by study’s 
ID [http://www.adp.fdv.uni-lj.si/opisi/, 
21. 1. 2015]. 
31 Open Science Slovenia [http:// 
openscience.si/, 21. 1. 2015]. 
32 CESSDA: The CESSDA Catalogue. 
[http://www.cessda.net/catalogue/, 
21. 1. 2015]. 

Respecting access conditions 
As a precondition of access 
each user is required to register 
and define the purpose for 
which the data will be used: 
• The archive distinguishes between using data for academic and using data for public 
(including commercial) purposes. 
• Among academic users there’s further distinction between registered researchers 
(based on SICRIS data) and other users who use data mainly for educational purposes. 
• Additionally, access can be controlled by exceptions defined by the depositor at the 
time of deposition to the ADP (e.g. access with a special regime of confidentiality, only 
with author’s agreement for a certain period of time). 
Respecting access conditions 
As a precondition of access 
each user is required to register 
and define the purpose for 
which the data will be used: 
• The archive distinguishes between using data for academic and using data for public 
(including commercial) purposes. 
• Among academic users there’s further distinction between registered researchers 
(based on SICRIS data) and other users who use data mainly for educational purposes. 
• Additionally, access can be controlled by exceptions defined by the depositor at the 
time of deposition to the ADP (e.g. access with a special regime of confidentiality, only 
with author’s agreement for a certain period of time). 
33 Ball, Alex and Monica Duke (2012): 
How to Cite Datasets and Link to 
Publications, Edinburgh: DCC. 
[http://www.dcc.ac.uk/sites/default/ 
files/documents/publications/reports/
guides/How_to_Cite_Link.pdf]. 

34 ADP: Predavanja in predstavitve 
ADP. [http://www.adp.fdv.uni-lj.si/ 
publikacije_adp/predavanja/, 21. 

1. 2015]. 
Reporting data use 

Data centres analyse access 

• Website traffic (e.g. measured via Google analytics). 
statistics for the purposes of 
• Access to metadata and related materials. 
reporting and for planning of 
• Online analysis and data downloads. 
promotional and educational 
activities: 
2.3.2 Advantages of acknowledging data as a scientific publication 
Published data are appraised in the same way as any other scientific publication. They represent a »first class 
information object within scholarly information systems« and the following advantages originate from that: 

Publication is uniquely 

Published data (and all ensuing versions) have a unique identifier which is designated by the 
identified 


data centre. At an international level, similarly to regular monographic publications and articles 
in journals, different forms of permanent identifiers have been introduced for microdata, 
such as: DOI,33 URN etc. Permanent identifiers, if explicitly and appropriately listed, represent 
a discrete connection between publication and underlying data. 

Citing data used Upon registration, in published study descriptions, in data workshop materials and in user 
guides, all users are reminded to cite research data and related materials.34 It is recommended 
that data be cited in journal article reference lists with a full reference to the author, the title, 
the place of data access, the permanent identifier, according to citation rules as detailed by 
each scientific journal. 

Data are acknowledged 

The author or a group of authors could receive points to the scoring of scientific excellence 

as a publication and 

based on the publication of data in the ADP catalogue. Deposited data of scientific signifi


are therefore evaluated 

cance and of potential interest for further use could be entered into COBIB.SI35 system after 

and evidenced in the 

being published by the ADP. That could also contribute to the scoring for the evaluation of 

bibliography of re-

project effectiveness. 

searcher’s institutions 

Citations of other data-
related publications are 
increased 
Open access publication of data increases the number of citations and results in the favourable 
reception of articles written by the original authors of the research.36 Data publication is 
accompanied by authors’ own publications and therefore increases the probability of other 
users who may consider using the data for their own analysis. At the same time, an article in 
which analysed data are referenced becomes more reliable through verification and promotes 
further analysis of the same data. 
Citation indexes Citing data used in reference lists increases traceability of use and visibility of existing data 
sources. Similar to citation indexes for traditional publications, data citation indexes for research 
data will become important for measuring efficiency and impact. Those effects will be 
realised through a consistent approach to citing research data use (e.g. by using permanent 
identifiers). Citing data in reference lists of publications also facilitates verification of the 
long-term importance of data for science.37 


35 The entry is classified under the 
category 2.20 Complete Scientific 
Database or Corpus, defined as: »An 
electronic data collection, the scientific 
relevance of which is demonstrated 
by the use for the purpose of 
researching a wide range of theoretical 
and applied problems. The data 
collection must be the outcome of an 
accomplished research and comply 
with high quality standards. The 
quality is assessed on the basis of the 
detailed accompanying documentation. 
The data collection must be 
publicly available in the national or 
international scientific data archives. 
The collection must be documented 
and available in a form that allows 
the repetition of published scientific 
findings made on its basis.« See: 
IZUM (2013): Typology of documents/ 
works for bibliography management 
in COBISS. Maribor: IZUM. [http:// 
home.izum.si/COBISS/bibliografije/ 
Tipologija_eng.pdf]. 

36 Costas, Rodrigo, Ingeborg Meijer, 
Zohreh Zahedi and Paul Wouters 
(2013): The Value of Research 
Data - Metrics for datasets from a 
cultural and technical point of view. 
Copenhagen: Knowledge Exchange. 
[www.knowledge-exchange.info/ 
datametrics]. 

37 See discussion on: Whyte, Angus 
and Andrew Wilson (2010): How to 
Appraise and Select Research Data for 
Curation. DCC. Research Data. Advice 
paper, no. 14. [http://www.dcc.ac.uk/ 
resources/how-guides/appraise-select-
data#sthash.4WjHGwZ1.dpuf]. 


2.3.3 How to participate in promoting data use 
Along with data centres and archives, the following stakeholders can participate in promoting and exploiting 
access to research data: 

Researcher: 

• Includes information about a data publication in researcher’s own bibliographic reports, and lists these 
as evidence of scientific integrity. 
• When publishing reports, the researcher cites his or her data with a full reference in bibliographic reference 
lists. 
• Participates in promoting data usage through training when data are complex and difficult to use (e.g. 
organization of workshops, seminars or conferences covering aspects of working with data). 
Research 
institution: 
• Reports statistics about their own data, which are available in data centres, and their use to add into the 
excellence profile.38 
• Offers research data management support, stimulates data deposition by acknowledging it as part of 
scientific career progression. 
• Promotes data reuse. 
Library: 

• Provides information about accessioning datasets into a bibliographic system for the purpose of scientific 
evaluation and resource discovery. 
• Provides data citation guidance. 
• Provides information on datasets, modes of access and possible use at information literacy training. 
• Provides information about linking data with publications and research projects. 
38 LERU Research Data Working 
Group (2013): LERU Roadmap for 
Research Data. Advice paper, no. 14. 
[http://www.leru.org/files/publications/
AP14_LERU_Roadmap_for_ 
Funder: • Monitors if data are openly available as specified in the research project contract and advises about 
possible consequences if not available. 
• Assures that properly published research data are acknowledged as a contribution to science in the 
framework of a national system of scientific evaluation. 
• Stimulates the creation of high quality data and their deposition in open access solutions, introduces 
sanctions for controlling access. 
• Provides conditions for sustainable data infrastructure and services. 
• Promotes reuse of data in their policies. 
Research_data_final.pdf], p. 21. 
Common 

• Coordinating development of supporting infrastructure and services aimed at helping researchers, and 
39 Ibid. 

tasks: 

to decrease the burden of adhering to additional open access requirements.39 

40 FOSTER [https://www.fosteropenscience.
eu/, 21. 1. 2015]. 

• Training current and future researchers and supporting personnel, data librarians, data scientists etc.40 

3 FURTHER SUPPORT 

Dealing with research data throughout the data lifecycle involves being familiar with a wide spectrum 
of standards and good practices. Recently, in order to fulfil funders requirements researchers are increasingly 
being asked to complete formal data management. 

To further support 

• Guides and tools, prepared by expert organisations, such as DCC.41 
planning and work• 
Online tools such as DMPonline42 or DMP Editor.43 
ing with data, the 
• Online research data management training resources, e.g. MANTRA.44 
following are available: 
Data centres also 
provide guidance 
about: 
• Methodology – about exploiting existing data and about professional standards related 
to data collection methods. 
• Technical aspects – data and metadata formats, normalisation and migration, documenting, 
versioning, digital curation. 
• Legal perspectives – agreements, privacy protection, intellectual property rights and 
licenses, ethics. 
ADP provides detailed recommendations about depositing and archiving procedures on their website 
section “About archiving”.45 We recommend using guidelines from similar data centres as well.46 Familiarization 
with DSA guidelines47 is also recommended in order to achieve a coordinated and responsible 
approach to research data management with stakeholders involved throughout the whole data lifecycle, 
from planning and creating, digital preservation, access in data centres and to the final use. 


41 Digital Curation Centre: Resources for digital 
curators. [ http://www.dcc.ac.uk/resources, 

20. 1. 2015]. 
42 Digital Curation Centre: DMPonline. 
[https://dmponline.dcc.ac.uk/, 20. 1. 2015]. 

43 OpenMetadata.org: Data Management 
Plan (DMP) Editor. OpenMetadata.org. [http:// 
www.openmetadata.org/site/?page_id=373, 

21. 1. 2015]. 
44 EDINA (2014): MANTRA – Research Data 
Management Training. The University of Edinburgh. 
[http://datalib.edina.ac.uk/mantra/]. 

45 ADP: About archiving. [http://www.adp. 
fdv.uni-lj.si/za_uporabnike/o_arhiviranju/, 

21. 1. 2015]. 
46 UK Data Service: Prepare and manage data. 
[http://ukdataservice.ac.uk/manage-data. 
aspx, 21. 1. 2015]. 

ICPSR: Data Management & Curation. [http:// 
www.icpsr.umich.edu/icpsrweb/content/datamanagement/
index.html, 21. 1. 2015]. 

Tjalsma, Heiko and Jeroen Rombouts (2011): 
Selection of research data, Guidelines for 
appraising and selecting research data. Haag 
in Delft: Stichting SURF, Data Archiving and 
Networked Services (DANS), 3TU.Datacentrum. 
[http://act.dans.knaw.nl/nl/over/organisatie-
beleid/Publicaties/DANSselectionofresearchdata.
pdf]. 

ICPSR and DANS (2010): Preparing data for 
sharing; Guide to Social Science data archiving. 
Amsterdam: Pallas Publications. [http:// 
act.dans.knaw.nl/nl/over/organisatie-beleid/ 
Publicaties/DANSpreparingdataforsharing. 
pdf]. 

47 Data Seal of Approval: The Guidelines 20142015. 
[http://www.datasealofapproval.org/en/ 
information/guidelines/, 21. 1. 2015]. 


48 Data Seal of Approval: The Guidelines 
2014-2015. [http://www.datasealofapproval.
org/en/information/ 
guidelines/, 21. 1. 2015]. 

Appendix: The DSA Guidelines 2014-2015 

Guidelines Relating to Data Producers: 

1. 
The data producer deposits the data in a data repository with sufficient information for others to assess 
the quality of the data and compliance with disciplinary and ethical norms. 
2. 
The data producer provides the data in formats recommended by the data repository. 
3. 
The data producer provides the data together with the metadata requested by the data repository. 
Guidelines Related to Repositories: 

4. The data repository has an explicit mission in the area of digital archiving and promulgates it. 
5. 
The data repository uses due diligence to ensure compliance with legal regulations and contracts including, 
when applicable, regulations governing the protection of human subjects. 
6. The data repository applies documented processes and procedures for managing data storage. 
7. 
The data repository has a plan for long-term preservation of its digital assets. 
8. Archiving takes place according to explicit work flows across the data life cycle. 
9. 
The data repository assumes responsibility from the data producers for access and availability of the 
digital objects. 
10.The data repository enables the users to discover and use the data and refer to them in a persistent way. 
11. The data repository ensures the integrity of the digital objects and the metadata. 
12. The data repository ensures the authenticity of the digital objects and the metadata. 
13. The technical infrastructure explicitly supports the tasks and functions described in internationally 
accepted archival standards like OAIS. 
Guidelines Related to Data Consumers: 

14. The data consumer complies with access regulations set by the data repository. 
15. The data consumer conforms to and agrees with any codes of conduct that are generally accepted in the 
relevant sector for the exchange and proper use of knowledge and information. 
16. The data consumer respects the applicable licences of the data repository regarding the use of the 
data.48 

DEPOSITING RESEARCH DATA WITH ADP 
ADP accepts quality research data with high reuse potential that is well-organised, properly prepared and documented for further analysis. 
The process of depositing research data consists of the following steps: 
1. Check the ADP criteria for the acquisition 
2. Fill in the Acquisition Proposal Form 
3. Fill in the Study Description Form 
4. Edit and document data, prepare accompanying materials 
5. Fill in and sign the Licence Agreement Form. 
www.adp.fdv.uni-lj.si/eng/za_dajalce/ 
DEPOSITING RESEARCH DATA WITH ADP 
ADP accepts quality research data with high reuse potential that is well-organised, properly prepared and documented for further analysis. 
The process of depositing research data consists of the following steps: 
1. Check the ADP criteria for the acquisition 
2. Fill in the Acquisition Proposal Form 
3. Fill in the Study Description Form 
4. Edit and document data, prepare accompanying materials 
5. Fill in and sign the Licence Agreement Form. 
www.adp.fdv.uni-lj.si/eng/za_dajalce/ 
ADP provides the following services to data depositors: 

• support with data management planning and preparing data for open access, 
• verifying and evaluating the importance of research data for science and its long-term usability, 
• introducing digital curation processes and workflows, 
• enabling discovery of and access to data, searching and browsing through study descriptions, 
• promotion of data use and, formal training about how to work with data in collaboration with partners. 
CONTACT: 

University of Ljubljana 
Faculty of Social Sciences 

Social Science Data Archives 

Kardeljeva ploščad 5 
SI-1000 Ljubljana 

www.adp.fdv.uni-lj.si 

arhiv.podatkov@fdv.uni-lj.si 


Arhiv.Druzboslovnih.Podatkov 
@ArhivPodatkov