Literatur

Sie wollen tiefer einsteigen? Aktuelle Literaturempfehlungen zum Thema Forschungsdatenmanagement.

Rechtliche Fragestellungen

  1. Brettschneider, P., Axtmann, A., Böker, E., & von Suchodoletz, D. (2021). Offene Lizenzen für Forschungsdaten - Rechtliche Bewertung und Praxistauglichkeit verbreiteter Lizenzmodelle. O-Bib. Das Offene Bibliotheksjournal, 8(3), 1–22. https://doi.org/10.5282/o-bib/5749
  2. Kleinkopf, F., Jacke, J., & Gärtner, M. (2021). Urheberrechtliche Grenzen der Nachnutzung wissenschaftlicher Korpora bei computergestützten Verfahren und digitalen Ressourcen.
  3. Wirth, T. (2020). Die Pflicht zur Löschung von Forschungsdaten – Urheber- und Datenschutzrecht im Widerspruch zu den Erfordernissen guter wissenschaftlicher Praxis? Zeitschrift für Urheber- und Medienrecht (ZUM), 64(8/9), 585–592. https://www.zew.de/publikationen/die-pflicht-zur-loeschung-von-forschungsdaten-urheber-und-datenschutzrecht-im-widerspruch-zu-den-erfordernissen-guter-wissenschaftlicher-praxis
  4. Kubis, M., Naczinsky, M., Selzer, A., Sperlich, T., Steiner, S., & Waldmann, U. (2019). Der digitale nachlass - Eine Untersuchung aus rechtlicher und technischer Sicht (F.-I. für Sichere Informationstechnologie, U. Bremen/IGMR, & U. Regensburg, Hrsg.). https://doi.org/10.24406/sit-n-572149
  5. Ostendorff, P., & Linke, D. (2019). Best-Practices im Umgang mit rechtlichen Fragestellungen zum Forschungsdatenmanagement (FDM). Bibliotheksdienst, 53(10–11), Article 10–11. https://doi.org/10.1515/bd-2019-0098
  6. Kreutzer, T., & Lahmann, H. (2019). Rechtsfragen bei Open Science. Hamburg University Press. https://doi.org/10.15460/HUP.195
  7. Johannes, P. C., Potthoff, J., Roßnagel, A., Neumair, B., Madiesh, M., & Hackel, S. (2013). Beweissicheres elektronisches Laborbuch (Nomos, Hrsg.).
  8. Meyermann, A., & Porzelt, M. (2014). Hinweise zur Anonymisierung von qualitativen Daten. forschungsdaten bildung informiert, 1, Article 1. https://www.forschungsdaten-bildung.de/get_files.php?action=get_file&file=fdb-informiert-nr-1.pdf
  9. Ebel, T., & Meyermann, A. (2015). Hinweise zur Anonymisierung von quantitativen Daten. forschungsdaten bildung informiert, 3, Article 3. https://www.forschungsdaten-bildung.de/get_files.php?action=get_file&file=fdb-informiert-nr-3.pdf
  10. Volkmann, S., Feiten, L., Zimmermann, C., Sester, S., Wehle, L., & Becker, B. (2016). Digitale Tarnkappe: Anonymisierung in Videoaufnahmen. In H. C. Mayr & M. Pinzger (Hrsg.), GI-Jahrestagung: Bd. P-259 (S. 413–426). GI. http://dblp.uni-trier.de/db/conf/gi/gi2016.html#VolkmannFZSWB16
  11. Klimpel, P. (2018). Mehr als Materialbewahrung Über die Bedeutung von Rechteinformationen und Lizenzierung in Bibliotheken. Lizenzangaben und Rechtedokumentationen im Dialog – Datenflüsse nachhaltig gestalten.
  12. Nationalbibliothek, D. (Hrsg.). (2018). Lizenzangaben und Rechtedokumentationen im Dialog - Datenflüsse nachhaltig gestalten.
  13. Hannover, L. U., & Informationsbibliothek, T. (2018). FAQs Zu Rechtlichen Aspekten Im Umgang Mit Forschungsdaten. https://doi.org/10.5281/zenodo.1173546
  14. Lauber‐Rönsberg, A., Krahn, P., & Baumann, P. (2018). Gutachten zu den rechtlichen Rahmenbedingungen des Forschungsdatenmanagements. https://tu-dresden.de/gsw/jura/igewem/jfbimd13/ressourcen/dateien/publikationen/DataJus_Zusammenfassung_Gutachten_12-07-18.pdf?lang=de
  15. Stietenroth, D., Nieschulze, J., & Arend, K. (2005). Rechtliche Aspekte und Umsetzung des Datenmanagement in internationalen interdisziplinären Forschungsprojekten. Zeitschrift Für Agrarinformatik, 3, 64–75. http://www.gil.de/publications/zai/archiv/11_3_2005.pdf
  16. Guibault, L., & Wiebe, A. (2013). Safe to be open. Study on the protection of research data and recommendations für access and usage. Universitätsverlag Göttingen.

Forschungssoftware

  1. Hirsch, M., Iglezakis, D., Leymann, F., & Zimmermann, M. (2022). The ReSUS Project - Infrastructure for Sharing Research Software. In E-Science-Tage 2021: Share Your Research Data (S. 267–276). heiBOOKS. https://doi.org/10.11588/HEIBOOKS.979.C13737
  2. Martinez, P. A., Barker, M., Struck, A., Castro, L. J., Erdmann, C., Garijo, D., Gesing, S., Loewe, A., & Moldón, J. (2022). A Survey on Adoption Guidelines for the FAIR4RS                    Principles. Zenodo. https://doi.org/10.5281/zenodo.6374598
  3. Martinez, P. A., Struck, A., Castro, L. J., Garijo, D., Loewe, A., Gesing, S., Barker, M., Chue Hong, N., Erdmann, C., Martinez-Ortiz, C., & Sansone, S.-A. (2022). A Survey on Adoption Guidelines for the FAIR4RS                    Principles: Dataset. Zenodo. https://doi.org/10.5281/zenodo.6375540
  4. Martinez-Ortiz, C., Katz, D. S., Lamprecht, A.-L., Barker, M., Loewe, A., Fouilloux, A., Wyngaard, J., Garijo, D., Moldon, J., Castro, L. J., Wheeler, D., Albers, J. R. D., & Lee, A. (2022). FAIR4RS: Adoption support. Zenodo. https://doi.org/10.5281/zenodo.6258366
  5. Anzt, H., Bach, F., Druskat, S., Löffler, F., Loewe, A., Renard, B. Y., Seemann, G., Struck, A., Achhammer, E., Aggarwal, P., Appel, F., Bader, M., Brusch, L., Busse, C., Chourdakis, G., Dabrowski, P. W., Ebert, P., Flemisch, B., Friedl, S., … Weeber, R. (2021). An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action. F1000Research, 9, 295. https://doi.org/10.12688/f1000research.23224.2
  6. Arvanitou, E.-M., Ampatzoglou, A., Chatzigeorgiou, A., & Carver, J. C. (2021). Software engineering practices for scientific software development: A systematic mapping study. Journal of Systems and Software, 172, 110848. https://doi.org/10.1016/j.jss.2020.110848
  7. Chue Hong, N. P., Katz, D. S., Barker, M., Lamprecht, A.-L., Martinez, C., Psomopoulos, F. E., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., & Honeyman, T. (2021). FAIR Principles for Research Software (FAIR4RS Principles). https://doi.org/10.15497/RDA00068
  8. Katz, D. S., Gruenpeter, M., & Honeyman, T. (2021). Taking a fresh look at FAIR for research software. Patterns, 2(3), Article 3. https://doi.org/10.1016/j.patter.2021.100222
  9. Koch, T., Gläser, D., Weishaupt, K., Ackermann, S., Beck, M., Becker, B., Burbulla, S., Class, H., Coltman, E., Emmert, S., Fetzer, T., Grüninger, C., Heck, K., Hommel, J., Kurz, T., Lipp, M., Mohammadi, F., Scherrer, S., Schneider, M., … Flemisch, B. (2021). DuMux 3 – an open-source simulator for solving flow and transport problems in porous media with a focus on model coupling. Computers & Mathematics with Applications, 81, 423--443. https://doi.org/10.1016/j.camwa.2020.02.012
  10. van Aalst, M., Ebenhoeh, O., & Matuszynska, A. (2021). Constructing and analysing dynamic models with modelbase v1.2.3: a    software update. BMC BIOINFORMATICS, 22(1), Article 1. https://doi.org/10.1186/s12859-021-04122-7
  11. Alliez, P., Cosmo, R. D., Guedj, B., Girault, A., Hacid, M.-S., Legrand, A., & Rougier, N. (2020). Attributing and Referencing (Research) Software: Best Practices and Outlook From Inria. Computing in Science  Engineering, 22(1), 39–52. https://doi.org/10.1109/MCSE.2019.2949413
  12. Anzt, H., Bach, F., Druskat, S., Löffler, F., Loewe, A., Renard, B. Y., Seemann, G., Struck, A., Achhammer, E., Aggarwal, P., Appel, F., Bader, M., Brusch, L., Busse, C., Chourdakis, G., Dabrowski, P. W., Ebert, P., Flemisch, B., Friedl, S., … Weeber, R. (2020). An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action. F1000Research, 9, 295. https://doi.org/10.12688/f1000research.23224.1
  13. Anzt, H., Bach, F., Druskat, S., Löffler, F., Loewe, A., Renard, B. Y., Seemann, G., Struck, A., Achhammer, E., Aggarwal, P., Appel, F., Bader, M., Brusch, L., Busse, C., Chourdakis, G., Dabrowski, P. W., Ebert, P., Flemisch, B., Friedl, S., … Weeber, R. (2020). An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action. F1000Research, 9, 295. https://doi.org/10.12688/f1000research.23224.1
  14. Anzt, H., Bach, F., Druskat, S., Löffler, F., Loewe, A., Renard, B. Y., Seemann, G., Struck, A., Achhammer, E., Aggarwal, P., Appel, F., Bader, M., Brusch, L., Busse, C., Chourdakis, G., Dabrowski, P. W., Ebert, P., Flemisch, B., Friedl, S., … Weeber, R. (2020). An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action. F1000Research, 9, 295. https://doi.org/10.12688/f1000research.23224.1
  15. Hasselbring, W., Carr, L., Hettrick, S., Packer, H., & Tiropanis, T. (2020). Open Source Research Software. Computer, 53(8), 84–88. https://doi.org/10.1109/MC.2020.2998235
  16. Hermann, S., Schneider, M., Flemisch, B., Frey, S., Iglezakis, D., Ruf, M., Schembera, B., Seeland, A., & Steeb, H. (2020). Datenmanagement im SFB 1313. Bausteine Forschungsdatenmanagement, 1. https://doi.org/10.17192/BFDM.2020.1.8085
  17. Magaña, P., Del-Rosal-Salido, J., Cobos, M., Lira-Loarca, A., & Ortega-Sánchez, M. (2020). Approaching Software Engineering for Marine Sciences: A Single Development Process for Multiple End-User Applications. Journal of Marine Science and Engineering, 8(5), 350. https://doi.org/10.3390/jmse8050350
  18. Pianosi, F., Sarrazin, F., & Wagener, T. (2020). How successfully is open-source research software adopted? Results and implications of surveying the users of a sensitivity analysis toolbox. Environmental Modelling & Software, 124, 104579. https://doi.org/10.1016/j.envsoft.2019.104579
  19. Ruiz-Rube, I., Person, T., Dodero, J. M., Mota, J. M., & Sánchez-Jara, J. M. (2020). Applying static code analysis for domain-specific languages. Software and Systems Modeling, 19(1), 95--110. https://doi.org/10.1007/s10270-019-00729-w
  20. SIRS, E. E. B. W. G. (WG) A. T. F. (TF). (2020). Scholarly infrastructures for research software (E. Commission, Hrsg.). European Commission. https://op.europa.eu/s/oMEw
  21. Trisovic, A., Durbin, P., Schlatter, T., Durand, G., Barbosa, S., Brooke, D., & Crosas, M. (2020). Advancing computational reproducibility in the Dataverse data repository  platform. http://arxiv.org/abs/2005.02985
  22. Akhmerov, A., Cruz, M., Drost, N., Hof, C., Knapen, T., Kuzak, M., Martinez-Ortiz, C., der Velden, Y. T., & van Werkhoven, B. (2019). Raising the Profile of Research Software: Recommendations for Funding Agencies and Research Institutions (NWO, Hrsg.).
  23. Ballhausen, M. (2019). Free and Open Source Software Licenses Explained. IEEE Computer, 52(6), 82–86. http://dblp.uni-trier.de/db/journals/computer/computer52.html#Ballhausen19
  24. Druskat, S., Spaaks, J. H., Chue Hong, N., Haines, R., & Baker, J. (2019). Citation File Format (CFF) - Specifications. Zenodo. https://doi.org/10.5281/zenodo.3515946
  25. Fehr, J., Himpe, C., Rave, S., & Saak, J. (2019). Sustainable Research Software Hand-Over. CoRR, abs/1909.09469. http://dblp.uni-trier.de/db/journals/corr/corr1909.html#abs-1909-09469
  26. Fehr, J., Himpe, C., Rave, S., & Saak, J. (2019). Sustainable Research Software Hand-Over. CoRR, abs/1909.09469. http://dblp.uni-trier.de/db/journals/corr/corr1909.html#abs-1909-09469
  27. Gomez-Diaz, T., & Recio, T. (2019). On the evaluation of research software: the CDUR procedure. F1000Research, 8, 1353. https://doi.org/10.12688/f1000research.19994.2
  28. Gärtner, M. (2019). RePlay-DH Client v1.3.0. https://doi.org/10.18419/darus-475
  29. Hasselbring, W., Carr, L., Hettrick, S., Packer, H., & Tiropanis, T. (2019). FAIR and Open Computer Science Research Software. In arXiv preprint arXiv:1908.05986. http://dblp.uni-trier.de/db/journals/corr/corr1908.html#abs-1908-05986
  30. Hermann, S., Iglezakis, D., & Seeland, A. (2019). Requirements for Finding Research Data and Software. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900480
  31. Hermann, S., Iglezakis, D., & Seeland, A. (2019). Requirements for Finding Research Data and Software. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900480
  32. Hsu, L., Hutchison, V. B., & Langseth, M. L. (2019). Measuring sustainability of seed-funded earth science informatics projects. PLOS ONE, 14(10), 1–25. https://doi.org/10.1371/journal.pone.0222807
  33. Johanson, A. N., & Hasselbring, W. (2019). Software Engineering for Computational Science. In S. Becker, I. Bogicevic, G. Herzwurm, & S. Wagner (Hrsg.), SE/SWM: Bd. P-292 (S. 43–44). GI. http://dblp.uni-trier.de/db/conf/se/se2019.html#JohansonH19
  34. Lamprecht, A.-L., Garcia, L., Kuzak, M., Martinez, C., Arcila, R., Pico, E. M. D., Angel, V. D. D., van de Sandt, S., Ison, J., Martinez, P. A., McQuilton, P., Valencia, A., Harrow, J., Psomopoulos, F., Gelpi, J. Ll., Hong, N. C., Goble, C., & Capella-Gutierrez, S. (2019). Towards FAIR principles for~research~software. Data Science, 1--23. https://doi.org/10.3233/ds-190026
  35. Lamprecht, A.-L., Garcia, L., Kuzak, M., Martinez, C., Arcila, R., Pico, E. M. D., Angel, V. D. D., van de Sandt, S., Ison, J., Martinez, P. A., McQuilton, P., Valencia, A., Harrow, J., Psomopoulos, F., Gelpi, J. Ll., Hong, N. C., Goble, C., & Capella-Gutierrez, S. (2019). Towards FAIR principles for~research~software. Data Science, 1--23. https://doi.org/10.3233/ds-190026
  36. Li, K., Chen, P.-Y., & Yan, E. (2019). Challenges of measuring software impact through citations: An examination of the lme4 R package. Journal of Informetrics, 13(1), 449--461. https://doi.org/10.1016/j.joi.2019.02.007
  37. Scheliga, K., Pampel, H., Konrad, U., Fritzsch, B., Schlauch, T., Nolden, M., Zu Castell, W., Finke, A., Hammitzsch, M., Bertuch, O., & Denker, M. (2019). Dealing with research software: Recommendations for best practices. https://doi.org/10.2312/OS.HELMHOLTZ.003
  38. Siepel, A. (2019). Challenges in funding and developing genomic software: roots and remedies. Genome Biology, 20(1), 147--. https://doi.org/10.1186/s13059-019-1763-7
  39. Task Group Forschungssoftware Des Arbeitskreises Open Science Der Helmholtz-Gemeinschaft. (2019). Muster-Richtlinie Nachhaltige Forschungssoftware an den Helmholtz-Zentren. https://doi.org/10.2312/OS.HELMHOLTZ.007
  40. van de Sandt, S., Nielsen, L. H., Ioannidis, A., Muench, A., Henneken, E. A., Accomazzi, A., Bigarella, C., Lopez, J. B. G., & Dallmeier-Tiessen, S. (2019). Practice meets Principle: Tracking Software and Data Citations to Zenodo DOIs. CoRR, abs/1911.00295. http://dblp.uni-trier.de/db/journals/corr/corr1911.html#abs-1911-00295
  41. VSNU, NFU, KNAW, NWO and ZonMw (Hrsg.). (2019). Room for everyone’s talent.
  42. AlNoamany, Y., & Borghi, J. A. (2018). Towards computational reproducibility: researcher perspectives on the use and sharing of software. PeerJ Computer Science, 4, e163. https://doi.org/10.7717/peerj-cs.163
  43. Cruz, M. J., Kurapati, S., & Turkyilmaz-van der Velden, Y. (2018). The Role of Data Stewardship in Software Sustainability and Reproducibility. 2018 IEEE 14th International Conference on e-Science (e-Science), 1–8. https://doi.org/10.1109/eScience.2018.00009
  44. Hallé, S., Khoury, R., & Awesso, M. (2018). Streamlining the Inclusion of Computer Experiments In a Research Paper. IEEE Computer, 51(11), 78–89. http://dblp.uni-trier.de/db/journals/computer/computer51.html#HalleKA18
  45. Hinsen, K. (2018). Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interface. PeerJ Computer Science, 4, e158. https://doi.org/10.7717/peerj-cs.158
  46. Johanson, A., & Hasselbring, W. (2018). Software Engineering for Computational Science: Past, Present, Future. Computing in Science  Engineering, 20(2), 90–109. https://doi.org/10.1109/MCSE.2018.021651343
  47. Karimzadeh, M., & Hoffman, M. M. (2018). Top considerations for creating bioinformatics software documentation. BRIEFINGS IN BIOINFORMATICS, 19(4), 693–699. https://doi.org/10.1093/bib/bbw134
  48. Katerbow, M., & Feulner, G. (2018). Handreichung zum Umgang mit Forschungssoftware. Zenodo. https://doi.org/10.5281/ZENODO.1172970
  49. Katz, D. S., & Hong, N. P. C. (2018). Software Citation in Theory and Practice. In J. H. Davenport, M. Kauers, G. Labahn, & J. Urban (Hrsg.), ICMS (Bd. 10931, S. 289–296). Springer. http://dblp.uni-trier.de/db/conf/icms/icms2018.html#KatzH18
  50. Kuzak, M., Harrow, J., Jimenez, R. C., Martinez, P. A., Psomopoulos, F. E., Svobodová Vařeková, R., & Via, A. (2018). Lesson Development for Open Source Software Best Practices Adoption. 2018 IEEE 14th International Conference on e-Science (e-Science), 19–20. https://doi.org/10.1109/eScience.2018.00011
  51. Lee, B. D. (2018). Ten simple rules for documenting scientific software. PLOS Computational Biology, 14(12), e1006561. https://doi.org/10.1371/journal.pcbi.1006561
  52. Russell, P. H., Johnson, R. L., Ananthan, S., Harnke, B., & Carlson, N. E. (2018). A large-scale analysis of bioinformatics code on GitHub. PLOS ONE, 13(10), 1–19. https://doi.org/10.1371/journal.pone.0205898
  53. Rüde, U., Willcox, K., McInnes, L. C., & Sterck, H. D. (2018). Research and Education in Computational Science and Engineering. SIAM Review, 60(3), 707–754. http://dblp.uni-trier.de/db/journals/siamrev/siamrev60.html#RudeWMS18
  54. Schlauch, T., Meinel, M., & Haupt, C. (2018). DLR Software Engineering Guidelines. https://doi.org/10.5281/zenodo.1344612
  55. Allen, A., Aragon, C. R., Becker, C., Carver, J., Chis, A., Combemale, B., Croucher, M., Crowston, K., Garijo, D., Gehani, A., Goble, C. A., Haines, R., Hirschfeld, R., Howison, J., Huff, K. D., Jay, C., Katz, D. S., Kirchner, C., Kuksenok, K., … Vinju, J. J. (2017). Engineering Academic Software (Dagstuhl Perspectives Workshop 16252). Dagstuhl Manifestos, 6(1), 1–20. http://dblp.uni-trier.de/db/journals/dagstuhl-manifestos/dagstuhl-manifestos6.html#AllenABCCCCCGGG17
  56. Bar-Sinai, M., & Dunlap, M. (2017). The Open Monolith - Keeping Your Codebase (and Your Headaches) Small (JavaOne, Hrsg.).
  57. Boettiger, C. (2017). Generating CodeMeta Metadata for R Packages. The Journal of Open Source Software, 2(19), 454. https://doi.org/10.21105/joss.00454
  58. Childers, B. R., & Chrysanthis, P. K. (2017). Artifact Evaluation: Is It a Real Incentive? 2017 IEEE 13th International Conference on e-Science (e-Science), 488–489. https://doi.org/10.1109/eScience.2017.79
  59. Cosmo, R. D., & Zacchiroli, S. (2017). Software Heritage: Why and How to Preserve Software Source Code. iPRES 2017 - 14th International Conference on Digital Preservation, 1–10. https://hal.archives-ouvertes.fr/hal-01590958/
  60. Henderson, F. (2017). Software Engineering at Google. CoRR, abs/1702.01715. http://arxiv.org/abs/1702.01715
  61. Hinsen, K. (2017). The Roles of Code in Computational Science. Computing in Science  Engineering, 19(1), 78–82. https://doi.org/10.1109/MCSE.2017.18
  62. Jiménez, R. C., Kuzak, M., Alhamdoosh, M., Barker, M., Batut, B., Borg, M., Capella-Gutierrez, S., Hong, N. C., Cook, M., Corpas, M., Flannery, M., Garcia, L., Gelp\’ı, J. Ll., Gladman, S., Goble, C., Ferreiro, M. G., Gonzalez-Beltran, A., Griffin, P. C., Grüning, B., … Crouch, S. (2017). Four simple recommendations to encourage best practices in research software. F1000Research, 6, 876. https://doi.org/10.12688/f1000research.11407.1
  63. Karimzadeh, M., & Hoffman, M. M. (2017). Top considerations for creating bioinformatics software documentation. Briefings in Bioinformatics, 19(4), 693–699. https://doi.org/10.1093/bib/bbw134
  64. Taschuk, M., & Wilson, G. (2017). Ten simple rules for making research software more robust. PLOS Computational Biology, 13(4), 1–10. https://doi.org/10.1371/journal.pcbi.1005412
  65. Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L., & Teal, T. K. (2017). Good enough practices in scientific computing. PLOS Computational Biology, 13(6), 1–20. https://doi.org/10.1371/journal.pcbi.1005510
  66. zu und Nachnutzung von wissenschaftlicher Software“, T. G. „Zugang. (2017). Empfehlungen zur Implementierung von Leit- und Richtlinien zum Umgang mit wissenschaftlicher Software an den Helmholtz-Zentren (A. O. S. der Helmholtz-Gemeinschaft, Hrsg.). Helmholtz Gemeinschaft. https://os.helmholtz.de/open-science-in-der-helmholtz-gemeinschaft/akteure-und-ihre-rollen/arbeitskreis-open-science/empfehlungen-zur-implementierung-von-leit-und-richtlinien-zum-umgang-mit-wissenschaftlicher-software-an-den-helmholtz-zentren/
  67. Boisvert, R. F. (2016). Incentivizing reproducibility. Communications of the ACM, 59(10), 5--5. https://doi.org/10.1145/2994031
  68. Collberg, C., & Proebsting, T. A. (2016). Repeatability in Computer Systems Research. Commun. ACM, 59(3), 62--69. https://doi.org/10.1145/2812803
  69. Febrero, F., Calero, C., & Moraga, M. Á. (2016). Software reliability modeling based on ISO/IEC SQuaRE. Information and Software Technology, 70, 18--29. https://doi.org/10.1016/j.infsof.2015.09.006
  70. Gil, Y., David, C. H., Demir, I., Essawy, B. T., Fulweiler, R. W., Goodall, J. L., Karlstrom, L., Lee, H., Mills, H. J., Oh, J.-H., Pierce, S. A., Pope, A., Tzeng, M. W., Villamizar, S. R., & Yu, X. (2016). Toward the Geoscience Paper of the Future: Best practices for documenting and sharing research from data to software to provenance. Earth and Space Science, 3(10), 388--415. https://doi.org/10.1002/2015ea000136
  71. Smith, A. M., Katz, D. S., & Niemeyer, K. E. (2016). Software citation principles. PeerJ Computer Science, 2, e86. https://doi.org/10.7717/peerj-cs.86
  72. Yu, X., Duffy, C. J., Rousseau, A. N., Bhatt, G., Alvarez, A. P., & Charron, D. (2016). Open science in practice: Learning integrated modeling of coupled    surface-subsurface flow processes from scratch. EARTH AND SPACE SCIENCE, 3(5), 190–206. https://doi.org/10.1002/2015EA000155
  73. McGibbon, R. T., Beauchamp, K. A., Harrigan, M. P., Klein, C., Swails, J. M., Hernández, C. X., Schwantes, C. R., Wang, L.-P., Lane, T. J., & Pande, V. S. (2015). MDTraj: A Modern Open Library for the Analysis of    Molecular Dynamics Trajectories. Biophysical Journal, 109(8), 1528-- 1532. https://doi.org/10.1016/j.bpj.2015.08.015
  74. Hastings, J., Haug, K., & Steinbeck, C. (2014). Ten recommendations for software engineering in research. GIGASCIENCE, 3. https://doi.org/10.1186/2047-217X-3-31
  75. Hong, N. C. (2014). Minimal information for reusable scientific software. Proceedings of the 2nd Workshop on Working towards Sustainable Scientific Software: Practice and Experience.
  76. Peer, L., Green, A., & Stephenson, E. (2014). Committing to Data Quality Review. International Journal of Digital Curation, 9(1), 263--291. https://doi.org/10.2218/ijdc.v9i1.317
  77. Stodden, V., & Miguez, S. (2014). Best Practices for Computational Science: Software Infrastructure and Environments for Reproducible and Extensible Research. Journal of Open Research Software, 2(1), Article 1. https://doi.org/10.5334/jors.ay
  78. Wilson, G., Aruliah, D. A., Brown, C. T., Chue Hong, N. P., Davis, M., Guy, R. T., Haddock, S. H., Huff, K. D., Mitchell, I. M., Plumbley, M. D., Waugh, B., White, E. P., & Wilson, P. (2014). Best practices for scientific computing. PLoS Biol, 12(1), Article 1. https://doi.org/10.1371/journal.pbio.1001745
  79. Bangerth, W., & Heister, T. (2013). What makes computational open source software libraries successful? Computational Science & Discovery, 6(1), 015010. https://doi.org/10.1088/1749-4699/6/1/015010
  80. Sandve, G. K., Nekrutenko, A., Taylor, J., & Hovig, E. (2013). Ten Simple Rules for Reproducible Computational Research. PLOS Computational Biology, 9(10), 1–4. https://doi.org/10.1371/journal.pcbi.1003285
  81. Tomas, P., Escalona, M. J., & Mejias, M. (2013). Open source tools for measuring the Internal Quality of Java software products. A survey. Computer Standards & Interfaces, 36(1), 244--255. https://doi.org/10.1016/j.csi.2013.08.006
  82. Turk, M. J. (2013). How to Scale a Code in the Human Dimension. CoRR, abs/1301.7064. http://dblp.uni-trier.de/db/journals/corr/corr1301.html#abs-1301-7064
  83. Howison, J., & Herbsleb, J. D. (2011). Scientific software production. Proceedings of the ACM 2011 conference on Computer supported cooperative work - CSCW \textquotesingle11. https://doi.org/10.1145/1958824.1958904
  84. Prabhu, P., Zhang, Y., Ghosh, S., August, D. I., Huang, J., Beard, S., Kim, H., Oh, T., Jablin, T. B., Johnson, N. P., Zoufaly, M., Raman, A., Liu, F., & Walker, D. (2011). A survey of the practice of computational science. State of the Practice Reports on - SC \textquotesingle11. https://doi.org/10.1145/2063348.2063374
  85. Hannay, J. E., MacLeod, C., Singer, J., Langtangen, H. P., Pfahl, D., & Wilson, G. (2009). How do scientists develop and use scientific software? 2009 ICSE Workshop on Software Engineering for Computational Science and Engineering, 1–8. https://doi.org/10.1109/SECSE.2009.5069155
  86. Ackroyd, K. S., Kinder, S. H., Mant, G. R., Miller, M. C., Ramsdale, C. A., & Stephenson, P. C. (2008). Scientific Software Development at a Research Facility. IEEE Software, 25(4), 44–51. https://doi.org/10.1109/MS.2008.93
  87. Basili, V. R., Carver, J. C., Cruzes, D., Hochstein, L., Hollingsworth, J. K., Shull, F., & Zelkowitz, M. V. (2008). Understanding the High-Performance-Computing Community: A Software Engineer’s Perspective. IEEE Software, 25(4), 29–36. https://doi.org/10.1109/MS.2008.103
  88. Glass, R. L. (2008). Two Mistakes and Error-Free Software: A Confession. IEEE Software, 25(4), 96–96. https://doi.org/10.1109/MS.2008.102
  89. Hall, T., Sharp, H., Beecham, S., Baddoo, N., & Robinson, H. (2008). What Do We Know about Developer Motivation? IEEE Software, 25(4), 92–94. https://doi.org/10.1109/MS.2008.105
  90. Hatton, L. (2008). Testing the Value of Checklists in Code Inspections. IEEE Software, 25(4), 82–88. https://doi.org/10.1109/MS.2008.100
  91. Kendall, R., Carver, J. C., Fisher, D., Henderson, D., Mark, A., Post, D., Rhoades, C. E., & Squires, S. (2008). Development of a Weather Forecasting Code: A Case Study. IEEE Software, 25(4), 59–65. https://doi.org/10.1109/MS.2008.86
  92. Sanders, R., & Kelly, D. (2008). Dealing with Risk in Scientific Software Development. IEEE Software, 25(4), 21–28. https://doi.org/10.1109/MS.2008.84
  93. Sangwan, R. S., Vercellone-Smith, P., & Laplante, P. A. (2008). Structural Epochs in the Complexity of Software over Time. IEEE Software, 25(4), 66–73. https://doi.org/10.1109/MS.2008.96
  94. Segal, J., & Morris, C. (2008). Developing Scientific Software. IEEE Software, 25(4), 18–20. https://doi.org/10.1109/MS.2008.85
  95. Spinellis, D. (2008). The Way We Program. IEEE Software, 25(4), 89–91. https://doi.org/10.1109/MS.2008.101
  96. Vigder, M., Vinson, N. G., Singer, J., Stewart, D., & Mews, K. (2008). Supporting Scientists’ Everyday Work: Automating Scientific Workflows. IEEE Software, 25(4), 52–58. https://doi.org/10.1109/MS.2008.97
  97. Woollard, D., Medvidovic, N., Gil, Y., & Mattmann, C. (2008). Scientific Software as Workflows: From Discovery to Distribution. IEEE Software, 25(4), 37–43. https://doi.org/10.1109/MS.2008.92
  98. Asanovic, K., Bodik, R., Catanzaro, B. C., Gebis, J. J., Husbands, P., Keutzer, K., Patterson, D. A., Plishker, W. L., Shalf, J., Williams, S. W., & others. (2006). The landscape of parallel computing research: A view from berkeley.
  99. Asanovic, K., Bodik, R., Catanzaro, B. C., Gebis, J. J., Husbands, P., Keutzer, K., Patterson, D. A., Plishker, W. L., Shalf, J., Williams, S. W., & others. (2006). The landscape of parallel computing research: A view from berkeley.
  100. Crowder, H. P., Dembo, R. S., & Mulvey, J. M. (1979). On Reporting Computational Experiments with Mathematical Software. ACM Trans. Math. Softw., 5(2), 193–203. http://dblp.uni-trier.de/db/journals/toms/toms5.html#CrowderDM79

Befragungen

  1. Berberich, J., Köhler, J., Müller, M. A., & Allgöwer, F. (2022). Linear tracking MPC for nonlinear systems part I: the model-based case. IEEE Trans. Automat. Control, 67(9), 4390–4405. https://doi.org/10.1109/TAC.2022.3166872
  2. Berberich, J., Köhler, J., Müller, M. A., & Allgöwer, F. (2022). Linear tracking MPC for nonlinear systems part II: the data-driven case. IEEE Trans. Automat. Control, 67(9), 4406–4421. https://doi.org/10.1109/TAC.2022.3166851
  3. Blascheck, T., Bentley, F., Choe, E. K., Horak, T., & Isenberg, P. (2022). Characterizing Glanceable Visualizations : From Perception to Behavior Change. In B. Lee, R. Dachselt, P. Isenberg, & E. K. Choe (Hrsg.), Mobile Data Visualization (1. Aufl., S. 209–240). CRC Press. https://doi.org/10.1201/9781003090823-5
  4. Carpendale, S., Isenberg, P., Perin, C., Blascheck, T., Daneshzand, F., Islam, A., Currier, K., Buk, P., Cheung, V., Quach, L., & Vermette, L. (2022). Mobile Visualization Design : An Ideation Method to Try. In B. Lee, R. Dachselt, P. Isenberg, & E. K. Choe (Hrsg.), Mobile Data Visualization (1. Aufl., S. 241–262). CRC Press. https://doi.org/10.1201/9781003090823-8
  5. Ehni, P., Bauch, S. M., Becker, P. M., Frey, W., Zens, A., Kästner, J., Molard, Y., & Laschat, S. (2022). Merging liquid crystalline self-assembly and linear optical properties of merocyanines via tailored donor units. Phys. Chem. Chem. Phys., 24(36), 21617–21630. https://doi.org/10.1039/D2CP02237K
  6. Epstein, D. A., Blascheck, T., Carpendale, S., Dachselt, R., & Vermeulen, J. (2022). Challenges in Everyday Use of Mobile Visualizations. In B. Lee, R. Dachselt, P. Isenberg, & E. K. Choe (Hrsg.), Mobile Data Visualization (1. Aufl., S. 209–240). CRC Press. https://doi.org/10.1201/9781003090823-7
  7. Hommel, J., Gehring, L., Weinhardt, F., Ruf, M., & Steeb, H. (2022). Effects of Enzymatically Induced Carbonate Precipitation on Capillary Pressure–Saturation Relations. Minerals, 12(10), Article 10. https://doi.org/10.3390/min12101186
  8. Kloker, L. H., & Bringedal, C. (2022). Solution approaches for evaporation-driven density instabilities in a slab of saturated porous media. Physics of Fluids, 34(9), 096606. https://doi.org/10.1063/5.0110129
  9. Klotz, T., Gizzi, L., & Röhrle, O. (2022). Investigating the spatial resolution of EMG and MMG based on a systemic multi-scale model. Biomechanics and Modeling in Mechanobiology, 21(3), 983–997. https://doi.org/10.1007/s10237-022-01572-7
  10. Mohamed, A., Djekic, D., Baumgärtner, L., & §H$Anders, J. (2022). Noise-aware design methodology of ultra-low-noise transimpedance amplifiers. 2021 28th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 1–4. https://doi.org/10.1109/ICECS53924.2021.9665532
  11. Neßlinger, V., Welzel, S., Rieker, F., Meinderink, D., Nieken, U., & Grundmeier, G. (2022). Thin Organic-inorganic Anti-fouling Hybrid-films for Microreactor Components. Macromolecular Reaction Engineering. https://doi.org/10.1002/mren.202200043
  12. Pott, P. P. (2022). Haptic interfaces. In L. Manfredi (Hrsg.), Endorobotics : design, R&D and future trends (1. Aufl.). Elsevier. https://www.elsevier.com/books/endorobotics/manfredi/978-0-12-821750-4
  13. Rodriguez-Diaz, N., Aspandi Latif, D., Federico M., S., & Binefa, X. (2022). Machine Learning-Based Lie Detector Applied to a Novel Annotated Game Dataset. Future Internet, 14(1), 2. https://doi.org/10.3390/fi14010002
  14. Windzio, M., & Heiberger, R. H. (2022). Talking About Education: How Topics Vary Between International Organizations. In K. Martens & M. Windzio (Hrsg.), Global Pathways to Education (S. 239–266). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-78885-8_9
  15. Windzio, M., & Heiberger, R. H. (2022). The social ecology of intergenerational closure in school class networks. Socio-spatial conditions of parents’ norm generation and their effects on students’ interpersonal conflicts. Social Networks. https://doi.org/10.1016/j.socnet.2021.12.009
  16. Berberich, J., Wildhagen, S., Hertneck, M., & Allgöwer, F. (2021). Data-driven analysis and control of continuous-time systems under aperiodic sampling. Proc. 19th IFAC Symp. System Identification (SYSID), 210–215. https://doi.org/10.1016/j.ifacol.2021.08.360
  17. Berberich, J., Köhler, J., Müller, M. A., & Allgöwer, F. (2021). Data-driven model predictive control: closed-loop guarantees and experimental results. at-Automatisierungstechnik, 69(7), 608–618. https://doi.org/10.1515/auto-2021-0024
  18. Berberich, J., Köhler, J., Müller, M. A., & Allgöwer, F. (2021). On the design of terminal ingredients for data-driven MPC. Proc. 7th IFAC Conf. Nonlinear Model Predictive Control (NMPC), 257–263. https://doi.org/10.1016/j.ifacol.2021.08.554
  19. Binz, H., Kreimeyer, M., Roth, D., Voigt, M., Bosch, M., & Burghardt, T. (2021). Weltweit erstes adaptives Hochhaus mit adaptivem Tragwerk und adaptiven Fassaden. Mitteilungen der WiGeP, 2021(2), 5–7. http://www.wigep.de/fileadmin/download/wigep/FINAL_WiGeP_News_2021-2.pdf
  20. Black, F., Schulze, P., & Unger, B. (2021). Modal Decomposition of Flow Data via Gradient-Based Transport Optimization. In R. King & D. Peitsch (Hrsg.), Active Flow and Combustion Control 2021 : Papers Contributed to the Conference “Active Flow and Combustion Control 2021”, September 28-29, 2021, Berlin, Germany (Nr. 152; Nummer 152, S. 203–224). Springer. https://doi.org/10.1007/978-3-030-90727-3_13
  21. Cheng, T., Wood, D., Kiesewetter, L., Özdemir, E., Antorveza, K., & Menges, A. (2021). Programming material compliance and actuation: hybrid additive fabrication of biocomposite structures for large-scale self-shaping. Bioinspiration & Biomimetics, 16(5), Article 5. https://doi.org/10.1088/1748-3190/ac10af
  22. Döpper, T., Große-Wöhrmann, B., Lindner, D., Milakovic, D., Oexle, J., Resch, M. M., Scheel, O., Slotosch, S., & Widmaier, L. (2021). Expanding HLRS Academic HPC Simulation Training Programs to More Target Groups. Journal of Computational Science Education, 12(3), 13–26. https://doi.org/10.22369/issn.2153-4136/12/3/2
  23. Eshghinezhad, H., Shariatmadari, N., & Askari Lasaki, B. (2021). Influence of Adding Tire Chips on the Mechanical Behavior of Calcareous Sands. Geotechnical and Geological Engineering, 39(3), 2147–2160. https://doi.org/10.1007/s10706-020-01615-9
  24. Grioui, F., & Blascheck, T. (2021). Study of Heart Rate Visualizations on a Virtual Smartwatch. In Y. Itoh, K. Takashima, P. Punpongsanon, M. Sra, K. Fujita, & S. Yoshida (Hrsg.), VRST ’21 : Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology (S. 96). Association for Computing Machinery. https://doi.org/10.1145/3489849.3489913
  25. Hampel, J., Störk-Biber, C., Zwick, M., & Kropp, C. (2021). Landwirtschaft und Medizin : Antipoden bei der Wahrnehmung der Gentechnik in Deutschland. In B. Fehse, F. Hucho, S. Bartfeld, S. Clemens, T. Erb, H. Fangerau, J. Hampel, M. Korte, L. Marx-Stölting, S. Mundlos, A. Osterheider, A. Pichl, J. Reich, H. Schickl, S. Schicktanz, J. Taupitz, J. Walter, E. Winkler, & M. Zenke (Hrsg.), Fünfter Gentechnologiebericht : Sachstand und Perspektiven für Forschung und Anwendung (Nr. 44; 1. Aufl., Nummer 44, S. 504–522). Nomos. https://doi.org/10.5771/9783748927242-504
  26. Kropp, C., & Sonnberger, M. (2021). Umweltsoziologie. In Studienkurs Soziologie (1. Aufl.). Nomos. https://doi.org/10.5771/9783845292076-1
  27. Képes, K., Leymann, F., Weder, B., & Wild, K. (2021). SiDD : The Situation-Aware Distributed Deployment System. In H. Hacid, F. Outay, H. Paik, A. Alloum, M. Petrocchi, M. R. Bouadjenek, A. Beheshti, X. Liu, & A. Maaradji (Hrsg.), Service-Oriented Computing : ICSOC 2020 Workshops : AIOps, CFTIC, STRAPS, AI-PA, AI-IOTS, and Satellite Events, Dubai, United Arab Emirates, December 14-17, 2020, Proceedings (Nr. 12632; Nummer 12632, S. 72–76). Springer. https://doi.org/10.1007/978-3-030-76352-7_11
  28. Liu, J., Göhring, C., Schiele, F., Möller, K., & Pott, P. P. (2021). Fabrication and Experimental Evaluation of Simple Tissue-Mimicking Phantoms with Realistic Electrical Properties for Impedance-Based Sensing. International Journal of Integrated Engineering, 13(5), 127–136. https://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/8516
  29. Liu, J., Göhring, C., & Pott, P. P. (2021). Integration of a Hollow, Bipolar Needle Electrode into a Handheld Impedance Measurement Device for Tissue Identification. 2021 13th Biomedical Engineering International Conference (BMEiCON). 2021 13th Biomedical Engineering International Conference (BMEiCON), Online. https://doi.org/10.1109/BMEiCON53485.2021.9745245
  30. Minn, F., Hügler, M., Kosow, H., Kramer, H., Krauß, M., León Huchler, C. D., Stauder, S., & Wasielewski, S. (2021). Leitfaden für Konzeption, Aufbau und Betrieb von Schulungs- und Pilotanlagen zur Aufbereitung von Trinkwasser und Reinigung von Abwasser aus einer sozio-technischen Perspektive. Bundesministerium für Bildung und Forschung. https://doi.org/10.18419/opus-11793
  31. Nitsche, J., Schlotthauer, T., Hermann, F., & Middendorf, P. (2021). Experimental Study on Depth of Cure During UV-Post-Curing of Photopolymers Used for Additive Manufacturing. In P. Weißgraeber, F. Heieck, & C. Ackermann (Hrsg.), Advances in Automotive Production Technology : Theory and Application : Stuttgart Conference on Automotive Production (SCAP2020) (S. 343–350). Springer. https://doi.org/10.1007/978-3-662-62962-8
  32. Schnell, P. (2021). Einflussmöglichkeiten bei Instandhaltung. ModernisierungsMagazin, 34(11), 18–19. https://app.smarticle.com/html5/L1Ipabu6bW/uSYlPz0TGsDCm/18
  33. Schnell, P. (2021). Korrelationspotentiale zwischen Modularem Bauen und Nachhaltigkeitszielen. ModernisierungsMagazin, 34(9), 18–19. https://app.smarticle.com/html5/L1Ipabu6bW/r58jqI7edUrqx/18
  34. Schnell, P. (2021). Potentiale bei Instandhaltungsmaßnahmen. ModernisierungsMagazin, 34(10), 20–21. https://app.smarticle.com/html5/L1Ipabu6bW/lVCOmo6lG9gHe/20
  35. Tietz, V., Schöpf, J., Waldvogel, A., & Annighöfer, B. (2021). A Concept for a Qualifiable (Meta)-Modeling Framework Deployable in Systems and Tools of Safety-Critical and Cyber-Physical Environments. 2021 ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems (MODELS), 163–169. https://doi.org/10.1109/MODELS50736.2021.00025
  36. Wang, W., Yang, G., Evrim, C., Terzis, A., Helmig, R., & Chu, X. (2021). An assessment of turbulence transportation near regular and random permeable interfaces. Physics of Fluids, 33(11), 115103. https://doi.org/10.1063/5.0069311
  37. Weder, B., Barzen, J., Leymann, F., & Zimmermann, M. (2021). Hybrid Quantum Applications Need Two Orchestrations in Superposition : A Software Architecture Perspective. In C. Chang (Hrsg.), 2021 IEEE International Conference on Web Services (ICWS). IEEE. https://doi.org/10.1109/ICWS53863.2021.00015
  38. Wieler, N., Berberich, J., Koch, A., & Allgöwer, F. (2021). Data-driven controller design via finite-horizon dissipativity. Proc. 3rd Learning for Dynamics and Control Conf. (L4DC), 144, 287–298.
  39. Özdemir, E., Kiesewetter, L., Antorveza, K., Cheng, T., Leder, S., Wood, D., & Menges, A. (2021). Towards Self-shaping Metamaterial Shells: A Computational Design Workflow for Hybrid Additive Manufacturing of Architectural Scale Double-Curved Structures. Proceedings of the 2021 DigitalFUTURES (CDRF 2021), 275–285. https://doi.org/10.1007/978-981-16-5983-6_26
  40. Cheng, T., Wood, D., Wang, X., Yuan, P., & Menges, A. (2020). Programming Material Intelligence: An Additive Fabrication Strategy for Self-Shaping Biohybrid Components. Lecture Notes in Artificial Intelligence: Biomimetic and Biohybrid Systems - Proceedings of the Living Machines 2020 Conference, 12413, 36--45. https://doi.org/10.1007/978-3-030-64313-3_5
  41. Arabani‬, M., & Askari Lasaki, B. (2017). Behavior of a Simulated Collapsible Soil Modified with XPS-Cement Mixtures. Geotechnical and Geological Engineering, 35(1), 137–155. https://doi.org/10.1007/s10706-016-0092-9
  42. Shariatmadari, N., Askari Lasaki, B., Eshghi Nezhad, H., & Askari, B. (2016). Investigating the Stress-Strain and Failure Behavior of Soils Contaminated with Urban Solid Waste Leachate : A Case Study from the Landfill Area of Saravan, Rasht. International Journal of Civil Engineering, 14(7), 451–457. https://doi.org/10.1007/s40999-016-0051-0
  43. Angelova, D. I., Dierichs, K., & Menges, A. (2015). Graded Light in Aggregate Structures – Modelling the Daylight in Designed Granular Systems Using Online Controlled Robotic Processes. Real Time - Proceedings of the 33rd eCAADe Conference, 2, 399--406.
  44. Baudy, B., Koehl, S., Menges, A., & Reichert, S. (2015). Computational Design and Automotive Material Gestalt – Cross-disciplinary Design Research by the Mercedes-Benz Center of Advanced Design and the Institute for Computational Design. Architectural Design, 85(5), 114--121. https://doi.org/10.1002/ad.1963
  45. Dörstelmann, M., Knippers, J., Menges, A., Parascho, S., Prado, M., & Schwinn, T. (2015). ICD/ITKE Research Pavilion 2013-14 – Modular Coreless Filament Winding Based on Beetle Elytra. Architectural Design, 85(5), 54--59. https://doi.org/10.1002/ad.1954
  46. Schwinn, T., & Menges, A. (2015). Fabrication Agency – Landesgartenschau Exhibition Hall. Architectural Design, 85(5), 92--99. https://doi.org/10.1002/ad.1960
  47. Topic, N., Poschel, T., Dierichs, K., & Menges, A. (2015). Packings of Complex Shaped Particles in Cylinders. Proceedings of the Particle Simulations Conference 2015, 53--54.
  48. Vasey, L., Baharlou, E., Dörstelmann, M., Koslowski, V., Prado, M., Schieber, G., Menges, A., & Knippers, J. (2015). Behavioral Design and Adaptive Robotic Fabrication of a Fiber Composite Compression Shell With Pneumatic Formwork. Computational ecologies: Design in the anthropocene, Proceedings of the 35th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), 297--309.
  49. Dörstelmann, M., Parascho, S., Prado, M., Menges, A., & Knippers, J. (2014). Integrative Computational Design Methodologies for Modular Architectural Fiber Composite Morphologies. Design Agency - Proceedings of the 34th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), 219--228.
  50. Kuma, T., Dörstelmann, M., Schwinn, T., Menges, A., & Knippers, J. (2014). Integrative Computational Design Methodology for Composite Spacer Fabric Architecture. Fusion - Proceedings of the 32nd eCAADe Conference, 2, 283--292.
  51. Reichert, S., Schwinn, T., La Magna, R., Waimer, F., Knippers, J., & Menges, A. (2014). Fibrous Structures: An integrative approach to design computation, simulation and fabrication for Lightweight, Glass and Carbon Fibre Composite Structures in Architecture based on Biomimetic Design Principles. CAD Journal, 52, 27--39. https://doi.org/10.1016/j.cad.2014.02.005
  52. Ahlquist, S., Lienhard, J., Knippers, J., & Menges, A. (2013). Exploring Materials Reciprocities for Textile-Hybrid Systems as Spatial Structures. Prototyping Architecture: The Conference Papers, 187--210.
  53. Baharlou, E., & Menges, A. (2013). Behavioural prototyping: an approach to agent-based computational design driven by fabrication characteristics and material constraints. Rethinking Prototyping - Proceedings of the Design Modelling Symposium Berlin 2013, 291--303.
  54. Dierichs, K., & Menges, A. (2013). Aggregate Architecture: Simulation models for synthetic non-convex granulates. Proceedings of the 33nd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) – Adaptive Architecture, 301--310.
  55. Krieg, O., & Menges, A. (2013). Potentials of Robotic Fabrication in Wood Construction: Elastically Bent Timber Sheets with Robotically Fabricated Finger Joints. Proceedings of the 33nd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA ) – Adaptive Architecture, 253--260.
  56. Krieg, O., & Menges, A. (2013). Prototyping Robotic Production: Development of Elastically Bent Wood Plate Morphologies with Curved Finger Joint Seams. Rethinking Prototyping - Proceedings of the Design Modelling Symposium Berlin 2013, 479--490.
  57. La Magna, R., Gabler, M., Reichert, S., Schwinn, T., Waimer, F., Menges, A., & Knippers, J. (2013). From Nature to Fabrication: Biomimetic Design Principles for the Production of Complex Spatial Structures. International Journal of Spatial Structures, 28(1), 27--40. https://doi.org/10.1260/0266-3511.28.1.27
  58. Parascho, S., Baur, M., Baharlou, E., Knippers, J., & Menges, A. (2013). Agent Based Model for the Development of Integrative Design Tools. Proceedings of the 33nd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) – Adaptive Architecture, 429--430.
  59. Schwinn, T., La Magna, R., Reichert, S., Waimer, F., Knippers, J., & Menges, A. (2013). Prototyping Biomimetic Structures for Architecture. Prototyping Architecture: The Conference Papers, 224--244.
  60. Weigele, J., Schloz, M., Schwinn, T., Reichert, S., La Magna, R., Waimer, F., Knippers, J., & Menges, A. (2013). Fibrous Morphologies. Computation and Performance – Proceedings of the 31th eCAADe Conference, 1, 549--558.
  61. Weimar, F., La Magna, R., Reichert, S., Schwinn, T., Knippers, J., & Menges, A. (2013). Integrated design methods for the simulation of fibre-based structures. Rethinking Prototyping - Proceedings of the Design Modelling Symposium Berlin 2013, 277--290.
  62. Ahlquist, S., & Menges, A. (2012). Physical Drivers: Synthesis of Evolutionary Developments and Force-Driven Design. Architectural Design, 82(2), 60--67.
  63. Dierichs, K., & Menges, A. (2012). Aggregate Architectures, Observing and Designing with Changeable Material Systems in Architecture. Change, Architecture, Education, Practices – Proceedings of the International ACSA Conference, Barcelona, Spain, 463--468.
  64. Dierichs, K., & Menges, A. (2012). Aggregate Structures: Material and Machine Computation of Designed Granular Substances. Architectural Design, 82(2), 74--81.
  65. Dierichs, K., & Menges, A. (2012). Functionally Graded Aggregate Structures: Digital Additive Manufacturing with Designed Granulates. Proceedings of the 32nd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), 295--304.
  66. Dierichs, K., & Menges, A. (2012). Material and Machine Computation of Designed Granular Matter: Rigid-Body Dynamics Simulations as a Design Tool for Robotically-Poured Aggregate Structures Consisting of Polygonal Concave Particles. Digital Physicality – Proceedings of the 30th eCAADe Conference, 711--719.
  67. Dierichs, K., Schwinn, T., & Menges, A. (2012). Robotic Pouring of Aggregate Structures - Responsive Motion Planning Strategies for Online Robot Control of Granular Pouring Processes with Synthetic Macro-Scale Particles. Proceedings of the Robots in Architecture Conference 2012, 196--205.
  68. Fleischmann, M., & Menges, A. (2012). Physics-Based Modeling as an alternative approach to geometrical constrain-modeling for the design of elastically-deformable material systems. Digital Physicality – Proceedings of the 30th eCAADe Conference, 565--575.
  69. Fleishmann, M., Knippers, J., Leinhard, J., Menges, A., & Schleicher, S. (2012). Material Behaviour: Embedding Physical Properties in Computational Design Processes. Architectural Design, 82(2), 44--51.
  70. Irlwek, M., & Menges, A. (2012). The extension of Rittel´s methodology in contemporary parametric design. International Journal of Design Sciences and Technology, 19(1), 1--25.
  71. Knippers, J., Menges, A., Gabler, M., La Magna, R., Waimer, F., Reichert, S., & Schwinn, T. (2012). From Nature to Fabrication: Biomimetic Design Principles for the Production of Complex Spatial Structures. Advances in Architectural Geometry 2012, 107--122.
  72. Krieg, O., Mihaylov, B., Schwinn, T., Reichert, S., & Menges, A. (2012). Computational Design of Robotically Manufactured Plate Structures Based on Biomimetic Design Principles Derived from Clypeasteroida. Digital Physicality – Proceedings of the 30th eCAADe Conference, 531--540.
  73. Ladurner, G., Gabler, M., Menges, A., & Knippers, J. (2012). Interactive Form-Finding for Biomimetic Fibre Structures: Development of a Computational Design Tool and Physical Fabrication Technique Based on the Biological Structure of the Lichen. Digital Physicality – Proceedings of the 30th eCAADe Conference, 519--529.
  74. Menges, A. (2012). Biomimetic design processes in architecture: morphogenetic and evolutionary computational design. Bioinspiration and Biomimetics, 7(1), Article 1. https://doi.org/10.1088/1748-3182/7/1/015003
  75. Menges, A., & Reichert, S. (2012). Material Capacity: Embedded Responsiveness. Architectural Design, 82(2), 52--59.
  76. Menges, A. (2012). Material Resourcefulness: Activating Material Information in Computational Design. Architectural Design, 82(2), 34--43.
  77. Menges, A. (2012). Morphospaces of Robotic Fabrication - From theoretical morphology to design computation and digital fabrication in architecture. Proceedings of the Robots in Architecture Conference 2012, 28--47. https://doi.org/10.1007/978-3-7091-1465-0_3
  78. Parascho, S., Baur, M., Knippers, J., & Menges, A. (2012). Integrative Design Methods in Architecture: An agent-based Modelling Tool for Integrative Design. Proceedings of the Conference of Integrated Planning Processes 2012, 221--233.
  79. Schwinn, T., Krieg, O., Menges, A., Mihaylov, B., & Reichert, S. (2012). Machinic Morphospaces: Biomimetic Design Strategies for the Computational Exploration of Robot Constraint Spaces for Wood Fabrication. Proceedings of the 32nd Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), 157--168.
  80. Schwinn, T., Krieg, O., & Menges, A. (2012). Robotically Fabricated Wood Plate Morphologies - Robotic Prefabrication of a Biomimetic, Geometrically Differentiated Lightweight Finger Joint Timber Plate Structure. Proceedings of the Robots in Architecture Conference 2012, 28--47.
  81. Ahlquist, S., & Menges, A. (2011). Articulated Behavior: Computational Methods for the Generation and Materialization of Complex Force-Active Textile Morphologies. Proceedings of the Ambience’11 International Conference, 13--19.
  82. Ahlquist, S., & Menges, A. (2011). Behavior-based Computational Design Methodologies - Integrative Processes for Force Defined Material Structures. Integration through Computation, Proceedings of the 31th Conference of the Association For Computer Aided Design In Architecture (ACADIA), 82--89.
  83. Ahlquist, S., & Menges, A. (2011). Integration of Behaviour-based Computational and Physical Models: Design Computation and Materialisation of Morphologically Complex Tension-Active Systems. Computational Design Modeling, Proceedings of the Design Modeling Symposium Berlin, 259--266. https://doi.org/10.1007/978-3-642-23435-4_9
  84. Ahlquist, S., & Menges, A. (2011). Methodological Approach for the Integration of Material Information and Performance in the Design Computation for Tension-Active Architectural Systems. Proceedings of the 29th eCAADE Conference, 799--807.
  85. Busch, B., Ladurner, G., Baharlou, E., & Menges, A. (2011). Adaptive Structure: A Modular System for Generative Architecture. XIV Generative Art - Proceedings of GA2011 International Conference, 88--98.
  86. Dierichs, K., Fleissner, F., & Menges, A. (2011). Interrelation of experiment and simulation in the development of Aggregate Architectures. Digital Proceedings of the International Symposion on Algorithmic Design for Architecture and Urban Design (ALGODE) in Tokyo (Japan).
  87. Fleischmann, M., & Menges, A. (2011). ICD/ITKE Research Pavilion: A case study of multi-disciplinary computational design. Computational Design Modeling, Proceedings of the Design Modeling Symposium Berlin, 239--248. https://doi.org/10.1007/978-3-642-23435-4_27
  88. Irlwek, M., & Menges, A. (2011). Variant Generation and Convergence in Computational Design Processes based on Horst Rittel´s Design Methodology. Connecting Brains Shaping the World – Collaborative Design Spaces, EuropIA 13 Conference 2011, 139--158.
  89. Krieg, O., Dierichs, K., Reichert, S., Schwinn, T., & Menges, A. (2011). Performative architectural morphology: Finger-joined plate structures integrating robotic manufacturing, biological principles and location-specific requirements. Computational Design Modeling, Proceedings of the Design Modeling Symposium Berlin, 259--266.
  90. Krieg, O., Dierichs, K., Reichert, S., Schwinn, T., & Menges, A. (2011). Performative architectural morphology: Robotically manufactured biomimetic finger-joined plate structures. Proceedings of the 29th eCAADE Conference, 573--580.
  91. Lienhard, J., Fleishmann, M., & Menges, A. (2011). Computational Design Synthesis: Embedding Material Behaviour in Generative Computational Processes. Proceedings of the 29th eCAADE Conference, 759--767.
  92. Menges, A. (2011). Integrative Design Computation: Integrating Material Behaviour and Robotic Manufacturing Processes in Computational Design for Performative Wood Constructions. Proceedings of the 31th Conference of the Association For Computer Aided Design In Architecture (ACADIA), 72--81.
  93. Menges, A., Schleicher, S., & Fleishmann, M. (2011). Research Pavilion ICD/ITKE. Proceedings of the Fabricate: Making Digital Architecture Conference, 22--27.
  94. Menges, A. (2011). Simple Systems – Complex Capacities: Integrative Processes of Computational Morphogenesis in Architecture. TECHNE Journal of Technology for Architecture and Environment, 02/2011, 68--77.
  95. Spaeth, A. B., & Menges, A. (2011). Performative Design for Spatial Acoustics – Concept for an evolutionary design algorithm based on acoustics as design driver. Proceedings of the 29th eCAADE Conference, 461--468.
  96. Ahlquist, S., & Menges, A. (2010). Realizing Formal and Functional Complexity for Structurally Dynamic Systems in Rapid Computational Means. Proceedings of Advances in Architectural Geometry Conference 2010, 205--220.
  97. Dierichs, K., & Menges, A. (2010). Material Computation in Architectural Aggregate Systems. Formation, Proceeding of the 30th Conference of the Association For Computer Aided Design In Architecture (ACADIA), 372--378.
  98. Menges, A. (2010). Integral Computational Design: Synthesizing Computation and Materialization in Architecture. AMIT International Journal for Architecture and Modern Information Technologies, 4(3), Article 3.
  99. Menges, A. (2010). Material Information: Integrating Material Characteristics and Behavior in Computational Design for Performative Wood Construction. Formation, Proceeding of the 30th Conference of the Association For Computer Aided Design In Architecture (ACADIA), 151--158.
  100. Reichert, S., & Menges, A. (2010). Responsive Surface Structures. Bionik: Patente aus der Natur, Proceedings of Fifth Bionics Conference, 28--35.

Best Practices

  1. Garbuglia, F., Saenen, B., Gaillard, V., & Engelhardt, C. (2021). D7.5 Good Practices in FAIR Competence Education. Zenodo. https://doi.org/10.5281/zenodo.5785253
  2. Kümmet, S., Lücke, S., Schulz, J., Spenger, M., & Weber, T. (2019). DataCite Best Practice Guide. Zenodo. https://doi.org/10.5281/zenodo.3559799
  3. Ostendorff, P., & Linke, D. (2019). Best-Practices im Umgang mit rechtlichen Fragestellungen zum Forschungsdatenmanagement (FDM). Bibliotheksdienst, 53(10–11), Article 10–11. https://doi.org/10.1515/bd-2019-0098
  4. Austin, C. C., Bloom, T., Dallmeier-Tiessen, S., Khodiyar, V. K., Murphy, F., Nurnberger, A., Raymond, L., Stockhause, M., Tedds, J., Vardigan, M., & Whyte, A. (2017). Key components of data publishing: using current best practices to develop a reference model for data publishing. International Journal on Digital Libraries, 18(2), 77--92. https://doi.org/10.1007/s00799-016-0178-2
  5. Fehr, J., and Jan Heiland, Himpe, C., & Saak, J. (2016). Best practices for replicability, reproducibility and reusability of computer-based experiments exemplified by model reduction software. AIMS Mathematics, 1(3), 261--281. https://doi.org/10.3934/math.2016.3.261

Beschreibung von Forschungsdaten

  1. Schembera, B., & Iglezakis, D. (o. J.). The Genesis of EngMeta - A Metadata Model for Research Data in Computational Engineering. In Metadata and Semantic Research. 12th International Conference, MTSR 2018, Limassol, Cyprus, 23-26 October 2018, Proceedings. Springer.
  2. Hirsch, M., Iglezakis, D., Leymann, F., & Zimmermann, M. (2022). The ReSUS Project - Infrastructure for Sharing Research Software. In E-Science-Tage 2021: Share Your Research Data (S. 267–276). heiBOOKS. https://doi.org/10.11588/HEIBOOKS.979.C13737
  3. Anzt, H., Bach, F., Druskat, S., Löffler, F., Loewe, A., Renard, B. Y., Seemann, G., Struck, A., Achhammer, E., Aggarwal, P., Appel, F., Bader, M., Brusch, L., Busse, C., Chourdakis, G., Dabrowski, P. W., Ebert, P., Flemisch, B., Friedl, S., … Weeber, R. (2021). An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action. F1000Research, 9, 295. https://doi.org/10.12688/f1000research.23224.2
  4. de Vries, J., Tykhonov, V., Scharnhorst, A., Indarto, E., & Admiraal, F. (2021). Flexible metadata schemes for research data repositories -  The Common Framework in Dataverse and the CMDI use case. In M. Monachini & M. Eskevich (Hrsg.), Proceedings of the CLARIN Annual Conference 2021 (S. 109–118).
  5. Horsch, M. T., Morgado, J. F., Goldbeck, G., Iglezakis, D., Konchakova, N. A., & Schembera, B. (2021). Domain-specific metadata standardization in materials modelling. Domain Ontologies for Research Data Management in Industry Commons of Materials and Manufacturing. https://openreview.net/forum?id=uYgdGd7_wgH
  6. Iglezakis, D., Fuhrmans, M., Arndt, S., Demandt, É., Hachinger, S., Hausen, D., Lanza, G., Lipp, J., Stotzka, R., & Terzijska, D. (2021). Interoperabilität von Metadaten innerhalb der NFDI: Konsortienübergreifender Metadaten-Workshop am 2./3. Juli 2020. Bausteine Forschungsdatenmanagement, 2, 124–135. https://doi.org/10.17192/bfdm.2021.2.8313
  7. Iglezakis, D., Fuhrmans, M., Arndt, S., Demandt, É., Hachinger, S., Hausen, D., Lanza, G., Lipp, J., Stotzka, R., & Terzijska, D. (2021). Interoperabilität von Metadaten innerhalb der NFDI: Konsortienübergreifender Metadaten-Workshop am 2./3. Juli 2020. Bausteine Forschungsdatenmanagement, 2, 124–135. https://doi.org/10.17192/bfdm.2021.2.8313
  8. Schembera, B. (2021). Like a rainbow in the dark: metadata annotation for HPC applications in the age of dark data. The Journal of Supercomputing. https://doi.org/10.1007/s11227-020-03602-6
  9. Wu, M., Juty, N., Research Metadata Schemas WG, R., Collins, J., Duerr, R., Ridsdale, C., Shepherd, A., Verhey, C., & Jael Castro, L. (2021). Guidelines for publishing structured metadata on the web (R. D. Alliance, Hrsg.). https://www.rd-alliance.org/system/files/documents/Guidelines%20for%20publishing%20structured%20data_V3.0_20210615.pdf
  10. Hermann, S., Schneider, M., Flemisch, B., Frey, S., Iglezakis, D., Ruf, M., Schembera, B., Seeland, A., & Steeb, H. (2020). Datenmanagement im SFB 1313. Bausteine Forschungsdatenmanagement, 1, 28–38. https://doi.org/10.17192/bfdm.2020.1.8085
  11. Hermann, S., Schneider, M., Flemisch, B., Frey, S., Iglezakis, D., Ruf, M., Schembera, B., Seeland, A., & Steeb, H. (2020). Datenmanagement im SFB 1313. Bausteine Forschungsdatenmanagement, 1, 28–38. https://doi.org/10.17192/bfdm.2020.1.8085
  12. Hub, T. C. I. (Hrsg.). (2020). A survey of Top-Level Ontologies.
  13. Hugo, W., Le Franc, Y., Coen, G., Parland-von Essen, J., & Bonino, L. (2020). D2.5 FAIR Semantics Recommendations Second Iteration. https://doi.org/10.5281/ZENODO.4314321
  14. Kesper, A., Wenz, V., & Taentzer, G. (2020). Detecting Quality Problems in Research Data: A Model-Driven Approach. http://arxiv.org/abs/2007.11298
  15. Schembera, B., & Iglezakis, D. (2020). EngMeta - Metadata for Computational Engineering. International Journal of Metadata, Semantics and Ontologies, 14(1), 26–38. https://doi.org/10.1504/IJMSO.2020.107792
  16. Selent, B., Kraus, H., Hansen, N., Schembera, B., Seeland, A., & Iglezakis, D. (2020). Management of Research Data in Computational Fluid Dynamics and Thermodynamics. In V. Heuveline, F. Gebhart, & N. Mohammadianbisheh (Hrsg.), E-Science-Tage 2019: Data to Knowledge (S. 128–139). HeiBOOKS. https://doi.org/10.11588/heibooks.598
  17. Grunzke, R., Hartmann, V., Jejkal, T., Kollai, H., Prabhune, A., Herold, H., Deicke, A., Dressler, C., Dolhoff, J., Stanek, J., Hoffmann, A., Müller-Pfefferkorn, R., Schrade, T., Meinel, G., Herres-Pawlis, S., & Nagel, W. E. (2019). The MASi repository service — Comprehensive, metadata-driven and multi-community research data management. Future Generation Computer Systems, 94, 879–894. https://doi.org/10.1016/j.future.2017.12.023
  18. Horsch, M. T., Niethammer, C., Boccardo, G., Carbone, P., Chiacchiera, S., Chiricotto, M., Elliott, J. D., Lobaskin, V., Neumann, P., Schiffels, P., Seaton, M. A., Todorov, I. T., Vrabec, J., & Cavalcanti, W. L. (2019). Semantic Interoperability and Characterization of Data Provenance in Computational Molecular Engineering. Journal of Chemical & Engineering Data, 65(3), 1313--1329. https://doi.org/10.1021/acs.jced.9b00739
  19. Iglezakis, D., & Schembera, B. (2019). EngMeta - a Metadata Scheme for the Engineering Sciences. DaRUS. https://doi.org/10.18419/darus-500
  20. Iglezakis, D. (2019). Relevance of Different Metadata Fields for the Description of Research Data from the Engineering Sciences (DaRUS, Hrsg.). https://doi.org/10.18419/darus-501
  21. Kümmet, S., Lücke, S., Schulz, J., Spenger, M., & Weber, T. (2019). DataCite Best Practice Guide. Zenodo. https://doi.org/10.5281/zenodo.3559799
  22. Schembera, B., & Iglezakis, D. (2019). The Genesis of EngMeta - A Metadata Model for Research Data in Computational Engineering. In E. Garoufallou, F. Sartori, R. Siatri, & M. Zervas (Hrsg.), Metadata and Semantic Research (Nr. 846; Nummer 846, S. 127–132). Springer International Publishing. https://doi.org/10.1007/978-3-030-14401-2_12
  23. Schembera, B., & Iglezakis, D. (2019). The Genesis of EngMeta - A Metadata Model for Research Data in Computational Engineering. In E. Garoufallou, F. Sartori, R. Siatri, & M. Zervas (Hrsg.), Metadata and Semantic Research (Nr. 846; Nummer 846, S. 127–132). Springer International Publishing. https://doi.org/10.1007/978-3-030-14401-2_12
  24. Selent, B., Schembera, B., Iglezakis, D., & Seeland, A. (2019). Datenmanagement in Infrastrukturen, Prozessen und Lebenszyklen für die Ingenieurwissenschaften : Abschlussbericht des BMBF-Projektes Dipl-Ing. Universität Stuttgart; https://doi.org/10.2314/KXP:1693393980
  25. Sprenger, J., Zehl, L., Pick, J., Sonntag, M., Grewe, J., Wachtler, T., Grün, S., & Denker, M. (2019). odMLtables: A User-Friendly Approach for Managing Metadata of Neurophysiological Experiments. Ludwig-Maximilians-Universität München. https://epub.ub.uni-muenchen.de/69215/
  26. Balatsoukas, P., Rousidis, D., & Garoufallou, E. (2018). A method for examining metadata quality in open research datasets using the OAI-PMH and SQL queries: the case of the Dublin Core „Subject“ element and suggestions for user-centred metadata annotation design. IJMSO, 13(1), 1–8. http://dblp.uni-trier.de/db/journals/ijmso/ijmso13.html#BalatsoukasRG18
  27. Brown, C., Hong, N. C., & Jackson, M. (2018). Software Deposit And Preservation Policy And Planning Workshop Report. https://doi.org/10.5281/zenodo.1250310
  28. Fowler, D., Barratt, J., & Walsh, P. (2018). Frictionless Data: Making Research Data Quality Visible. International Journal of Digital Curation, 12(2), Article 2. https://doi.org/10.2218/ijdc.v12i2.577
  29. Gärtner, M., Hahn, U., & Hermann, S. (2018). Preserving Workflow Reproducibility: The RePlay-DH Client as a Tool for Process Documentation. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Hrsg.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (S. 563--570). European Language Resources Association (ELRA).
  30. Gärtner, M., Hahn, U., & Hermann, S. (2018). Preserving Workflow Reproducibility: The RePlay-DH Client as a Tool for Process Documentation. In N. C. (Conference chair), K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Hrsg.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). European Language Resources Association (ELRA).
  31. Group, D. M. W. (2017). DataCite Metadata Schema for the Publication and Citation of Research Data. Version 4.1. https://doi.org/10.5438/0015
  32. Hellerstein, J. M., Sreekanti, V., Gonzalez, J. E., Dalton, J., Dey, A., Nag, S., Ramachandran, K., Arora, S., Bhattacharyya, A., Das, S., & others. (2017). Ground: A Data Context Service. CIDR.
  33. Jones, M. B., Boettiger, C., Mayes, A. C., Smith, A., Slaughter, P., Niemeyer, K., Gil, Y. G., Fenner, M., Nowak, K., Hahnel, M., Coy, L., Allen, A., Crosas, M., Sands, A., Hong, N. C., Cruse, P., Katz, D., & Goble, C. (2017). CodeMeta: an exchange schema for software metadata. Version 2.0. https://doi.org/10.5063/schema/codemeta-2.0
  34. Schembera, B., & Bönisch, T. (2017). Challenges of Research Data Management for High Performance Computing. International Conference on Theory and Practice of Digital Libraries, 140--151. https://link.springer.com/chapter/10.1007/978-3-319-67008-9_12
  35. Stein, A., Applegate, K. J., & Robbins, S. (2017). Achieving and Maintaining Metadata Quality: Toward a Sustainable Workflow for the IDEALS Institutional Repository. Cataloging & Classification Quarterly, 55(7–8), 644–666. https://doi.org/10.1080/01639374.2017.1358786
  36. Wilkinson, M. D., Sansone, S.-A., Schultes, E., Doorn, P., Bonino da Silva Santos, L. O., & Dumontier, M. (2017). A design framework and exemplar metrics for FAIRness. bioRxiv. https://doi.org/10.1101/225490
  37. Kohwalter, T., Oliveira, T., Freire, J., Clua, E., & Murta, L. (2016). Prov Viewer: A Graph-Based Visualization Tool for Interactive Exploration of Provenance Data. In M. Mattoso & B. Glavic (Hrsg.), Provenance and Annotation of Data and Processes (S. 71--82). Springer International Publishing.
  38. Neumaier, S., Umbrich, J., & Polleres, A. (2016). Automated quality assessment of metadata across open data portals. Journal of Data and Information Quality (JDIQ), 8(1), 2.
  39. Pimentel, J. F., Freire, J., Braganholo, V., & Murta, L. (2016). Tracking and Analyzing the Evolution of Provenance from Scripts. In M. Mattoso & B. Glavic (Hrsg.), Provenance and Annotation of Data and Processes (S. 16--28). Springer International Publishing.
  40. Pizzi, G., Cepellotti, A., Sabatini, R., Marzari, N., & Kozinsky, B. (2016). AiiDA: automated interactive infrastructure and database for computational science. Computational Materials Science, 111, 218–230. https://doi.org/10.1016/j.commatsci.2015.09.013
  41. Schreiber, A. (2016). Standardisierung eines erweiterbaren Modells für Provenance-Daten (PROV-SPEC) (Nr. 2016–04). 2016–04, Article 2016–04.
  42. Wu, K., Coviello, E. N., Flanagan, S. M., Greenwald, M., Lee, X., Romosan, A., Schissel, D. P., Shoshani, A., Stillerman, J., & Wright, J. (2016). MPO: A System to Document and Analyze Distributed Heterogeneous Workflows. In M. Mattoso & B. Glavic (Hrsg.), Provenance and Annotation of Data and Processes (S. 166--170). Springer International Publishing.
  43. Belhajjame, K., Zhao, J., Garijo, D., Gamble, M., Hettne, K., Palma, R., Mina, E., Corcho, O., Gómez-Pérez, J. M., Bechhofer, S., Klyne, G., & Goble, C. (2015). Using a suite of ontologies for preserving workflow-centric research objects. Journal of Web Semantics, 32, 16–42. https://doi.org/10.1016/j.websem.2015.01.003
  44. Belhajjame, K., Zhao, J., Garijo, D., Gable, M., Hettne, K., Palma, R., Mina, E., Corcho, O., Gómez-Pérez, J. M., Bechofer, S., Klyne, G., & Goble, C. (2015). Using a suite of ontologies for preserving workflow-centric research objects. Web Semantics: Science, Services and Agents on the World Wide Web, 32, 16–42. https://doi.org/10.1016/j.websem.2015.01.003
  45. Cai, L., & Zhu, Y. (2015). The Challenges of Data Quality and Data Quality Assessment in the Big Data Era. Data Science Journal, 14(0), 2. https://doi.org/10.5334/dsj-2015-002
  46. Chao, T. (2015). Mapping Methods Metadata for Research Data. International Journal of Digital Curation, 10(1), Article 1. https://doi.org/10.2218/ijdc.v10i1.347
  47. Moreau, L., Groth, P., Cheney, J., Lebo, T., & Miles, S. (2015). The rationale of PROV. Web Semantics: Science, Services and Agents on the World Wide Web, 35(4), 235–257. https://doi.org/10.1016/j.websem.2015.04.001
  48. Rasaiah, B. A., Jones, S. D., Bellman, C., Malthus, T. J., & Hueni, A. (2015). Assessing Field Spectroscopy Metadata Quality. Remote Sensing, 7(4), 4499–4526. http://dblp.uni-trier.de/db/journals/remotesensing/remotesensing7.html#RasaiahJBMH15
  49. Rasaiah, B. A., Bellman, C., Jones, S. D., Malthus, T. J., & Roelfsema, C. M. (2015). Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications. Remote Sensing, 7(11), 15668–15701. http://dblp.uni-trier.de/db/journals/remotesensing/remotesensing7.html#RasaiahBJMR15
  50. Starr, J., Castro, E., Crosas, M., Dumontier, M., Downs, R. R., Duerr, R., Haak, L. L., Haendel, M., Herman, I., Hodson, S., Hourclé, J., Kratz, J. E., Lin, J., Nielsen, L. H., Nurnberger, A., Proell, S., Rauber, A., Sacchi, S., Smith, A., … Clark, T. (2015). Achieving human and machine accessibility of cited data in scholarly publications. PeerJ Computer Science. https://doi.org/10.7717/peerj-cs.1
  51. Amorim, R., Aguiar Castro, J., Rocha, J., & Ribeiro, C. (2014). LabTablet: Semantic Metadata Collection on a Multi-domain Laboratory Notebook. Communications in Computer and Information Science, 478, 193–205. https://doi.org/10.1007/978-3-319-13674-5_19
  52. Brauer, P., Czerniak, A., & Hasselbring, W. (2014). Start Smart and Finish Wise: The Kiel Marine Science Provenance-Aware Data Management Approach. In A. Chapman, B. Ludäscher, & A. Schreiber (Hrsg.), TAPP. USENIX Association. http://dblp.uni-trier.de/db/conf/tapp/tapp2014.html#BrauerCH14
  53. Farnel, S., & Shiri, A. (2014). Metadata for Research Data: Current Practices and Trends. In W. E. Moen & A. Rushing (Hrsg.), Dublin Core Conference (S. 74–82). Dublin Core Metadata Initiative. http://dblp.uni-trier.de/db/conf/dc/dc2014.html#FarnelS14
  54. Grunzke, R., Hesser, J., Starek, J., Kepper, N., Gesing, S., Hardt, M., Hartmann, V., Kindermann, S., Potthoff, J., Hausmann, M., Müller-Pfefferkorn, R., & Jäkel, R. (2014). Device-Driven Metadata Management Solutions for Scientific Big Data Use Cases. 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 317–321.
  55. Grunzke, R., Breuers, S., Gesing, S., Herres-Pawlis, S., Kruse, M., Blunk, D., de la Garza, L., Packschies, L., Schäfer, P., Schärfe, C., Schlemmer, T., Steinke, T., Schuller, B., Müller-Pfefferkorn, R., Jäkel, R., Nagel, W. E., Atkinson, M., & Krüger, J. (2014). Standards-based metadata management for molecular simulations. Concurrency and Computation: Practice and Experience, 26(10), 1744--1759. https://doi.org/10.1002/cpe.3116
  56. Grunzke, R., Breuers, S., Gesing, S., Herres-Pawlis, S., Kruse, M., Blunk, D., de la Garza, L., Packschies, L., Schäfer, P., Schärfe, C., Schlemmer, T., Steinke, T., Schuller, B., Müller-Pfefferkorn, R., Jäkel, R., Nagel, W. E., Atkinson, M. P., & Krüger, J. (2014). Standards-based metadata management for molecular simulations. Concurrency and Computation: Practice and Experience, 26(10), 1744–1759. http://dblp.uni-trier.de/db/journals/concurrency/concurrency26.html#GrunzkeBGHKBGPSSSSSMJNA014
  57. Malik, T. (2014). Geobase: Indexing NetCDF Files for large-scale Data Analysis. In Big Data Management, Technologies, and Applications (S. 295--313). IGI Global. https://doi.org/10.4018/978-1-4666-4699-5.ch012
  58. Rousidis, D., Sicilia, M.-Á., Garoufallou, E., & Balatsoukas, P. (2014). Data Quality Issues and Content Analysis for Research Data Repositories : The Case of Dryad. In P. Polydoratou & M. Dobreva (Hrsg.), ELPUB (S. 49–58). IOS Press. http://dblp.uni-trier.de/db/conf/elpub/elpub2014.html#RousidisSGB14
  59. Rousidis, D., Garoufallou, E., Balatsoukas, P., & Sicilia, M.-Á. (2014). Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories. Inf. Services and Use, 34(3–4), 279–286. http://dblp.uni-trier.de/db/journals/isu/isu34.html#RousidisGBS14
  60. Tran, H. D., Holt, J., Goodrich, R. W., Mader, J. A., Swain, M., Laity, A. C., Kong, M., Gelino, C. R., & Berriman, G. B. (2014). Metadata and Data Management for the Keck Observatory Archive. https://doi.org/10.1117/12.2054830
  61. Bechhofer, S., Buchan, I., de Roure, D., Missier, P., Ainsworth, J., Bhagat, J., Couch, P., Cruickshank, D., Delderfield, M., Dunlop, I., Gamble, M., Michaelides, D., Owen, S., Newman, D., Sufi, S., & Goble, C. (2013). Why linked data is not enough for scientists. Future Generation Computer Systems, 29(2), 599–611. https://doi.org/10.1016/j.future.2011.08.004
  62. Lebo, T., Sahoo, S., McGuinness, D., Belhajjame, K., Cheney, J., Corsar, D., Garijo, D., Soiland-Reyes, S., Zednik, S., & Zhao, J. (2013). PROV-O: The PROV Ontology. https://www.w3.org/TR/prov-o/
  63. Sahoo, S., Lebo, T., & McGuinness, D. (2013). PROV-O: The PROV Ontology [W3C Recommendation]. W3C.
  64. Grewe, J., Wachtler, T., & Benda, J. (2011). A Bottom-up Approach to Data Annotation in Neurophysiology. Frontiers in Neuroinformatics, 5. https://doi.org/10.3389/fninf.2011.00016
  65. Han, J., Miller, J. A., & Silver, G. A. (2011). SoPT: Ontology for simulation optimization for scientific experiments. Proceedings of the 2011 Winter Simulation Conference (WSC), 2909–2920. https://doi.org/10.1109/WSC.2011.6147994
  66. Murray-Rust, P., & Rzepa, H. S. (2011). CML: Evolution and design. J. Cheminformatics, 3, 44. http://dblp.uni-trier.de/db/journals/jcheminf/jcheminf3.html#Murray-RustR11
  67. Murray-Rust, P., Townsend, J., Adams, S. E., Phadungsukanan, W., & Thomas, J. (2011). The semantics of Chemical Markup Language (CML): dictionaries and conventions. J. Cheminformatics, 3, 43. http://dblp.uni-trier.de/db/journals/jcheminf/jcheminf3.html#Murray-RustTAPT11
  68. Haslhofer, B., & Klas, W. (2010). A survey of techniques for achieving metadata interoperability. ACM Comput. Surv., 42(2), 7:1-7:37. https://doi.org/10.1145/1667062.1667064
  69. Park, J.-R., & Tosaka, Y. (2010). Metadata Quality Control in Digital Repositories and Collections: Criteria, Semantics, and Mechanisms. Cataloging & Classification Quarterly, 48(8), 696–715. https://doi.org/10.1080/01639374.2010.508711
  70. Park, J.-R. (2009). Metadata Quality in Digital Repositories: A Survey of the Current State of the Art. Cataloging & Classification Quarterly, 47(3–4), 213–228. https://doi.org/10.1080/01639370902737240
  71. Hillmann, D. I. (2008). Metadata Quality: From Evaluation to Augmentation. Cataloging & Classification Quarterly, 46(1), 65–80. https://doi.org/10.1080/01639370802183008
  72. Vardigan, M., Heus, P., & Thomas, W. (2008). Data Documentation Initiative: Toward a Standard for the Social Sciences. IJDC, 3(1), 107–113. https://doi.org/10.2218/ijdc.v3i1.45
  73. Bruce, T. R., & Hillmann, D. I. (2004). The Continuum of Metadata Quality: Defning, Expression, Exploiting: Bd. Metadata in Practice. ALA Editions.
  74. Lautenschlager, M., Toussaint, F., Thiemann, H., & Reinke, M. (1998). The CERA-2 data model. https://www.pik-potsdam.de/cera/Descriptions/Publications/Papers/9807_DKRZ_TechRep15/cera2.pdf

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