1,721,213 research outputs found
Data Visualization and Information Literacy
No full textData visualization has grown in significance and complexity as the quantity of data and the technology supporting it have developed. Understanding and using data visualization is now a core skill that should be incorporated into information literacy goals by librarians and educators. Competency in data visualization is also closely related to data literacy and other quantitative literacies. Undergraduate students and other general learners should be exposed to the fundamentals of data visualization early in their education. This article proposes that evaluation, critique, and use of data visualization be the initial focus of education, and discusses some starting points for training in these three areas.Peer reviewe
FAIR BOT:as metadata is data is metadata is data ...
Full text linkWelcome to the first issue of IASSIST Quarterly for the year 2023 - IQ vol. 47(1).
The last article in this issue has in the title the FAIR acronym that stands for Findable, Accessible, Interoperable, and Reusable. These are the concepts most often focused on by our articles in the IQ and FAIR has an extra emphasis in this issue. The first article introduces and demonstrates a shared vocabulary for data points where the need arose after confusions about data and metadata. Basically, I find that the most valuable virtue of well-structured data – I deliberately use a fuzzy term to save you from long excursions here in the editor\u27s notes – is that other well-structured data can benefit from use of the same software. Similarly, well-structured metadata can benefit from the same software. I also see this as the driver for the second article, on time series data and description. Sometimes, the software mentioned is the same software in both instances as metadata is treated as data or vice versa. This allows for new levels of data-driven machine actions. These days universities are busy investigating and discussing the latest chatbots. I find many of the approaches restrictive and prefer to support the inclusive ones. Likewise, I also expect and look forward to bots having great relevance for the future implementation of FAIR principles.
The first article is on data and metadata by George Alter, Flavio Rizzolo, and Kathi Schleidt and has the title ‘View points on data points: A shared vocabulary for cross-domain conversations on data and metadata’. The authors have observed that sharing data across scientific domains is often impeded by differences in the language used to describe data and metadata. To avoid confusion, the authors develop a terminology. Part of the confusion concerns disagreement about the boundaries between data and metadata; and that what is metadata in one domain can be data in another. The shift between data and metadata is what they name as ‘semantic transposition’. I find that such shifts are a virtue and a strength and as the authors say, there is no fixed boundary between data and metadata, and both can be acted upon by people and machines. The article draws on and refers to many other standards and developments, most cited are the data model of Observations and Measurements (ISO 19156) and tools of the Data Documentation Initiative’s Cross Domain Integration (DDI-CDI). The article is thorough and explanatory with many examples and diagrams for learning, including examples of transformations between the formats: wide, long, and multidimensional. The long format of entity-attribute-value has the value domain restricted by the attribute, and in examples time and source are added, which demonstrates how further metadata enter the format. When transposing to the wide format, this is a more familiar data matrix where the same value domain applies to the complete column. The multidimensional format with facets is for most readers the familiar aggregations published by statistical agencies. The authors argue that their domain-independent vocabulary enables the cross-domain conversation. George Alter is Research Professor Emeritus in the Institute for Social Research at the University of Michigan, Flavio Rizzolo is Senior Data Science Architect for Statistics Canada. Kathi Schleidt is a data scientist and the founder of DataCove.
The format discussion in the first article is also the point of the second paper on ‘Modernizing data management at the US Bureau of Labor Statistics’. The US Bureau of Labor Statistics (BLS) has a focus on time series and Daniel W. Gillman and Clayton Waring (both from the BLS) view time series data as a combination of three components: A measure element; an element for person, places, and things (PPT); and a time element. In the paper Gillman and Waring also describe the conceptual model (UML) and the design and features of the system. First, they go back in history to the 1970s and the Codd relational model and to the standards developed and refined after 2000. You will not be surprised to find here among the references also the Data Documentation Initiative’s Cross Domain Integration (DDI-CDI). The mission is: ‘to find a simple and intuitive way to store and organize statistical data with the goal of making it easy to find and use the data’. A semantic approach is adopted, i.e. the focus is on the meaning of the data based upon the ‘Measures / People-Places-Things / Time’ model. Detailed examples show how PPT are categories of dimensions, for instance ‘nurse’ is in the Standard Occupational Classification and \u27hospital\u27 in the North American Industry Classification System. The paper – like the first paper – also refers to multidimensional structures. The modernization described at BLS is expected to be released in early 2023.
The third paper is by João Aguiar Castro, Joana Rodrigues, Paula Mena Matos, Célia Sales, and Cristina Ribeiro where all authors are affiliated with the University of Porto. Like the earlier articles this also references the Data Documentation Initiative (DDI) with a focus on the concepts behind the FAIR acronym: Findable, Accessible, Interoperable, and Reusable. The title is: ‘Getting in touch with metadata: a DDI subset for FAIR metadata production in clinical psychology’. Clinical psychology is not an area frequently occurring in IASSIST Quarterly, but it turns out that the project described started with interviews and data description sessions with research groups in the Social Sciences for identifying a manageable DDI subset. The project also draws on other projects such as TAIL, TOGETHER, and Dendro. The TAIL project concerned the integration metadata tools in the research workflow and assessed the requirements of researchers from different domains. TOGETHER was a project in the psycho-oncology domain and family-centered care for hereditary cancer. As most researchers showed to be inexperienced with metadata, they concentrated on a DDI subset that meant that FAIR metadata would be available for deposit. Support for researchers is essential as the they have the domain expertise and can create highly detailed descriptions. On the other hand, data curators can ensure that the metadata follow the rules of FAIR. This was achieved by embedding the Dendro platform in the research workflow, where creation of metadata is performed in an incremental description of the data. The article includes screenshots of the user interface showing the choice of vocabularies. The approach and the adoption of a DDI subset produced more comprehensive metadata than is usually available.
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 2023
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
Failure as the treatment for transforming complexity to complicatedness
Full text linkWelcome to the fourth issue of volume 42 of the IASSIST Quarterly (IQ 42:4, 2018).
The IASSIST Quarterly presents in this issue three papers. When you know how, cycling is easy. However, data for cycling infrastructure appears to be a messiness of complications, stakeholders and data producers. The exemplary lesson is that whatever your research area there are often many views and types of data possible for your research. And the fuller view does not make your research easier, but it does make it better. The term geospatial data covers many different types of data, and as such presents problems for building access points or portals for these data. The second paper also brings experiences with complicated data, now with a focus on data management and curation. I would say that the third paper on software development in digital humanities is also about complicatedness, but this time the complicatedness was not overcome. Maybe here complexity is a better choice of word than complicatedness. In my book things are complex until we have solved how to deal with them; after that they are only complicated. The word failure is even among the keywords selected for this entry. Again: Read and learn. You might learn more from failure than from success. I find that Sir Winston Churchill is always at hand to keep up the good spirit: ‘Success consists of going from failure to failure without loss of enthusiasm’.
From Canada comes the paper ‘Cycling Infrastructure in the Ottawa-Gatineau Area: A Complex Assemblage of Data’ that some readers might have seen in the form of a poster at the IASSIST 2018 conference in Montreal. The authors are Sylvie Lafortune, Social Sciences Librarian at Carleton University in Ottawa, and Joël Rivard, Geography and GIS Librarian at the University of Ottawa. The article is a commendable example of how to encompass and illuminate an area of research not only though data but also by including the data producers and stakeholders, and the relationships between them. The article is based upon a study conducted in 2017-2018 that explored the data story behind the cycling infrastructure in Ottawa, Canada’s capital city; or to be precise, the infrastructure of the cycling network of over 1,000 km which spans both sides of the Ontario and Quebec provincial boundary known as the Ottawa-Gatineau National Capital Region. The municipalities invest in cycling infrastructure including expanded and improved bike lanes and paths, traffic calming measures, parking facilities, bike-transit integration, bike sharing and training programs to promote cycling and increased cycling safety. The research included many types of data among which were data from telephone interviews concerning ‘who, where, why, when, and how’ in an Origin-Destination survey, data generated by mobile apps tracking fitness activities, collision data, and bike counters placed in the area. The study shows how a narrow subject topic such as cycling infrastructure is embedded in complicated data and many relationships.
Ningning Nicole Kong is the author of ‘One Store has All? – the Backend Story of Managing Geospatial Information Toward an Easy Discovery’. Many libraries are handling geographical information and my shortened version of the abstract from the article promises: GeoBlacklight and OpenGeoportal are two open-source projects that initiated from academic institutions, which have been adopted by many universities and libraries for geospatial data discovery. The paper provides a summary of geospatial data management strategies by reviewing related projects, and focuses on best management practices when curating geospatial data. The paper starts with a historical introduction to geospatial datasets in academic libraries in the United States and also presents the complicatedness involved in geospatial data. The paper mentions geoportals and related projects in both the United States and Europe with a focus on OpenGeoportal. Nicole Kong is an assistant professor and GIS specialist at Purdue University Libraries.
Sophie 1.0 was an attempt to create a multimedia editing, reading, and publishing platform. Based at the University of Southern California with national and international collaboration, Sophie 2.0 was a project to rewrite Sophie 1.0 in the Java programming language. The author Jasmine S. Kirby gives the rationale for the article ‘How NOT to Create a Digital Media Scholarship Platform: The History of the Sophie 2.0 Project’ in the sentence: ‘Understanding what went wrong with Sophie 2.0 can help us understand how to create better digital media scholarship tools’. For the first time we now have failure among the keywords used for a paper in IQ. The Institute of the Future of the Book (IFB) was a central collaborator in the development of the Sophie versions. The IFB describes itself as a think-and-do tank and it is doing many projects. The Kirby paper gives us a brief insight into the future of reading, starting from basic e-books in the 1960s. When you read through the article you will note caveats like lack of focus on usability and changing of the underneath software language. The article ends with good questions for evaluating digital scholarship tools.
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 - February 201
The interest group on qualitative data sums up and continues
Full text linkWelcome to the second issue of volume 43 of the IASSIST Quarterly (IQ 43:2, 2019).
With joy and pride the many people behind each issue of the IQ are here presenting a special issue. IASSIST has several interest groups of members committed to selected important areas under the umbrella of IASSIST. Be aware that you could become a member of an interest group (see: https://iassistdata.org/about/committees.html#interest). If an interest area that you find important is not presently on this list, you are invited to start campaigning for the formation of a new interest group. The interest groups discuss and document their area and often arrange sessions at the IASSIST conferences. More formalization and continued documentation of the group’s work are presented in conference papers and papers published here in the IQ.
This issue of the IQ is dedicated to papers on qualitative data presented by members of the group named ‘Qualitative Social Science & Humanities Data Interest Group’ (QSSHDIG) and related practitioners. Lynda Kellam from the Cornell Institute for Social & Economic Research and Mandy Swygart-Hobaugh of George State University end their leadership of the group with this special issue. Lynda Kellam and Celia Emmelhainz (qualitative research librarian at the University of California Berkeley) are guest editors of this issue and their introduction to the issue is following this page. I want to express my great thanks from the IQ to Lynda and Celia for taking the job of compiling a special issue. Support for qualitative data is important and a growing area. I trust you as readers will find valuable information and excellent advice in the papers of the many authors that are committed to improving the use and value of qualitative data.
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 201
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
Digital curation after digital extraction for data sharing
Full text linkWelcome to the third issue of volume 42 of the IASSIST Quarterly (IQ 42:3, 2018).
The IASSIST Quarterly presents in this issue three papers from geographically widespread countries. We call IASSIST ‘International’, so I am happy to present papers from three continents in this issue with papers from Zimbabwe, Italy and Canada.
The paper \u27The State of Preparedness for Digital Curation and Preservation: A Case Study of a Developing Country Academic Library\u27 is by Phillip Ndhlovu, who works as the institutional repository librarian and liaison librarian, and Thomas Matingwina, who is a lecturer at the Department of Library and Information Service at the National University of Science and Technology (NUST) in Bulawayo, Zimbabwe. Modern day libraries have vast amounts of digital content and the authors noted that because these collections require very different management than the traditional paper-based materials, the new materials’ longevity is endangered. Their study assessed the state of preparedness of the NUST Library for digital curation and preservation, including the assessment of awareness, competencies, technology infrastructure, digital disaster preparedness, and challenges to digital curation and preservation. They found a lack of policies, lack of expertise by library staff, and lack of funding.
You might conclude that investigating your own organization and reaching the very well known conclusion that \u27we need more money!\u27 is not so surprising. However, you have to take note that the Jeff Rothenberg statement from 1995 that \u27Digital information lasts forever – or five years, whichever comes first\u27 has not yet sunk in with politicians and administrators, who will immediately associate the term \u27digital\u27 with \u27saving money\u27. This study shows them why this is not a valid connotation. It is a study of a single institution, and as the authors note it cannot be generalized even to other academic libraries in Zimbabwe. However, other libraries - also outside Zimbabwe - have here a good guide for making their own assessment of the digital preparedness of their institution.
The second paper was - as was the paper above - presented at the IASSIST conference in 2018 and is also about the transition from media known for thousands of years to new media and digital forms. Peter Peller presented the paper \u27From Paper Map to Geospatial Vector Layer: Demystifying the Process\u27. He is the Director of the Spatial and Numeric Data Services unit at Libraries and Cultural Resources at the University of Calgary in Canada.
The conversion of raster images of maps to vector data is analogous to OCR technologies extracting words from scanned print documents. Thereby the map information becomes more accessible, and usable in geographic information systems (GIS). An illustrative example is that historical geospatial information can be overlaid in Google Earth. The description of the entire process incorporates examples of the various techniques, including different types of editing. Furthermore, descriptions of the software used in selected studies are listed in the appendix. It is mentioned that \u27paper texture and ink spread\u27 can be responsible for introducing noise and errors, so remember to keep the old maps. This is because what is considered noise in one context might become the subject for interesting future research. In addition the software for extracting information will most certainly improve.
For once both the author and we at IASSIST Quarterly have been quite fast. The data for the third paper was collected in late 2017 and the results are presented here only a year later. In October 2017 a message appeared on the IASSIST mail list with the start of the sentence \u27I would share the data but...\u27 It quickly generated many ways of completing that sentence. Flavio Bonifacio - who works at Metis Ricerche srl in Torino, Italy - quickly launched a questionnaire sent to members of the mail list and to others from similar communities of interested individuals. The questionnaire was an extension of an earlier one concerning scientists\u27 reuse and sharing of data. The paper includes many tabulations and models showing the background as well as the data sharing attitudes found in the survey. A respondent typology is developed based upon the level of propensity for sharing data and the level of experiencing problems in data sharing into a 2-by-2 table consisting of \u27irreducible reluctant\u27, \u27reducible reluctant\u27, \u27problematic follower\u27, and \u27premium follower\u27.
In the Nordic countries we tend to have the impression that certain services are publicly available and for free. This impression is plainly superficial because we Nordic people also know very well that \u27there is no such thing as a free lunch\u27! All services must be paid for in one way or another. If you have many services that carry no direct cost, it is probably because you - and others - paid for them beforehand through taxation. Because of cuts in the public economy one of the things Flavio Bonifacio wanted to investigate was the question \u27Is there a market for selling data-sharing services?\u27 The results imply that \u27reducible reluctants\u27 can be a target for services that reduce the problems of that group.
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 - November 201
We talk data. We do data
Full text linkWelcome to the third issue of IASSIST Quarterly for the year 2022 - IQ vol. 46(3).
In Denmark we sometimes retrieve an old quote from a member of the Danish Parliament: \u27If those are the facts, then I deny the facts\u27. We have laughed at that for more than a hundred years, but now fact denial is apparently the new normal in many places. And we are not amused. Data can become dangerous as facts can be fabricated. Therefore, a critical approach to data is fundamental to producing reliable information: facts. The articles in this issue are about teaching students good data behavior, and how researchers with great care and attention can carry out the task of fact production.
The first article is about improvement in teaching data: \u27Investigating teaching practices in quantitative and computational Social Sciences: a case study\u27 by Rebecca Greer and Renata G. Curty. The authors are both at the University of California, Santa Barbara Library, where Rebecca Greer is director of Teaching & Learning and Renata Curty is social science research facilitator. They are investigating data education and present some of the findings from a local report - part of a national project - into how instructors adapt curricula and pedagogy to advance undergraduates computational and statistical knowledge in the social sciences. The core goal of the instructors concerns \u27data thinking\u27 - the critical understanding and evaluation of data. Many students have a preconceived fear of mathematics that influences other areas. Personally, I feel that data thinking is essential to live and participation in society, and I believe that it should be achievable even with a background of math fear. However, for social science students I also expect they have acquired some level of \u27data doing\u27. I agree with the authors that the necessary support for data is more often found in the areas of Science, Technology, Engineering and Mathematics than it is in Social Sciences. However, many IASSIST members successfully work to relate data to social science students. And the implicit relationship via data to STEM areas will furthermore often improve job success for social science students. The local study interviewed instructors and the article presents among other things the learning goals and the explicit skills contained in these goals. The study uses many quotations from the interviewees, including quotes on sharing among the instructors. This leads to how the instructors can be further supported and how the library can support them, including a partnership between the library\u27s Research Data Services and Teaching & Learning.
With the second article we continue at a university. Now the focus shifts from teaching to research - the other main area of university work, and more specifically the data in research. The article \u27Research data integrity: A cornerstone of rigorous and reproducible research\u27 is by Patricia B. Condon, Julie F. Simpson and Maria E. Emanuel. All three are in positions at the University of New Hampshire, Durham, USA. The article starts with the foundation of the four Rs of research: rigor, reproducibility, replication, and reuse. The interest in data integrity came from a question at a graduate seminar on the difference between data integrity and data quality. When exploring the data quality component, they found that research data integrity is closely associated with data management as well as with data security. The aims of the article are several, but the first is to establish practical explanations of research data integrity and its components. Training and documentation are fundamental and form the surroundings in the proposed Research Data Integrity Model that also graphically presents the overlapping areas between the components: data quality, data management, and data security. I find this focus on the sharing between components a structurally clear approach, and with good outcome too. When juggling concepts that often are regarded as being more or less identical, it is clearly positive to make these relationships and distinctions. This positive structural approach is continued as the authors relate research data integrity to the research data lifecycle to produce an implementation schema. The last section is relating research data integrity to the four Rs.
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 - November 202
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
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