Research Skills

Workshop: "Advanced Topics in Applied Regression Analysis" (18 - 21.03.2024, 9.30 - 1.00 p.m.)

Workshop: "Advanced Topics in Applied Regression Analysis" (18 - 21.03.2024, 9.30 - 1.00 p.m.)

This workshop is organised by BAGSS.

Course Outline:

While it feels like regression analysis is not getting much love these days in the social sciences, it is still foundational for survey analysis – the tool that causal inferential models utilize for most (if not all their) estimation and that serves as the basis of the fancy advanced techniques receiving most of the attention today in social science outlets. For this reason, it is not only worth learning regression foundations well, but it is important to understand how advanced techniques build upon regression to analyse more flexibly.

We will start by reviewing the assumptions of regression modeling with an eye on what could go wrong with the kind of data used in the social sciences. We will explore the estimators and link functions necessary to deal with binary, ordered, and unordered (multinomial) outcomes with a specific emphasis on the correct interpretation of such regression results. Second, we start to explore the complexities of various data structures that emerge in voting behavior research, such as cross-country surveys, repeated cross-sectional surveys, panel data, or other within-person analyses. We will approach this complexity through three approaches: clustered standard errors, fixed and random effects corrections, also venturing into the world of multilevel modeling. In addition, we will also consider the (admittedly frustrating) topic of survey weights and discuss considerations and limitations in their applications. Building on this knowledge, time allowing, we will address topics of nonresponse and use imputation procedures for item missing data.

Although we will not fully cover topics of GLM, panel data analysis, multilevel modeling, sampling and weights, missing data, we will highlight the foundations important to embark on any of these paths and have glance at (and take home some R code for) examples of such analyses. This workshop will have an applied focus and will not go into the mathematical foundations of mentioned tools.

Prerequisites:

If you have done regressions before but feel like you are missing some foundations, you need a review, or you would like to build on the regression basics you have expanding into the advanced topics, you have come to the right workshop. If you have never done any regression analysis and would like to receive an introduction, this workshop is probably not for you just yet.

Basic R knowledge is strongly recommended. At least, you should be able to load a dataset and run a simple lm command. If you don’t know how to do this, please get there before the workshop. (This is not much, you can do it.) Also, once you know what you are doing, you can easily transfer your knowledge to the analysis tools of your preference.

Date & time: 18 - 21 March 2024, 9.30 - 11.00 a.m. & 11.30 a.m. - 1.00 p.m.

Location: Room tba. - Feldkirchenstraße 21

Instructor: Professor Levente Littvay, Centre for Social Sciences, Hungarian Academy of Sciences Centre of Excellence

Levente Littvay is a Research Professor (part-time) at the Centre for Social Sciences of the Hungarian Academy of Sciences Centre of Excellence. His research interests include multilevel & structural equation models, populist polarization, in particular the measurement & mitigation of partisan motivated democracy eroding policy preferences, and motivations underlying secessionist attitudes.

Course units: 16

Registration: Please register via this form by February 26, 2024.

Workshop: "Coding and Analysing Qualitative Data" (18 - 22.03.2024, 9.30 - 1.00 p.m.)

Workshop: "Coding and Analysing Qualitative Data" (18 - 22.03.2024, 9.30 - 1.00 p.m.)

This workshop is organised by BAGSS.

Course Outline:

Qualitative data can be very complex. Data coding allows one to organize, relate, and visualize data. Above all, it is a powerful tool to generate results in a structured and transparent fashion. Over decades, qualitative data coding has become much more advanced, not in the least because of the arrival of software packages that support it. This course introduces PhD students to qualitative data coding. The course addresses two aspects: the logic and operations of coding, and the use of software when coding data. We will address topics such as understanding the (layered) complexity of data, data exploration, discovery of patterns, structuring and visualization, and presentation of the results. This course is especially useful for those PhD students actively working with qualitative data, if only because there will be opportunities to explore and code one’s own dataset. Please note: the course is not just focused on how the software works. It very much is about getting coding right, regardless of whether software is involved or not.

Prerequisites:

Please ensure that you have the software MAXQDA or AtlasTI installed. MAXQDA is supported by the University of Bamberg, but we can also use AtlasTI. Please ensure that you have a qualitative dataset available. This can be of any type (e.g., interview transcripts, newspaper articles, photos or videos). This dataset should be accessible on the same laptop that has the software installed. PhD students who followed the BAGSS course ‘Qualitative Research Design’ get priority in enrollment.

Date & time: 18 - 22 March 2024, 9.30 a.m. - 1.00 p.m.

Location: Room tba. - Feldkirchenstraße 21

Instructor: Professor Dr Lasse Gerrits, Erasmus University Rotterdam

Lasse Gerrits is Academic Director at the Institute for Housing and Urban Development Studies of Erasmus University Rotterdam, focusing on the PhD program, student supervision, and developing the scientific portfolio of the institute.

Course units: 20

Registration: Please register via this form by February 26, 2024.

Workshop: "Introduction to Machine Learning for Social Sciences" (18 - 22.03.2024, 9.30 - 1.00 p.m.)

Workshop: "Introduction to Machine Learning for Social Sciences" (18 - 22.03.2024, 9.30 - 1.00 p.m.)

This workshop is organised by BAGSS.

Course Outline:

In this course, students will learn the basics of machine learning, specifically for social scientists. While the course will introduce specific models, such as support vector machines, decisions trees, or lasso regressions, we will also focus on general principles that apply to all machine learning algorithms. This will equip students with the tools to not only apply machine learning in their own research, but also judge the performance of such models and adapt to new developments in the field. The course includes practical applications with code and examples from different social science fields.

Prerequisites:

All code examples and applications will be done in R. The course requires basic knowledge of R, which includes being able to load and work with data. The code examples are based on the tidyverse (e.g. filter, mutate, summarise functions), but can be adjusted to base R without much trouble. No special mathematical knowledge beyond master level statistics and quantitative methods courses is required, the course focuses on the concepts of machine learning algorithms rather than the mathematical basis. The examples and lab session don’t require any in-depth knowledge of political science or any other field.

Date & time: 18 - 22 March 2024, 9.30 a.m. - 1.00 p.m.

Location: Room tba. - Feldkirchenstraße 21

Instructor: Dr Jens Wäckerle, University of Cologne

Jens Wäckerle is a post-doctoral researcher at the Cologne Center for Comparative Politics and currently the substitute professor at the Chair of European Politics. His research focuses on women in politics, legislative politics, quantitative text analysis and the European Union. He holds a Master degree from the University of Essex and a PhD from the University of Cologne.

Course units: 20

Registration: Please register via this form by February 26, 2024.

Workshop: "Introduction to Git for Social Scientists - Enhancing Reproducibility, Visibility, and Team Collaboration" (12.04.2024, 09.30 a.m. to 05.00 p.m. (s.t.))

Workshop: "Introduction to Git for Social Scientists - Enhancing Reproducibility, Visibility, and Team Collaboration" (12.04.2024, 09.30 a.m. to 05.00 p.m. (s.t.))

This workshop is organised by BAGSS.

Course Outline:

In this beginner's Git workshop, discover the essentials of version control crucial for social scientists. No prior experience is needed; we start with basics, covering principles, installing Git, and fundamental commands. Gain hands-on experience in tracking changes for enhanced reproducibility. Learn effective code communication for collaboration and set up your profile homepage for increased visibility.
Key Features:

  • Beginner-friendly Git introduction
  • Create a Git profile/homepage
  • Optimize collaborative workflows
  • Practical exercises, and comprehensive materials for efficient learning.

Tailored for beginners, this workshop provides a robust foundation in collaborative research. Ideal for Stata, R, and Python users at all levels.

Date & time:

Friday, April 12th, 2024, 09.30 a.m. to 12.45 p.m. (s.t.) & 01.45 p.m. to 05.00 p.m. (s.t.)

Location: BAGSS, Feldkirchenstraße 21, 96050 Bamberg, Room FG1/00.06

Instructor: Dr Diana Schacht, German Youth Institute

Dr Diana D. Schacht is a senior quantitative researcher at the German Youth Institute (DJI) Munich, specializing in early education quality, migration and integration research, and survey methodologies, including strategies to reduce or correct for survey bias. Dr Schacht has extensive experience collaborating on various surveys in large teams.

Course units: 8

Registration: Please register via this form by April 1st, 2024.

Workshop: "Cluster Analysis and Latent Class Analysis" (06.05.2024, 09.00 a.m. to 05.00 p.m. (s.t.) & 07.05.2024, 01.00 p.m. to 05.00 p.m. (s.t.))

Workshop: "Cluster Analysis and Latent Class Analysis" (06.05.2024, 09.00 a.m. to 05.00 p.m. (s.t.) & 07.05.2024, 01.00 p.m. to 05.00 p.m. (s.t.))

This workshop is organised by BAGSS.

Short Outline:

This course offers a practical introduction to identifying groups in your data.
When confronted with large datasets containing numerous variables, casual browsing or superficial data examination will be insufficient for discovering similar cases that may form groups.
Cluster analysis and latent class analysis will be helpful in these cases.

Cluster analysis is a bottom-up approach, which employs different algorithms to identify similar
cases within the data, such as individuals or organizations, resulting in distinct clusters. Cluster
analysis is a type of unsupervised machine learning.
Latent class analysis follows a top-down approach by assuming a probabilistic model to explain
group membership. It utilizes the data distribution and allows for the inclusion of covariates,
providing goodness of fit measures that facilitate the comparison of different solutions.
We will cover hierarchical cluster analysis, non-hierarchical clustering, fuzzy clustering, latent
class analysis, as well as latent profile analysis and longitudinal applications.
Upon completion of this course, participants will have a good understanding of the possibilities
and challenges of cluster analysis and latent class analysis.

Prerequisites:

Participants should be familiar with multivariate statistics. If you have never been exposed to ttests, ANOVA, and (OLS) regression, this is not the course for you. We will use the software R
and R Studio for demos and short exercises. While some familiarity with R is useful, this is not
strictly necessary if you have some knowledge of working with other statistical software packages using syntax (e.g., Mplus, Stata, etc.) and are willing to learn. If you have never used R and R Studio or have not used them for some time, please install/update them and have a little look around before the first day of the course.
You will find some helpful materials here: https://stats.idre.ucla.edu/r/

Maximum number of participants: 16

Date & time: Monday, 06.05.2024; 09.00 a.m. - 5.00 p.m. (s.t.) &

                      Tuesday 07.05.2024 1.00 p.m.  - 5.00 p.m. (s.t.)

Location: BAGSS, Feldkirchenstraße 21, 96050 Bamberg, Room FG1/00.06

Lecturer: Professor Dr Robin Samuel, University of Luxembourg

Robin Samuel has been an Associate Professor at the Department of Social Sciences at the University of Luxembourg since 2016, where he was appointed Head of the Centre for Childhood
and Youth Research in 2020. His research is mainly concerned with the collection and analysis
of large data sets. In some projects, he also applies experimental designs and qualitative methods.
He is currently investigating the appropriateness of certain statistical models to study social
inequalities in a range of health outcomes. His substantive research interests include social inequality, work, health, well-being, and sustainability, often with a focus on young people.

Course units: 12

Registration: Please register via this form by April 8, 2024.

Online-Workshop "Literaturverwaltung mit Zotero" (06.05.2024, 10:00 bis 12:00 Uhr)

Online-Workshop "Literaturverwaltung mit Zotero" (06.05.2024, 10:00 bis 12:00 Uhr)

Inhalt:

Beim Verfassen einer längeren wissenschaftlichen Arbeit ist es wichtig, den Überblick über gelesene und zitierte Texte zu behalten. Auch die Formatierung der Literaturangaben wird mit zunehmender Quellenanzahl immer zeitaufwändiger.

Literaturverwaltungsprogramme können bei diesen Aufgaben unterstützen und bieten zahlreiche weitere Funktionen an, die die wissenschaftliche Arbeit erleichtern können. An der Universität Bamberg wird dazu vor allem das Open-Source-Literaturverwaltungsprogramms verwendet. Dennoch stellt sich oft die Frage: Brauche ich so etwas überhaupt?

•             Überblick: Wie können Literaturverwaltungsprogramme im Forschungsprozess unterstützen? Wann ist es sinnvoll, ein Literaturverwaltungsprogramm zu verwenden?

•             Grundlagen der Literaturverwaltung mit Zotero: Literaturangaben sammeln und verwalten, sinnvolle Programmeinstellungen

•             Wissensmanagement mit Zotero: Arbeit mit PDFs, Zitaten, Tags und Kommentaren

•             Zusammenspiel von Zotero und Textsatz/-verarbeitungsprogramm: Literaturangaben einfügen, Literaturverzeichnis erstellen, Zitierstile

•             Literaturverwaltungs-Support an der Uni Bamberg

Ablauf:

Vortrag mit Präsentation und Vorführung sowie praktischen Übungen

Lernziele:

Die Teilnehmenden

•             wissen, wozu Literaturverwaltungsprogramme verwendet werden können und können einschätzen, ob der Einsatz eines Literaturverwaltungsprogramms für sie persönlich sinnvoll ist,

•             können in Zotero Literaturangaben anlegen und mit PDF-Dokumenten verknüpfen,

•             kennen die Grundlagen des Wissensmanagements mit Zotero und können Zitate und Anmerkungen aus Zotero in ein Textsatz-/verarbeitungsprogramm exportieren,

•             können mit Zotero ein Literaturverzeichnis im gewünschten Zitierstil erstellen,

•             wissen, wohin sie sich bei Fragen zu Literaturverwaltungsthemen wenden können.

Zielgruppe: Promovierende, Postdocs

Zeit: 06.05.2024, 10:00 bis 12:00 Uhr

Arbeitseinheiten: 2 AE

Ort: https://uni-bamberg.zoom-x.de/j/62769318039 ; der Kenncode wird nach Anmeldung, kurz vor dem Workshop bereitgestellt.

Workshopleitung: Louise Rumpf, M.A. (Universitätsbibliothek)

Louise Rumpf ist Fachreferentin für Politikwissenschaft und Soziologie und Leiterin der Teilbibliothek 3 (Sozial- und Wirtschaftswissenschaften).

Anmeldung: Bitte melden Sie sich bis spätestens 22.04.2024 über dieses Formular an.

Online-Workshop: "Academic Writing with AI Tools" (13.05.2024, 09.30 a.m. to 10.00 a.m. (s.t.), 10.06.2024, 09.00 a.m. to 01.00 p.m. (s.t.) & 01.07.2024, 09.00 a.m. to 01.00 p.m. (s.t.))

Online-Workshop: "Academic Writing with AI Tools" (13.05.2024, 09.30 a.m. to 10.00 a.m. (s.t.), 10.06.2024, 09.00 a.m. to 01.00 p.m. (s.t.) & 01.07.2024, 09.00 a.m. to 01.00 p.m. (s.t.))

This workshop is organised by BAGSS.

Course Outline:

In this workshop, participants will get an overview of the possibilities of using AI tools for academic writing. The course is divided into a short kick-off session, two synchronous and two asynchronous phases.

In the first asynchronous phase, participants will familiarize themselves with AI tools and receive input on how they work and what opportunities and risks arise for academic writing when working with them. The first synchronous online workshop day will be used to discuss these findings. In teams, the participants research the possible applications such as literature research, text corrections or text production.

The second self-learning phase consists of trying out these tools for themselves. Participants receive input by email and can apply the knowledge to their own academic writing, with the opportunity to receive individual feedback.

The workshop concludes with a second synchronous online workshop in which the results of the asynchronous phase can be discussed and the weaknesses and strengths of the tools can be evaluated.

Date & time:

Monday, 13 May, 2024, 09.30 a.m. to 10.00 a.m. (s.t.) [Kick-Off]&

Monday, 10 June, 2024, 09.00 a.m. to 01.00 p.m. (s.t.) [1st Workshop Day] &

Monday, 01 July, 2024, 09.00 a.m. to 01.00 p.m. (s.t.) [2nd Workshop Day]

Location:Online via Zoom

Instructor:Dr Sabrina Sontheimer, kommkult

Dr Sabrina Sontheimer studied Literature, Linguistics and Theater at the LMU in Munich. She has a PhD in English Literature and she worked as scientific fellow and lecturer at the Chair for English Philology in LMU, with a 10-year experience in university teaching. She is a certified trainer in communications, in university teaching with a specialization on virtual teaching, and in academic writing.

Course units: 8

Registration: Please register via this form by April 9, 2024.

Workshop: "Wie schreibe ich ein überzeugendes Exposé?" (17.05.2024, 9:00 bis 13:30 Uhr)

Workshop: "Wie schreibe ich ein überzeugendes Exposé?" (17.05.2024, 9:00 bis 13:30 Uhr)

Inhalte:

Die Erstellung eines Exposés für eine Stipendienbewerbung stellt Promovierende in der Anfangsphase oft vor fast unlösbare Aufgaben: Wie kann ich erklären, was ich selbst noch erforschen will? Wie kann ich überzeugend darlegen, dass ich einen Weg zum Ziel „Dissertation“ kenne, der für mich selbst oft genug noch nicht klar erscheint?

In diesem Workshop wollen wir Antworten auf diese Fragen finden, indem wir uns bewusst machen, was das Ziel eines Exposés ist und wie dieses durch einen klaren Aufbau, spezifische sprachliche Mittel und die Erstellung eines überzeugenden Zeitplans erreicht werden kann.

Ablauf:

  • Für wen schreibe ich das Exposé?
  • Adressatengerechter Textaufbau
  • Eingrenzung des Themas
  • Gliederung des Exposés
  • Umgang mit Unsicherheiten
  • Sprachliche Tipps & Tricks
  • Zeitplanerstellung für das Exposé

Methode:

Die Trainerin gibt kurze Inputs über das Ziel eines Exposés und wie die Teilnehmenden dieses durch eine sinnvolle Vorstrukturierung der fachlichen Inhalte und eine geeignete sprachliche Darstellung erreichen können. Diese Inhalte üben die Teilnehmenden in kurzen Aufgabensequenzen selbstständig ein. In der Arbeit in Kleingruppen wird das Gelernte auf die Promotionsvorhaben der Teilnehmenden übertragen.

Lernziele:

  • Geeigneten Arbeitstitel formulieren
  • Das eigene Exposé überzeugend aufbauen
  • Die eigenen Gedanken klar formulieren
  • Einen Zeitplan für das Dissertationsvorhaben erstellen

Maximale Teilnehmerzahl: 12 Personen

Zielgruppe: Promovierende und Master-Studierende mit der Absicht zu promovieren

Termin: 17.05.2024, 9:00 bis 13:30 Uhr (s.t.), inkl. 30 Minuten Pause

Arbeitseinheiten: 4

Ort: U5/02.17

Leitung: Alisa Müller, M.A.

Alisa Müller arbeitet in Nürnberg als Redakteurin und seit zehn Jahren als freie Journalistin für verschiedene Printmedien. Sie hat in der slavischen Sprachwissenschaft an der Universität Bamberg promoviert.

Anmeldung: Bitte melden Sie sich bis zum 03.05.2024 über dieses Formular an.

Online-Workshop: "Professionell recherchieren" (24.05.2024, 10:00 bis 12:00 Uhr)

Online-Workshop: "Professionell recherchieren" (24.05.2024, 10:00 bis 12:00 Uhr)

Inhalte:

Der Workshop stellt Strategien für die Suche nach wissenschaftlichen Texten in Fachdatenbanken und im Internet vor: Wie verschafft man sich einen möglichst vollständigen Literaturüberblick zu einem Thema? Wo sucht man am besten? Wie kann man besonders relevante Texte identifizieren und wissenschaftliche Debatten nachvollziehen?

Die Teilnehmerinnen und Teilnehmer üben, komplexe Suchanfragen zu ihren Themen zu formulieren und lernen Strategien kennen, um auch bei längeren Arbeiten in Bezug auf relevante Literatur auf dem Laufenden zu bleiben.

Ablauf:

Vortrag mit Präsentation und Vorführung sowie einem Übungsteil

Lernziele:

  • Formulieren komplexer Suchanfragen
  • Kennenlernen spezieller Suchmaschinen
  • Nutzung von Zitationsdatenbanken
  • Einsatz von Alert-Funktionen

Voraussetzung für die Teilnahme: VPN-Verbindung

Zielgruppe: Promovierende, Postdocs

Termin: Freitag, 24.05.2024, 10:00 bis 12:00 Uhr

Arbeitseinheiten: 2 AE

Ort: https://uni-bamberg.zoom-x.de/j/61045152527 ; der Kenncode wird nach Anmeldung, kurz vor dem Workshop bereitgestellt.

Leitung:

Louise Rumpf, M.A.

Louise Rumpf ist Fachreferentin für Politikwissenschaft und Soziologie und Leiterin der Teilbibliothek 3 (Sozial- und Wirtschaftswissenschaften).

Anmeldung: Bitte melden Sie sich bis spätestens 10.05.2024 über dieses Formular an.

Workshop: "Multiple Imputation with STATA – Basics" (03.06.2024, 09.00 a.m. to 05.00 p.m. (s.t.) & 04.06.2024, 1.00 p.m. to 05.00 p.m. (s.t.))

Workshop: "Multiple Imputation with STATA – Basics" (03.06.2024, 09.00 a.m. to 05.00 p.m. (s.t.) & 04.06.2024, 1.00 p.m. to 05.00 p.m. (s.t.))

This workshop is organised by BAGSS.

Course Outline:

Complete case analysis (also known as “listwise deletion”), the traditional way of dealing with missing data in quantitative social science, excludes every observation with missing information on at least one variable of interest. While easy to implement, this approach is wasteful and can lead to biased estimates. Multiple imputation (MI) can provide more efficient and unbiased estimates when certain conditions are met. The course will introduce participants to the basic concepts and statistical foundations of MI and to common challenges arising in real-life applications. Hands-on exercises in Stata will show participants how to implement MI in simple settings with cross-sectional data.

Prerequisites:

Participants should have a basic understanding of probability theory, good familiarity with regression analysis, and good working knowledge of Stata. Participants who are not familiar with Stata may still benefit from the course but will likely find some of the hands-on exercises quite challenging.

Maximum number of participants: 16

Date & time:

Monday, 03 June 2024, 09.00 a.m. to 05.00 p.m. (s.t.) & Tuesday, 04 June 2024, 1.00 p.m. to 05.00 p.m. (s.t.)

Location: BAGSS, Feldkirchenstraße 21, 96050 Bamberg, Room FG1/00.06

Instructor: Professor Dr Jan Paul Heisig, Berlin Social Science Center (WZB)

Jan Paul Heisig is head of the “Health and Social Inequality” research group at WZB Berlin Social Science Center and Professor of Sociology at Freie Universität Berlin. His research focuses on social inequalities in health, education, and the labor market as well as quantitative methods. He regularly teaches courses on multiple imputation, analysis of multilevel data, and other topics in statistics and data analysis.

Course units: 12

Registration: Please register via this form by May 06, 2024.

Workshop: "Multiple Imputation with STATA – Advanced topics, incl. longitudinal and multilevel data" (21.06.2024, 09.00 a.m. to 05.00 p.m. (s.t.))

Workshop: "Multiple Imputation with STATA – Advanced topics, incl. longitudinal and multilevel data" (21.06.2024, 09.00 a.m. to 05.00 p.m. (s.t.))

This workshop is organised by BAGSS.

Course Outline:

This one-day course will take a closer look at practically important issues arising in morecomplex, yet common applications of Multiple Imputation. A major focus will be onapplications with hierarchical data structures, including longitudinal (e.g., household panels) as well as multilevel data with both larger (e.g., countries) and smaller groups (e.g., schools or classrooms).

Prerequisites:

Participants should be familiar with the basics of multiple imputation of cross-sectional data and its implementation Stata. Basic expertise in the analysis of longitudinal and/or multilevel data is strongly recommended. Participants who are not familiar with Stata may still benefit from the course but will likely find some of the hands-on exercises quite challenging.

Maximum number of participants: 16

Date & time: Friday, 21 June 2024, 09.00 a.m. to 05.00 p.m. (s.t.)

Location: BAGSS, Feldkirchenstraße 21, 96050 Bamberg, Room FG1/00.06

Instructor: Professor Dr Jan Paul Heisig, Berlin Social Science Center (WZB)

Jan Paul Heisig is head of the “Health and Social Inequality” research group at WZB Berlin Social Science Center and Professor of Sociology at Freie Universität Berlin. His research focuses on social inequalities in health, education, and the labor market as well as quantitative methods. He regularly teaches courses on multiple imputation, analysis of multilevel data, and other topics in statistics and data analysis.

Course units: 8

Registration: Please register via this form by May 06, 2024.

Online-Kurs "Publikation der Dissertation mit Tessa Sauerwein und Barbara Ziegler (Universitätsbibliothek Bamberg)" (18.06.2024, 14:00 bis 15:00 Uhr)

Online-Kurs "Publikation der Dissertation mit Tessa Sauerwein und Barbara Ziegler (Universitätsbibliothek Bamberg)" (18.06.2024, 14:00 bis 15:00 Uhr)

Online-Publikation oder Verlag? Was muss ich bei der Veröffentlichung der Dissertation beachten? Der Vortrag beleuchtet die Vor- und Nachteile verschiedener Publikationsmodelle und Verlagsformen, geht auf Besonderheiten kumulativer Dissertationen ein, und spricht Urheber- und vertragsrechtliche Fragen an. Am Beispiel der „University of Bamberg Press“ werden auch die Vorteile des sogenannten hybriden Publizierens thematisiert.

Zielgruppe: Promovierende

Zeit: 18.06.2024, 14:00 bis 15:00 Uhr

Arbeitseinheiten: 2 AE

Ort: https://uni-bamberg.zoom-x.de/j/93383947701 ; der Kenncode wird nach der Anmeldung, kurz vor dem Workshop bereitgestellt

Kursleitung: Tessa Sauerwein und Barbara Ziegler, Universitätsbibliothek Bamberg

Tessa Sauerwein, M.A., berät Promovierende zur Veröffentlichung der Dissertation und bearbeitet die Dissertationen innerhalb des Sachgebiet Forschungs- und Publikationsservices der Universitätsbibliothek Bamberg.

Dipl.-Volkswirtin Barbara Ziegler leitet das Sachgebiet Forschungs- und Publikationsservices der Universitätsbibliothek Bamberg und ist Geschäftsführerin der „University of Bamberg Press“.

Anmeldung: Bitte melden Sie sich bis spätestens 04.06.2024 über dieses Formular an.

Dies ist ein Angebot der Universitätsbibliothek.