2019

  1. A

    1. A. Akhmerov et al., “Raising the Profile of Research Software: Recommendations for Funding Agencies and Research Institutions.” 2019.
    2. P. Alliez et al., “Attributing and Referencing (Research) Software: Best Practices and Outlook from Inria,” 2019.
  2. B

    1. M. Ballhausen, “Free and Open Source Software Licenses Explained.,” IEEE Computer, vol. 52, no. 6, pp. 82–86, 2019, [Online]. Available: http://dblp.uni-trier.de/db/journals/computer/computer52.html#Ballhausen19.
    2. J. Baz, C. Held, J. Pleiss, and N. Hansen, “Thermophysical properties of glyceline–water mixtures investigated by molecular modelling,” Phys. Chem. Chem. Phys., vol. 21, no. 12, pp. 6467–6476, 2019, doi: 10.1039/C9CP00036D.
    3. R. Bertacco et al., “UNIVERSITIES OF S&T AS ENGINES OF EXCELLENCE, TALENT AND INNOVATION ROLES IN RESEARCH AND INNOVATION INFRASTRUCTURES.” 2019.
    4. P. Buchfink, A. Bhatt, and B. Haasdonk, “Symplectic Model Order Reduction with Non-Orthonormal Bases,” 2019.
  3. C

    1. X. Chen et al., “Open is not enough,” Nature Physics, vol. 15, no. 2, pp. 113--119, 2019, doi: 10.1038/s41567-018-0342-2.
  4. D

    1. S. Dresden, Ed., “Rechteauszeichnung im SLUB Langzeitarchiv,” Jan. 2019, [Online]. Available: https://www.slub-dresden.de/fileadmin/groups/slubsite/SLUBArchiv/SLUBArchiv_Diskussionspapier_Rechteauszeichnung_v1.0.pdf.
    2. D. Driess, S. Schmitt, and M. Toussaint, “Active Inverse Model Learning with Error and Reachable Set Estimates,” in Proc. of the IEEE Int. Conf. on Intelligent Robotsand Systems (IROS), 2019, doi: 10.1109/IROS40897.2019.8967858.
  5. E

    1. C. Elsner, N. Rosenke, M. Weber, C. Hoppe, S. Drößler, and S. Hermann, “Von Bottom up zu Top down. Umfrage: Forschende der Ingenieurwissenschaften erwarten klare Rahmenbedingungen von den Hochschulleitungen bei Open Access und Open Educational Resources,” o-bib. Das offene Bibliotheksjournal / Herausgeber VDB, vol. 6, no. 2, 2019, doi: 10.5282/o-bib/2019H2S80-91.
    2. C. Erdmann et al., “Top 10 FAIR Data & Software Things.” 2019, doi: 10.5281/zenodo.2555498.
  6. G

    1. T. Gomez-Diaz and T. Recio, “On the evaluation of research software: the CDUR procedure,” F1000Research, vol. 8, p. 1353, 2019, doi: 10.12688/f1000research.19994.2.
    2. D. Grunert, J. Fehr, and B. Haasdonk, “Well-scaled, A-posteriori Error Estimation for Model Order Reduction of Large Second-order Mechanical Systems,” International Journal for Numerical Methods in Engineering, 2019.
    3. M. Gärtner, “RePlay-DH Process Metadata Schema.” 2019, doi: https://doi.org/10.18419/darus-474.
    4. M. Gärtner, “RePlay-DH Client v1.3.0.” 2019, doi: https://doi.org/10.18419/darus-475.
  7. H

    1. M. Hammer, M. Günther, D. F. B. Haeufle, and S. Schmitt, “Tailoring anatomical muscle paths: a sheath-like solution for muscle routing in musculoskeletal computer models,” Mathematical Biosciences, vol. 311, pp. 68–81, 2019, doi: https://doi.org/10.1016/j.mbs.2019.02.004.
    2. W. Hasselbring, L. Carr, S. Hettrick, H. Packer, and T. Tiropanis, “FAIR and Open Computer Science Research Software,” arXiv preprint arXiv:1908.05986. 2019, [Online]. Available: http://dblp.uni-trier.de/db/journals/corr/corr1908.html#abs-1908-05986.
    3. S. Hermann, D. Iglezakis, and A. Seeland, “Requirements for Finding Research Data and Software,” PAMM, 2019, doi: 10.1002/pamm.201900480.
    4. L. Hsu, V. B. Hutchison, and M. L. Langseth, “Measuring sustainability of seed-funded earth science informatics projects,” PLOS ONE, vol. 14, no. 10, pp. 1–25, Oct. 2019, doi: 10.1371/journal.pone.0222807.
  8. I

    1. D. Ivanović, B. Schmidt, R. Grim, and A. Dunning, “FAIRness of Repositories & Their Data: A Report                    from LIBER’s Research Data Management Working                    Group.” Zenodo, 2019, doi: 10.5281/zenodo.3251593.
  9. J

    1. A. N. Johanson and W. Hasselbring, “Software Engineering for Computational Science.,” in SE/SWM, 2019, vol. P-292, pp. 43–44, [Online]. Available: http://dblp.uni-trier.de/db/conf/se/se2019.html#JohansonH19.
  10. K

    1. N. K. Karadimitriou, H. Mahani, H. Steeb, and V. Niasar, “Nonmonotonic Effects of Salinity on Wettability Alteration and Two-Phase Flow Dynamics in PDMS Micromodels,” Water Resources Research, vol. 55, no. 11, pp. 9826--9837, 2019, doi: 10.1029/2018wr024252.
    2. T. Kreutzer and H. Lahmann, Rechtsfragen bei Open Science. Hamburg University Press, 2019.
    3. K. Kuritz, S. Zeng, and F. Allgöwer, “Ensemble Controllability of Cellular Oscillators,” IEEE Control Systems Letters, vol. 3, no. 2, pp. 296–301, 2019, doi: 10.1109/LCSYS.2018.2870967.
    4. K. Kuritz, D. Stöhr, D. Maichl, N. Pollak, M. Rehm, and F. Allgöwer, “Reconstructing temporal and spatial dynamics in single-cell experiments,” bioRxiv, 2019, doi: 10.1101/697151.
  11. L

    1. A.-L. Lamprecht et al., “Towards FAIR principles for~research~software,” Data Science, pp. 1--23, 2019, doi: 10.3233/ds-190026.
    2. K. Li, P.-Y. Chen, and E. Yan, “Challenges of measuring software impact through citations: An examination of the lme4 R package,” Journal of Informetrics, vol. 13, no. 1, pp. 449--461, 2019, doi: 10.1016/j.joi.2019.02.007.
    3. S. Linsenmayer, M. A. Müller, H. Ishii, and F. Allgöwer, “Event-based Containability for Linear Systems with Arbitrarily Small Bit Rates,” in Proc. 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), Chicago, IL, USA, 2019, pp. 31–36, doi: 10.1016/j.ifacol.2019.12.138.
    4. S. Linsenmayer, B. W. Carabelli, F. Dürr, J. Falk, F. Allgöwer, and K. Rothermel, “Integration of Communication Networks and Control Systems Using a Slotted Transmission Classification Model,” in Proc. IEEE Annual Consumer Communications Networking Conf. (CCNC), Las Vegas, NV, USA, 2019, pp. 1–6, doi: 10.1109/CCNC.2019.8651811.
    5. S. Linsenmayer, D. V. Dimarogonas, and F. Allgöwer, “Periodic event-triggered control for networked control systems based on non-monotonic Lyapunov functions,” Automatica, vol. 106, pp. 35--46, 2019, doi: 10.1016/j.automatica.2019.04.039.
  12. Q

    1. B. Quintal, E. Caspari, K. Holliger, and H. Steeb, “Numerically quantifying energy loss caused by squirt flow,” Geophysical Prospecting, vol. 67, no. 8, pp. 2196–2212, 2019, doi: 10.1111/1365-2478.12832.
  13. R

    1. M. F. Rehme and D. Pflüger, “Hierarchical Extended B-splines for Approximations on Sparse Grids,” Sparse Grids and Applications 2018, Springer, 2019.
    2. M. F. Rehme, F. Franzelin, and D. Pflüger, “B-Splines on Sparse Grids for Surrogates in Uncertainty Quantification,” Reliability Engineering and System Safety, Elsevier, Radarweg 29, 1043 NX Amsterdam, The Netherlands, 2019.
    3. T. Reichenbach, P. Tempel, A. Verl, and A. Pott, “Static Analysis of a Two-Platform Planar Cable-Driven Parallel Robot with Unlimited Rotation,” in Proceedings of the Fourth International Conference on Cable-Driven Parallel Robots, 2019.
  14. S

    1. G. Santin and B. Haasdonk, “Kernel Methods for Surrogate Modeling,” 2019.
    2. K. Scheliga et al., “Dealing with research software: Recommendations for best practices,” 2019, doi: 10.2312/OS.HELMHOLTZ.003.
    3. P. Schmidt and H. Steeb, “Numerical aspects of hydro-mechanical coupling of fluid-filled fractures using hybrid-dimensional element formulations and non-conformal meshes,” GEM - International Journal on Geomathematics, vol. 10, no. 1, p. 14, 2019, doi: 10.1007/s13137-019-0127-5.
    4. S. Schmitt, M. Günther, and D. F. Häufle, “The dynamics of the skeletal muscle: A systems biophysics perspective on muscle modeling with the focus on Hill-type muscle models,” GAMM-Mitteilungen, p. e201900013, 2019.
    5. S. Scholtens et al., “Life sciences data steward function matrix.” Zenodo, 2019, doi: 10.5281/zenodo.2561723.
    6. S. Scholtens et al., “Final report: Towards FAIR data steward as                    profession for the lifesciences. Report of a ZonMw                    funded collaborative approach built on existing                    expertise.” Zenodo, 2019, doi: 10.5281/zenodo.3474789.
    7. S. Scholtens et al., “Function and competencies matrices for three types                    of data stewards 'policy', 'research' and                    'infrastructure'” Zenodo, 2019, doi: 10.5281/zenodo.3490855.
    8. A. Siepel, “Challenges in funding and developing genomic software: roots and remedies,” Genome Biology, vol. 20, no. 1, pp. 147--, 2019, doi: 10.1186/s13059-019-1763-7.
    9. C. Staiger et al., “Data stewards function landscape and its                    stakeholders.” Zenodo, 2019, doi: 10.5281/zenodo.3460552.
    10. H. Steeb and J. Renner, “Mechanics of Poro-Elastic Media: A Review with Emphasis on Foundational State Variables,” Transport in Porous Media, vol. 120, no. 2, pp. 437–461, 2019, doi: 10.1007/s11242-019-01319-6.
  15. T

    1. Task Group Forschungssoftware Des Arbeitskreises Open Science Der Helmholtz-Gemeinschaft, “Muster-Richtlinie Nachhaltige Forschungssoftware an den Helmholtz-Zentren,” 2019, doi: 10.2312/OS.HELMHOLTZ.007.
    2. P. Tempel, D. Lee, F. Trautwein, and A. Pott, “Modeling of Elastic-Flexible Cables with Time-Varying Length for Cable-Driven Parallel Robotsj,” in Proceedings of the Fourth International Conference on Cable-Driven Parallel Robots, 2019.
  16. V

    1. S. van de Sandt et al., “Practice meets Principle: Tracking Software and Data Citations to Zenodo DOIs.,” CoRR, vol. abs/1911.00295, 2019, [Online]. Available: http://dblp.uni-trier.de/db/journals/corr/corr1911.html#abs-1911-00295.
    2. I. Verheul, M. Imming, J. Ringerma, A. Mordant, J.-L. van der Ploeg, and M. Pronk, “Data Stewardship on the map: A study of tasks and                    roles in Dutch research institutes.” Zenodo, 2019, doi: 10.5281/zenodo.2669150.
    3. VSNU, NFU, KNAW, NWO and ZonMw, Ed., “Room for everyone’s talent.” 2019.
  17. W

    1. C. Wiljes and P. Cimiano, “Teaching Research Data Management for Students,” Data Science Journal, vol. 18, no. 1, p. 38, 2019, doi: http://doi.org/10.5334/dsj-2019-038.
    2. M. Wu, F. Psomopoulos, S. J. Khalsa, and A. de Waard, “Data Discovery Paradigms: User Requirements and Recommendations for Data Repositories,” Data Science Journal, vol. 18, 2019, [Online]. Available: https://doi.org/10.5334%2Fdsj-2019-003.
  18. Z

    1. H. Zhang, S. Frey, H. Steeb, D. Uribe, T. Ertl, and W. Wang, “Visualization of Bubble Formation in Porous Media,” IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 1, pp. 1060–1069, 2019, doi: 10.1109/TVCG.2018.2864506.
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