IASSIST Quarterly (Journal)
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Joining language with data and data with data
No full textWelcome to the IASSIST Quarterly first issue of 2021 and of volume 45 (IQ 45(1) 2021).
I always find it interesting to learn more about other research areas. Often, I find approaches in less well-known areas can be transformed and transferred to my own areas, or make me aware of problems unwisely ignored hitherto and becoming potentials. In the case of the first article, you will become aware of the connection with linguistics from a data viewpoint. As a search for datasets requires using words of a language it is obvious that linguistic knowledge can be of benefit. However, most is obvious when you think of it - afterwards. Often, it is because you did not think it through - beforehand - that new information surprises you. And this also gives you a good opportunity to thank people who are working in areas you had not thought of - before. The benefits of combining and merging types of data such as linking survey data and social media data are obvious - again! Before you start the journey of joining these types of data, the second article will provide you with valuable information gained from the experience of several projects and exemplified through cases using Twitter, Facebook, and LinkedIn.
The first article shows the support for diversity in research areas already in the title: \u27A recommendation to the SSH community: take a linguist on board\u27 authored by Jeannine Beeken of UK Data Service at University of Essex (UK). Theories and methods of linguistics are obviously relevant for data services where the search for and retrieval of data collections from vast data archives is an important step in the process towards analysis and findings in data. Beeken starts by introducing us to areas of this important retrieval step that are supported by Natural Language Processing (NLP) that increases findability, with the result that relevant descriptions of data collections are identified through online search. A simple example is that when searching for survey questions concerning \u27war\u27 the results will also include those from a search for \u27armed conflict\u27. The development and upkeep of thesauri and language relationships is a huge and valuable task that is itself supported by linguistics and computers, for example by intelligent creation of metadata for studies. Linguistic knowledge is not only relevant for finding data but also valuable for the production of data. Computer linguistics have made great progress for the growing number of studies based on texts and data in the form of interviews. In the article, speech recognition and speech-to-text transcription is mentioned and the resulting interview transcription text can again become the subject of further computer and linguistic analysis.
The second article \u27Informed consent for linking survey and social media data - differences between platforms and data types\u27 will prepare you for benefits and obstacles when joining data from surveys and social media. The article is a part of the outcomes of several projects with participation of the authors Johannes Breuer, Tarek Al Baghal, Luke Sloan, Libby Bishop, Dimitra Kondyli, and Apostolos Linardis. The authors are based at GESIS in Germany, Essex University and Cardiff University in the UK, and EKKE in Greece. The article draws on their own projects as well as on specific other projects delivering the examples in the article.
When using self-reporting in research surveys - in this case for the study of social media - the data can prove to be unreliable. On the other hand, when research obtains data directly from the social media platforms the background, attitude, and behaviour variables for individuals are sparse compared to surveys. The obvious solution is to link such data collections. However, the linking requires informed consent. The \u27joining of data\u27 and \u27informed consent\u27 implies awareness of legal regulations - like GDPR (General Data Protection Regulation) in Europe - as well as ethical standards and guidelines of relevant institutions. The article discusses these issues and demonstrates them through three studies that used data from Twitter, Facebook, and LinkedIn. Furthermore, the regulations and setups for the social platforms have to be well scrutinized. For example, if respondents share their private data, these may also affect the privacy rights of others, and data that are collected via APIs may have special restrictions with regard to data sharing. The appendices of the article contain the full text used in the various projects for explicating the use of data and the conditions in the linking of survey and social media data. In addition to raising general awareness and giving a good overview of problems when using social media data, the article will initiate you into being well prepared, as the cases discussed include many valuable references to pursue if you plan on commencing a project linking social media data with survey data.
Enjoy the reading.
Submissions of papers for the IASSIST Quarterly are always very welcome. We welcome input from IASSIST conferences or other conferences and workshops, from local presentations or papers especially written for the IQ. When you are preparing such a presentation, give a thought to turning your one-time presentation into a lasting contribution. Doing that after the event also gives you the opportunity of improving your work after feedback. We encourage you to login or create an author profile at https://www.iassistquarterly.com (our Open Journal System application). We permit authors to have \u27deep links\u27 into the IQ as well as deposition of the paper in your local repository. Chairing a conference session or workshop with the purpose of aggregating and integrating papers for a special issue IQ is also much appreciated as the information reaches many more people than the limited number of session participants and will be readily available on the IASSIST Quarterly website at https://www.iassistquarterly.com. Authors are very welcome to take a look at the instructions and layout:
https://www.iassistquarterly.com/index.php/iassist/about/submissions
Authors can also contact me directly via e-mail: [email protected]. Should you be interested in compiling a special issue for the IQ as guest editor(s) I will also be delighted to hear from you.
Karsten Boye Rasmussen - March 202
Publishing trends on research data management in Sub-Saharan Africa: A bibliometrics analysis
Full text linkResearch data management is an umbrella term used to describe activities related to the creation, organisation, structuring, naming, backing up, storage, conservation, and sharing of research data as well as all actions that guarantee security of research data. As is often the case, researchers from Sub-Saharan Africa are lagging behind their counterparts in developed countries in embracing the best practices of research data management. One of the factors to which this slow pace of adoption of research data management could be attributed, is inadequate research on the subject. The purpose of this paper is to analyse the quantity, quality, visibility and authorship of publications on research data management in Sub-Saharan Africa. Bibliometrics approaches were used to analyse publications on research data management from, and on, Sub-Saharan Africa which are currently indexed in Google Scholar. The index was chosen because it is free and is reputed to have liberal selection criteria which do not favour, or discriminate, any discipline or geographic regions. Data was retrieved from Google Scholar using Harzing’s “Publish or Perish” software and analysed using VOSviewer. The findings of the study revealed that the quantity, quality, visibility and authorship collaboration of scholarly publications on research data management in Sub-Saharan Africa is low. The findings may be used by libraries and research institutions in Sub-Saharan Africa to develop and promote best practices in research data management as a means of enhancing their research output and impact
Better data management, one nudge at a time
Full text linkHow do you help people improve their data management skills? For our team at the University of Illinois at Urbana-Champaign, we decided the answer was "one nudge at a time”.
A study conducted by Wiley and Mischo (2016) found that Illinois researchers are aware of data services available but under-utilize them. Many researchers do not consider data management as a concern distinct from researching and producing scholarly work products. In 2017, the RDS piloted the Data Nudge – a monthly, opt-in email service to “nudge” Illinois researchers toward good data management practices, and towards utilizing data services on campus. The aim of the Data Nudge was to address the gap between knowing about a service and using it by highlighting best practices and campus resources.
The topics covered in the Data Nudge center around data. Some topics are applicable to everyone, such as data back-up, documentation, and file naming conventions. Other topics are specific to Illinois, like storage options, events, and conferences.
After four years, the Data Nudge has accumulated over 400 subscribers through word-of-mouth, marketing channels on campus and inclusion in subject liaisons\u27 instructional workshops. It receives stable open rates averaging at 52% (compared to 19.44% average industry rate for Higher Education*) and many compliments from subscribers. We expect the Data Nudge to continue supplementing workshops and training as an effective means of communication to reach researchers on our campus. In the spirit of re-use, we are in the process of archiving the Data Nudge topics in a reusable format, readily adaptable by other institutions.
Data Nudge link: https://go.illinois.edu/past_nudge
Potential opportunities and risks of sharing agricultural research data in Tanzania
Full text linkPurpose: The purpose of this paper was to examine the potential opportunities and risks of sharing agricultural research data in Tanzania identified in the existing research literature.
Design/methodology/approach: The study involved a review of the literature on research data sharing practices.
Findings: The findings indicate that, research data sharing have significant positive benefits among researchers such as increase high research impact; enhancing international community collaboration among researchers with same interests; improving scientific transparency and accuracy of data (Rappert and Bezuidenhout, 2016); increasing research output whereby a single dataset can be used to generate more than one article by different authors; and many more. The risks hampering data sharing practices includes researchers’ fears that data will be scooped, poached or misused (Onyancha, 2016); unreliable electric power; lack of fund to support research data sharing activities; absence of institutional governmental support for data management; perceived lack of evidence benefits (Leonelli, Rappert and Bezuidenhout, 2018); and others. However, in Tanzania research data sharing is relatively new, thus, no any governmental agency mandating or encouraging research data sharing; therefore, there is no research data management; no research open data repositories and no research data sharing policy at any agricultural institution in Tanzania. The study recommends that agricultural researchers should be sensitized to share their data, research data policy and data repositories should also be established to support data sharing practices in Tanzania.
Originality and usefulness: From the available literature, this has been the first time that an effort has been made to examine the potential opportunities and risks of sharing agricultural research data in Tanzania. The study could be used by agricultural institutions and other institutions to assess the researchers’ needs in supporting research data sharing. Also, it can be used by the government and institutions to see the need of establishing open data repositories and open data policies to support research data sharing
Examining barriers for establishing a national data service
Full text linkA system for monitoring the current situation of Data Archive Services (DAS) maturity in European countries was developed during the CESSDA Strengthening and Widening in (SaW 2016 and 2017) and further adapted in CESSDA Widening Activities 2018 (WA 2018) projects for continuous monitoring. An assessment of the existing national data sharing culture, the development of the social science sector and its production of high-quality research data, the funders’ research data policy requirements, and the capacity and skills of national grassroots initiatives, provide a framework for understanding the current situation in different countries. Methods used in the projects, included desk research of existing documents and a survey, combined with extensive interviews focused on the area of expertise of the informants (individuals from data services, research and decision makers’ representatives from each country). The focus of the paper is the situation in 20 non-member CESSDA European countries with emerging and immature DAS initiatives. Results show that countries are slowly but persistently removing the key obstacles in establishing a DAS initiative in their respective countries. The remaining obstacles reside mainly outside the control of the data professional community – namely research funders slowly adopt data sharing policies and incentives for data sharing, including the provision of a sustainable DAS infrastructure, capable of supporting researchers with publishing and accessing research data. The results show that the lack of expertise and skills of DAS initiatives, their understanding of tools and services or organizational settings are not such an issue, as more mature DAS are organising training and mentorship activities. Detailed guidance in the DAS advocacy and planning was prepared in the framework of the above-mentioned pan-European and some past regional projects. The tools and framework of those activities will be referred to in the discussions as a resource that can be used in other countries and continents
Learning from data reuse: successful and failed experiences in a large public research university library
Full text linkThis paper illustrates a large research university library experience in reusing the data for research collected both within and outside of the library to demonstrate data reuse practice. The purpose of the paper is to 1) demonstrate when and how data are reused in a large public research university library, 2) share tips on what to consider when reusing data, and 3) share challenges and lessons learned from data reuse experiences. This paper presents five proposed opportunities for data reuse conducted by three researchers at the institution’s library which resulted in three successful instances of data reuses and two failed data reuses. Learning from successful and failed experiences is critical to understand what works and what does not work in order to identify best practices for data reuse. This paper will be helpful for librarians who intend to reuse data for publication
Reproducibility, preservation, and access to research with ReproZip and ReproServer
Full text linkThe adoption of reproducibility remains low, despite incentives becoming increasingly common in different domains, conferences, and journals. The truth is, reproducibility is technically difficult to achieve due to the complexities of computational environments. To address these technical challenges, we created ReproZip, an open-source tool that automatically packs research along with all the necessary information to reproduce it, including data files, software, OS version, and environment variables. Everything is then bundled into an rpz file, which users can use to reproduce the work with ReproZip and a suitable unpacker (e.g.: using Vagrant or Docker). The rpz file is general and contains rich metadata: more unpackers can be added as needed, better guaranteeing long-term preservation. However, installing the unpackers can still be burdensome for secondary users of ReproZip bundles. In this paper, we will discuss how ReproZip and our new tool, ReproServer, can be used together to facilitate access to well-preserved, reproducible work. ReproServer is a web application that allows users to upload or provide a link to a ReproZip bundle, and then interact with/reproduce the contents from the comfort of their browser. Users are then provided a persistent link to the unpacked work on ReproServer which they can share with reviewers or colleagues
Sharing qualitative research data, improving data literacy and establishing national data services
Full text linkWelcome to the fourth issue of volume 43 of the IASSIST Quarterly (IQ 43:4, 2019).
The first article is authored by Jessica Mozersky, Heidi Walsh, Meredith Parsons, Tristan McIntosh, Kari Baldwin, and James M. DuBois – all located at the Bioethics Research Center, Washington University School of Medicine, St. Louis, Missouri in USA. They ask the question “Are we ready to share qualitative research data?”, with the subtitle “Knowledge and preparedness among qualitative researchers, IRB Members, and data repository curators.” The subtitle indicates that their research includes a survey of key personnel related to scientific data sharing. The report is obtained through semi-structured in-depth interviews with 30 data repository curators, 30 qualitative researchers, and 30 IRB staff members in the USA. IRB stands for Institutional Review Board, which in other countries might be called research ethics committee or similar. There is generally an increasing trend towards data sharing and open science, but qualitative data are rarely shared. The dilemma behind this reluctance to share is exemplified by health data where qualitative methods explore sensitive topics. The sensitivity leads to protection of confidentiality, which hinders keeping sufficient contextual detail for secondary analyses. You could add that protection of confidentiality is a much bigger task in qualitative data, where sensitive information can be hidden in every corner of the data, that consequently must be fine-combed, while with quantitative data most decisions concerning confidentiality can be made at the level of variables. The reporting in the article gives insights into the differences between the three stakeholder groups. An often-found answer among researchers is that data sharing is associated with quantitative data, while IRB members have little practice with qualitative. Among curators, about half had curated qualitative data, but many only worked with quantitative data. In general, qualitative data sharing lacks guidance and standards.
The second article also raises a question: “How many ways can we teach data literacy?” We are now in Asia with a connection to the USA. The author Yun Dai is working at the Library of New York University Shanghai, where they have explored many ways to teach data literacy to undergraduate students. These initiatives, described in the article, included workshops and in-class instruction - which tempted students by offering up-to-date technology, through online casebooks of topics in the data lifecycle, to event series with appealing names like “Lying with Data.” The event series had a marketing mascot - a “Lying with Data” Pinocchio - and sessions on being fooled by advertisements and getting the truth out of opinion surveys. Data literacy has a resemblance to information literacy and in that perspective, data literacy is defined as “critical thinking applied to evaluating data sources and formats, and interpreting and communicating findings,” while statistical literacy is “the ability to evaluate statistical information as evidence.” The article presents the approaches and does not conclude on the question, “How many?” No readers will be surprised by the missing answer, and I am certain readers will enjoy the ideas of the article and the marketing focus.
With the last article “Examining barriers for establishing a national data service,” the author Janez Štebe takes us to Europe. Janez Štebe is head of the social science data archives (Arhiv Družboslovnih Podatkov) at the University of Ljubljana, Slovenia. The Consortium of European Social Science Data Archives (CESSDA) is a distributed European social science data infrastructure for access to research data. CESSDA has many - but not all - European countries as members. The focus is on the situation in 20 non-CESSDA member European countries, with emerging and immature data archive services being developed through such projects as the CESSDA Strengthening and Widening (SaW 2016 and 2017) and CESSDA Widening Activities (WA 2018). By identifying and comparing gaps and differences, a group of countries at a similar level may consider following similar best practice examples to achieve a more mature and supportive open scientific data ecosystem. Like the earlier articles, this article provides good references to earlier literature and description of previous studies in the area. In this project 22 countries were selected, all CESSDA non-members, and interviewees among social science researchers and data librarians were contacted with an e-mail template between October 2018 and January 2019. The article brings results and discussion of the national data sharing culture and data infrastructure. Yes, there is a lack of money! However, it is the process of gradually establishing a robust data infrastructure that is believed to impact the growth of a data sharing culture and improve the excellence and the efficiency of research in general.
Submissions of papers for the IASSIST Quarterly are always very welcome. We welcome input from IASSIST conferences or other conferences and workshops, from local presentations or papers especially written for the IQ. When you are preparing such a presentation, give a thought to turning your one-time presentation into a lasting contribution. Doing that after the event also gives you the opportunity of improving your work after feedback. We encourage you to login or create an author login to https://www.iassistquarterly.com (our Open Journal System application). We permit authors to “deep link” into the IQ as well as to deposit the paper in your local repository. Chairing a conference session with the purpose of aggregating and integrating papers for a special issue IQ is also much appreciated as the information reaches many more people than the limited number of session participants and will be readily available on the IASSIST Quarterly website at https://www.iassistquarterly.com. Authors are very welcome to take a look at the instructions and layout:
https://www.iassistquarterly.com/index.php/iassist/about/submissions
Authors can also contact me directly via e-mail: [email protected]. Should you be interested in compiling a special issue for the IQ as guest editor(s) I will also be delighted to hear from you.
Karsten Boye Rasmussen - December 201
The matter of meta in research data management: Introducing the CESSDA Metadata Office Project
Full text linkAccompanying the growing importance of research data management, the provision and maintenance of metadata – understood as data about (research) data – have obtained a key role in contextualizing, understanding, and preserving research data. Acknowledging the importance of metadata in the social sciences, the Consortium of European Social Science Data Archives started the Metadata Office project in 2019. This project report presents the various activities of the Metadata Office (MDO). Metadata models, schema, controlled vocabularies and thesauri are covered, including the MDO’s collaboration with the DDI Alliance on multilingual translations of DDI vocabularies for CESSDA Service Providers. The report also summarizes the communication, training and advice provided by MDO, including DDI use across CESSDA, illustrates the impact of the project for the social science and research data management community, and offers an outline regarding future plans of the project
Countries closing down - reproducibility keeping science open
Full text linkWelcome to volume 44 of the IASSIST Quarterly. Here in 2020 we start with a double issue on reproducibility (IQ 44(1-2)).
The start of 2020 was in the sign of Corona. Though we are now only in the middle of the year, we can say with confidence that 2020 will be known for the closing down of nearly all public life. From our very own world this included the move of the IASSIST 2020 conference to 2021. The closing down of societies took different forms and this will and should be long debated and investigated, because many civil rights in open society were put on instant standby by governments, with various precautionary measures. Fortunately, many countries are now in the processes of opening up. Hopefully, we are now more careful, keeping socially distant, executing better sanitation, etc. We are also eagerly expectant of science breakthroughs: the vaccine, the better treatment, the cure. But Corona science extends beyond health and biology. Social science in particular has an obligation to make us better prepared to take necessary measures and to uphold democracy.
Social science has always had the reliable issue that you cannot step into the same river twice: Survey data collected at one time will not in a subsequent data collection bring the same results, even with the same panel of respondents. Reproducibility has many more forms than exact data collection, though, and is foundational for open science and an open society. Science needs to be transparent in order to be challenged and improved. Fellow scientists as well as laymen should have the possibility of performing analyses to find whether results can be reproduced.
I am therefore very happy to send my thanks to Harrison Dekker and Amy Riegelman for taking the initiative to create this special issue of the IASSIST Quarterly on reproducibility. Harrison Dekker is a data librarian at University of Rhode Island and Amy Riegelman a librarian in social sciences at the University of Minnesota. Together, Amy and Harrison reviewed the papers submitted for their special issue and wrote the introduction in the following pages. In addition to expressing my great appreciation to them, I also want to thank all the authors who submitted papers for this issue.
Thanks! Let\u27s keep science open again!
Submissions of papers for the IASSIST Quarterly are always very welcome. We welcome input from IASSIST conferences or other conferences and workshops, from local presentations or papers especially written for the IQ. When you are preparing such a presentation, give a thought to turning your one-time presentation into a lasting contribution. Doing that after the event also gives you the opportunity of improving your work after feedback. We encourage you to login or create an author login to https://www.iassistquarterly.com (our Open Journal System application). We permit authors \u27deep links\u27 into the IQ as well as deposition of the paper in your local repository. Chairing a conference session with the purpose of aggregating and integrating papers for a special issue IQ is also much appreciated as the information reaches many more people than the limited number of session participants and will be readily available on the IASSIST Quarterly website at https://www.iassistquarterly.com. Authors are very welcome to take a look at the instructions and layout:
https://www.iassistquarterly.com/index.php/iassist/about/submissions
Authors can also contact me directly via e-mail: [email protected]. Should you be interested in compiling a special issue for the IQ as guest editor(s) I will also be delighted to hear from you.
Karsten Boye Rasmussen - June 202