Publishing Analytics Tracker – PANTER; Teilvorhaben: Implementierung des Systems

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The PANTER project establishes a reliable, publicly available monitor for funding models, prices and price developments in the OA journal market. It thus aims to address one of the major information gaps that stand in the way of a sustainable and innovation-friendly OA transformation. Although the importance of prices and costs can hardly be overestimated, the OA publication market lacks what has long been established in most market segments: comparison portals that make prices for products and services transparent and comparable. Article processing charges, submission fees, etc. represent financial barriers that determine whether a research result can be published in OA or not. Scientists who plan their publications, as well as funding bodies and libraries that decide on budgets and negotiate contracts, are therefore dependent on valid price information. However, there is a lack of suitable comparison tools. In turn, the individual search is time-consuming and quickly overwhelms due to the heterogeneous price structures. The price monitor that is being developed in the project fills this gap. It enables all stakeholders in OA publishing to view and compare prices for publication services. It has a user interface that is optimized to meet the needs of the relevant stakeholders. In addition to the current data, it also makes medium- and long-term trends visible and creates transparency in the pricing policy on the publication market.

Related Publications

Keck, M., Stoll, E., Kammer, D. (2021). A Didactic Framework for Analyzing Learning Activities to Design InfoVis Courses. In: IEEE Computer Graphics and Applications. https://doi.org/10.1109/MCG.2021.3115416

Kammer, D., Stoll, E., Urban, A. (2021). Experience of Teaching Data Visualization using Project-based Learning. In: VisActivities: 2nd IEEE VIS Workshop on Data Vis Activities to Facilitate Learning, Reflecting, Discussing, and Designing, held in conjunction with IEEE VIS 2021. http://visactivities.github.io/. http://arxiv.org/abs/2111.04428

Keck, M., Kammer, D., Ferreira, A., Giachetti, A., Groh, R. (2020). VIDEM 2020: Workshop on Visual Interface Design Methods. In: AVI '20: Proceedings of the International Conference on Advanced Visual Interfaces. https://doi.org/10.1145/3399715.3400863

Kammer, D., Keck, M., Gründer, T., Maasch, A., Thom, T., Kleinsteuber, M., Groh, R. (2020). Glyphboard: Visual Exploration of High-dimensional Data Combining Glyphs with Dimensionality Reduction. In: IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2020.2969060

Vosough, Z., Kammer, D., Keck, M., Groh, R. (2019). Visualization approaches for understanding uncertainty in flow diagrams. In: Journal of Computer Languages. http://doi.org/10.1016/j.cola.2019.03.002

Vosough, Z., Kammer, D., Keck, M., Groh, R. (2018). Mirroring Sankey Diagrams for Visual Comparison Tasks. In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and applications. https://doi.org/10.5220/0006651203490355

Keck, M., Kammer, D. (2018). Exploring Visualization Challenges for Interactive Recommender Systems. In: Proceedings of VisBIA 2018 – Workshop on Visual Interfaces for big Data environments in Industrial applications, International Working Conference on advanced Visual Interfaces. http://ceur-ws.org/Vol-2108/paper3.pdf

Keck, M., Kammer, D., Groh, R. (2018). Visual Version Comparison of Multidimensional Data Sets Using Glyphs. In: IEEE VIS 2018 Posters. http://ieeevis.org/year/2018/info/posters

Kammer, D., Keck, M., Both, A., Jacucci, G., Groh, R. (2018). VisBIA 2018 – Workshop on Visual Interfaces for Big Data Environments in Industrial Applications. In: Proceedings of the 2018 International Working Conference on advanced Visual Interfaces. https://doi.org/10.1145/3206505.3206603

Kammer, D., Keck, M., Gründer, T., Groh, R. (2018). Big Data Landscapes: Improving the Visualization of Machine Learning-based Clustering Algorithms. In: Proceedings of the 2018 International Working Conference on advanced Visual Interfaces. https://doi.org/10.1145/3206505.3206556

Vosough, Z., Kammer, D., Keck, M., Groh, R. (2017). Visualizing Uncertainty in Flow Diagrams: A Case Study in Product Costing. In: Proceedings of VINCI ’17. https://doi.org/10.1145/3105971.3105972

Keck, M., Kammer, D., Gründer, T., Thom, T., Kleinsteuber, M., Maasch, A., Groh, R. (2017). Towards Glyph-based Visualizations for Big Data Clustering. In: Proceedings of VINCI ’17. https://doi.org/10.1145/3105971.3105979

Wojdziak, J., Kirchner, B., Kammer, D., Herrmann, M., Groh, R. (2016). Towards a Visual Data Language to Improve Insights into Complex Multidimensional Data. In: Human Interface and the Management of Information: Information, Design and Interaction. https://doi.org/10.1007/978-3-319-40349-6_20

Both, A., Nguyen, V., Keck, M., Herrmann, M., Kammer, D., Groh, R., Henkens, D. (2014). Motive-based Search using a Recommendation-driven Visual Divide and Conquer Approach. In: IADIS International Journal on WWW/Internet. http://www.iadisportal.org/ijwi/papers/2014121208.pdf

Keck, M., Kammer, D., Iwan, R., Groh, R., Taranko S. (2011). DelViz: Exploration of Tagged Information Visualizations. In: Informatik 2011 - Interaktion und Visualisierung im Daten-Web. https://www.user.tu-berlin.de/komm/CD/paper/060514.pdf

Keck, M., Koalick, G., Kammer, D., Taranko, S., Wojdziak, J. (2011). DelViz: Ein Werkzeug zur Exploration von Visualisierungen. In: Wieder mehr sehen! - Aktuelle Einblicke in die Technische Visualistik. https://t1p.de/ndv8

Keck, M., Kammer, D., Wojdziak, J., Taranko, S., Groh, R. (2010). DelViz: Untersuchen von Visualisierungsformen durch eine Klassifizierung beruhend auf Social Tagging. In: Virtual enterprises, Communities & social networks: Workshop GeneMe ’10 Gemeinschaften in neuen Medien. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-142838