@online{_linkahead_2023,
  title = {{{LinkAhead}}},
  date = {2023-10-05},
  abstract = {LinkAhead is a Free and Open-Source data management system toolkit. More information is available at https://getlinkahead.com .},
  langid = {english},
  organization = {{GitLab}},
  note = {Website: \url{https://getlinkahead.com}, Source code: \url{https://gitlab.com/linkahead}}
}

@online{_linkaheadenhancement_2023,
  title = {{{LinkAhead Enhancement Requests}}},
  date = {2023-10-05},
  url = {https://gitlab.com/groups/linkahead/-/issues?or[label_name][]=Enhancement%3A%3AAccepted&or[label_name][]=Enhancement%3A%3AProposed&state=opened},
  urldate = {2023-10-05},
  abstract = {LinkAhead is a Free and Open-Source data management system toolkit. More information is available at https://getlinkahead.com .},
  langid = {english},
  organization = {{GitLab - LinkAhead}}
}

@online{_linkaheadmatrix_2023,
  title = {\#linkahead on {{Matrix}} Chat},
  date = {2023-10-05},
  url = {https://matrix.to/#/#linkahead:matrix.org},
  urldate = {2023-10-05}
}

@online{_linkaheadquery_2023,
  title = {{{LinkAhead Query Language Examples}} — LinkAhead-Server 0.11.0 Documentation},
  date = {2023},
  url = {https://docs.indiscale.com/caosdb-server/LinkAhead-Query-Language.html},
  urldate = {2023-10-05}
}

@online{_linkaheadtrino_2023,
  title = {{{LinkAhead Trino}} Branch},
  date = {2023-10-05},
  url = {https://gitlab.com/linkahead/linkahead-server/-/tree/f-experiment-trino},
  urldate = {2023-10-05},
  abstract = {GitLab},
  langid = {english},
  organization = {{GitLab LinkAhead}}
}

@software{_dataverse_2023,
  title = {Dataverse},
  date = {2023-07-07},
  url = {https://dataverse.org/home},
  urldate = {2023-07-12},
  file = {/home/daniel/Zotero/storage/VLDTXPAW/dataverse.org.html}
}

@software{_elabjournal_,
  title = {{{eLabJournal}}},
  url = {https://www.elabnext.com/products/elabjournal/},
  abstract = {eLabJournal is a comprehensive electronic laboratory journal suitable for all laboratory environments, from small academic institutions and start-up companies to large academic institutions and global corporations. Besides the full electronic lab notebook solution, eLabJournal also enables you to streamline the entire workflow in a laboratory, including sample tracking, protocol management, device sharing and booking as well as managing supplies.},
  organization = {{eLabNext}}
}

@online{_elnconsortium_2023,
  title = {The {{ELN Consortium}}},
  date = {2023},
  url = {https://github.com/TheELNConsortium},
  urldate = {2023-07-12},
  abstract = {A consortium of ELN vendors. The ELN Consortium has 4 repositories available. Follow their code on GitHub.},
  langid = {english},
  organization = {{GitHub}},
  file = {/home/daniel/Zotero/storage/EVVBG457/TheELNConsortium.html}
}

@online{_r2rmlrdb_2012,
  title = {{{R2RML}}: {{RDB}} to {{RDF Mapping Language}}},
  date = {2012-09-27},
  url = {https://www.w3.org/TR/2012/REC-r2rml-20120927/},
  urldate = {2023-07-12},
  file = {/home/daniel/Zotero/storage/5MP59D25/REC-r2rml-20120927.html}
}

@software{_rspaceeln_,
  title = {{{RSpace ELN}}},
  location = {{Edinburgh, Scotland}},
  url = {https://www.researchspace.com/},
  urldate = {2023-07-12},
  organization = {{Research Space}},
  note = {Formerly eCAT from the University of Wisconsin.},
  file = {/home/daniel/Zotero/storage/89WCW366/www.researchspace.com.html}
}

@article{abdullah_investigatinginfluence_2016,
  title = {Investigating the Influence of the Most Commonly Used External Variables of {{TAM}} on Students' {{Perceived Ease}} of {{Use}} ({{PEOU}}) and {{Perceived Usefulness}} ({{PU}}) of e-Portfolios},
  author = {Abdullah, Fazil and Ward, Rupert and Ahmed, Ejaz},
  date = {2016-10-01},
  journaltitle = {Computers in Human Behavior},
  shortjournal = {Comput. Hum. Behav.},
  volume = {63},
  number = {C},
  pages = {75--90},
  issn = {0747-5632},
  doi = {10.1016/j.chb.2016.05.014},
  url = {https://doi.org/10.1016/j.chb.2016.05.014},
  abstract = {Engagement with e-portfolios has been shown to improve students' learning. However, what influences students to accept e-portfolios is a question that needs careful study. The purpose of this study is to investigate the influence of Self-Efficacy, Subjective Norm, Enjoyment, Computer Anxiety and Experience on students' Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of an e-portfolio system and their Behavioural Intention (BI) to use the system for learning. To do this, the study tested and used the General Extended Technology Acceptance Model for E-Learning (GETAMEL) in the context of e-portfolios. Valid data were collected from 242 UK undergraduate students who had been introduced to e-portfolios. The data set was analysed using SPSS software. Results showed that the best predictor of student's Perceived Ease of Use of the e-portfolio is Experience, followed by Enjoyment, Self-Efficacy and Subjective Norm. The best predictor of student's Perceived Usefulness of the e-portfolio is Perceived Ease of Use followed by Enjoyment. Both Perceived Ease of Use and Perceived Usefulness predict student's Behavioural Intention to Use the e-portfolio. The findings improve understanding regarding acceptance of e-portfolio systems and this work is therefore of particular interest to researchers, developers and practitioners of e-portfolios. We validated and used the GETAMEL to examine students' e-portfolio adoption.Four variables affected Perceived Ease of Use (PEOU) of the e-portfolio.The four variables are Experience, Enjoyment, Self-Efficacy and Subjective Norm.PEOU and Enjoyment affected Perceived Usefulness (PU) of the e-portfolio.Both PEOU and PU affected students' intention to use the e-portfolio.},
  keywords = {E-learning,E-portfolios,Technology Acceptance Model,Technology adoption},
  file = {/home/daniel/Zotero/storage/ULUP6UFA/Abdullah et al. - 2016 - Investigating the influence of the most commonly u.pdf}
}

@article{abujayyab_biologicaltreatment_2022,
  title = {Biological Treatment of Produced Water: {{A}} Comprehensive Review and Metadata Analysis},
  shorttitle = {Biological Treatment of Produced Water},
  author = {Abujayyab, Mohammed A. and Hamouda, Mohamed and Aly Hassan, Ashraf},
  date = {2022-02-01},
  journaltitle = {Journal of Petroleum Science and Engineering},
  shortjournal = {Journal of Petroleum Science and Engineering},
  volume = {209},
  pages = {109914},
  issn = {0920-4105},
  doi = {10.1016/j.petrol.2021.109914},
  url = {https://www.sciencedirect.com/science/article/pii/S0920410521015308},
  urldate = {2023-07-11},
  abstract = {A metadata analysis was conducted to analyze the impact of several operating conditions on the biological removal of chemical oxygen demand (COD) from produced water (PW). Operating conditions including temperature, salinity, oxygen availability, treatment technology, microorganism type, and treatment scale were investigated. No limiting maximum COD elimination capacity was reported in the literature, signaling the need to experiment with higher COD concentrations at reduced retention times to identify if such a limit exists. The maximum recorded COD elimination capacity of PW was achieved under low salinity and aerobic conditions in a membrane bioreactor using oil-degradation bacteria on a laboratory scale. Suspended growth exhibited maximum COD removal efficiency, and membrane bioreactors were the most studied technique and achieved the highest performance. Superior COD removal efficiency was realized under hypersaline conditions; however, the COD removal efficiency under freshwater conditions was higher than that under hypersaline conditions.},
  langid = {english},
  keywords = {COD removal,Oxygen availability,Salinity,Treatment process,Treatment scale},
  file = {/home/daniel/Zotero/storage/3IWJXMHP/S0920410521015308.html}
}

@article{ailamaki_managingscientific_2010,
  title = {Managing Scientific Data},
  author = {Ailamaki, Anastasia and Kantere, Verena and Dash, Debabrata},
  date = {2010-06-01},
  journaltitle = {Communications of the ACM},
  shortjournal = {Commun. ACM},
  volume = {53},
  number = {6},
  pages = {68--78},
  issn = {0001-0782},
  doi = {10.1145/1743546.1743568},
  url = {https://doi.org/10.1145/1743546.1743568},
  abstract = {Needed are generic, rather than one-off, DBMS solutions automating storage and analysis of data from scientific collaborations.},
  keywords = {data management,dms use sql},
  file = {/home/daniel/Zotero/storage/YIXKTYIB/Ailamaki et al. - 2010 - Managing scientific data.pdf}
}

@article{anderson_issuesbiomedical_2007,
  title = {Issues in {{Biomedical Research Data Management}} and {{Analysis}}: {{Needs}} and {{Barriers}}},
  shorttitle = {Issues in {{Biomedical Research Data Management}} and {{Analysis}}},
  author = {Anderson, Nicholas R. and Lee, E. Sally and Brockenbrough, J. Scott and Minie, Mark E. and Fuller, Sherrilynne and Brinkley, James and Tarczy-Hornoch, Peter},
  date = {2007-07-01},
  journaltitle = {Journal of the American Medical Informatics Association},
  shortjournal = {Journal of the American Medical Informatics Association},
  volume = {14},
  number = {4},
  pages = {478--488},
  issn = {1067-5027},
  doi = {10.1197/jamia.M2114},
  url = {https://doi.org/10.1197/jamia.M2114},
  abstract = {Objectives: A. Identify the current state of data management needs of academic biomedical researchers. B. Explore their anticipated data management and analysis needs. C. Identify barriers to addressing those needs.Design: A multimodal needs analysis was conducted using a combination of an online survey and in-depth one-on-one semi-structured interviews. Subjects were recruited via an e-mail list representing a wide range of academic biomedical researchers in the Pacific Northwest.Measurements: The results from 286 survey respondents were used to provide triangulation of the qualitative analysis of data gathered from 15 semi-structured in-depth interviews.Results: Three major themes were identified: 1) there continues to be widespread use of basic general-purpose applications for core data management; 2) there is broad perceived need for additional support in managing and analyzing large datasets; and 3) the barriers to acquiring currently available tools are most commonly related to financial burdens on small labs and unmet expectations of institutional support.Conclusion: Themes identified in this study suggest that at least some common data management needs will best be served by improving access to basic level tools such that researchers can solve their own problems. Additionally, institutions and informaticians should focus on three components: 1) facilitate and encourage the use of modern data exchange models and standards, enabling researchers to leverage a common layer of interoperability and analysis; 2) improve the ability of researchers to maintain provenance of data and models as they evolve over time though tools and the leveraging of standards; and 3) develop and support information management service cores that could assist in these previous components while providing researchers with unique data analysis and information design support within a spectrum of informatics capabilities.},
  file = {/home/daniel/Zotero/storage/DI888RU4/Anderson et al. - 2007 - Issues in Biomedical Research Data Management and .pdf;/home/daniel/Zotero/storage/XJGV97DP/788143.html}
}

@article{bauer_architecturebiomedical_2016,
  title = {Architecture of a {{Biomedical Informatics Research Data Management Pipeline}}},
  author = {Bauer, Christian R. and Umbach, Nadine and Baum, Benjamin and Buckow, Karoline and Franke, Thomas and Grütz, Romanus and Gusky, Linda and Nussbeck, Sara Yasemin and Quade, Matthias and Rey, Sabine and Rottmann, Thorsten and Rienhoff, Otto and Sax, Ulrich},
  date = {2016},
  journaltitle = {Exploring Complexity in Health: An Interdisciplinary Systems Approach},
  pages = {262--266},
  publisher = {{IOS Press}},
  doi = {10.3233/978-1-61499-678-1-262},
  url = {https://ebooks.iospress.nl/doi/10.3233/978-1-61499-678-1-262},
  keywords = {complexity},
  file = {/home/daniel/Zotero/storage/ZXPQU97G/Bauer et al. - 2016 - Architecture of a Biomedical Informatics Research .pdf}
}

@article{borgman_conundrumsharing_2012,
  title = {The Conundrum of Sharing Research Data},
  author = {Borgman, Christine L.},
  date = {2012},
  journaltitle = {Journal of the American Society for Information Science and Technology},
  volume = {63},
  number = {6},
  pages = {1059--1078},
  issn = {1532-2890},
  doi = {10.1002/asi.22634},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.22634},
  abstract = {We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, \& Alberts, ) Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice.},
  langid = {english},
  keywords = {collaboration,complexity,information policy,information reuse,motivation,research data sets},
  file = {/home/daniel/Zotero/storage/ZGTWWVVJ/asi.html}
}

@article{brandt_kadi4matresearch_2021,
  title = {{{Kadi4Mat}}: {{A Research Data Infrastructure}} for {{Materials Science}}},
  shorttitle = {{{Kadi4Mat}}},
  author = {Brandt, Nico and Griem, Lars and Herrmann, Christoph and Schoof, Ephraim and Tosato, Giovanna and Zhao, Yinghan and Zschumme, Philipp and Selzer, Michael},
  date = {2021-02-10},
  volume = {20},
  number = {1},
  pages = {8},
  publisher = {{Ubiquity Press}},
  issn = {1683-1470},
  doi = {10.5334/dsj-2021-008},
  url = {https://datascience.codata.org/articles/10.5334/dsj-2021-008},
  urldate = {2023-09-27},
  abstract = {The concepts and current developments of a research data infrastructure for materials science are presented, extending and combining the features of an electronic lab notebook and a repository. The objective of this infrastructure is to incorporate the possibility of structured data storage and data exchange with documented and reproducible data analysis and visualization, which finally leads to the publication of the data. This way, researchers can be supported throughout the entire research process. The software is being developed as a web-based and desktop-based system, offering both a graphical user interface and a programmatic interface. The focus of the development is on the integration of technologies and systems based on both established as well as new concepts. Due to the heterogeneous nature of materials science data, the current features are kept mostly generic, and the structuring of the data is largely left to the users. As a result, an extension of the research data infrastructure to other disciplines is possible in the future. The source code of the project is publicly available under a permissive Apache 2.0 license.},
  issue = {1},
  langid = {american},
  file = {/home/daniel/Zotero/storage/5YSWQZCJ/Brandt et al. - 2021 - Kadi4Mat A Research Data Infrastructure for Mater.pdf}
}

@article{bron_mediastudies_2016,
  title = {Media Studies Research in the Data-Driven Age: {{How}} Research Questions Evolve},
  shorttitle = {Media Studies Research in the Data-Driven Age},
  author = {Bron, Marc and Van Gorp, Jasmijn and family=Rijke, given=Maarten, prefix=de, useprefix=true},
  date = {2016},
  journaltitle = {Journal of the Association for Information Science and Technology},
  volume = {67},
  number = {7},
  pages = {1535--1554},
  issn = {2330-1643},
  doi = {10.1002/asi.23458},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23458},
  abstract = {The introduction of new technologies and access to new information channels continue to change the way media studies researchers work and the questions they seek to answer. We investigate the current practices of media studies researchers and how these practices affect their research questions. Through the analysis of 27 interviews about the research practices of media studies researchers during a research project we developed a model of the activities in their research cycle. We find that information gathering and analysis activities are dominating the research cycle. These activities influence the research outcomes as they determine how research questions asked by media studies researchers evolve. Specifically, we show how research questions are related to the availability and accessibility of data as well as new information sources for contextualization of the research topic. Our contribution is a comprehensive account of the overall research cycle of media studies researchers as well as specific aspects of the research cycle, i.e., information sources, information seeking challenges, and the development of research questions. This work confirms findings of previous work in this area using a previously unstudied group of researchers, as well as providing new details about how research questions evolve.},
  langid = {english},
  keywords = {humanities,information needs,information seeking},
  file = {/home/daniel/Zotero/storage/KLFPK28F/asi.html}
}

@online{bronger_juliabase_2023,
  title = {Introduction — {{JuliaBase}}, the Samples Database},
  author = {Bronger, Torsten},
  date = {2023},
  url = {https://www.juliabase.org/},
  urldate = {2023-09-27},
  file = {/home/daniel/Zotero/storage/WG4JI7WV/www.juliabase.org.html}
}

@online{caffaro_inveniomodern_2010,
  title = {Invenio: {{A Modern Digital Library}} for {{Grey Literature}}},
  shorttitle = {Invenio},
  author = {Caffaro, Jerome and Kaplun, Samuele},
  date = {2010},
  eprinttype = {CERN},
  location = {{Geneva}},
  url = {https://cds.cern.ch/record/1312678},
  urldate = {2023-07-12},
  abstract = {Grey literature has historically played a key role for researchers in the field of High- Energy Physics (HEP). Consequently CERN (European Organization for Nuclear Research) as the world’s largest particle physics laboratory has always been facing the challenge of distributing and archiving grey material. Invenio, an open-source repository software, has been developed as part of CERN’s institutional repository strategy to answer these needs. In this document we describe how the particular context of grey literature within the HEP community shaped the development of Invenio. We focus on the strategies that have been established in order to process grey material within the software and we analyse how it is used in a real production environment, the CERN Document Server (CDS).},
  pubstate = {preprint},
  note = {Sources: \url{https://github.com/inveniosoftware}},
  file = {/home/daniel/Zotero/storage/TK4ZXYSE/Caffaro and Kaplun - 2010 - Invenio A Modern Digital Library for Grey Literat.pdf}
}

@online{linkahead_humansmd_2023,
  title = {{{HUMANS}}.md},
  shorttitle = {{{HUMANS}}.md - {{LinkAhead}}},
  author = {{LinkAhead}},
  date = {2023-09-13},
  url = {https://gitlab.com/linkahead/linkahead/-/blob/main/HUMANS.md},
  urldate = {2023-10-05},
  abstract = {The meta repository for the LinkAhead project, for an overview and with important files. LinkAhead is a flexible research data management toolkit, which allows to change...},
  langid = {english},
  organization = {{GitLab}}
}

@article{carpi_elabftwopen_2017,
  title = {{{eLabFTW}}: {{An}} Open Source Laboratory Notebook for Research Labs},
  shorttitle = {{{eLabFTW}}},
  author = {Carpi, Nicolas and Minges, Alexander and Piel, Matthieu},
  date = {2017-04-14},
  journaltitle = {Journal of Open Source Software},
  volume = {2},
  number = {12},
  pages = {146},
  issn = {2475-9066},
  doi = {10.21105/joss.00146},
  url = {https://joss.theoj.org/papers/10.21105/joss.00146},
  abstract = {CARPi et al, (2017), eLabFTW: An open source laboratory notebook for research labs, Journal of Open Source Software, 2(12), 146, doi:10.21105/joss.00146},
  langid = {english},
  note = {Sources: \url{https://github.com/elabftw/}},
  file = {/home/daniel/Zotero/storage/6VQZE8JK/CARPi et al. - 2017 - eLabFTW An open source laboratory notebook for re.pdf}
}

@article{draxl_nomadlaboratory_2019,
  title = {The {{NOMAD}} Laboratory: From Data Sharing to Artificial Intelligence},
  shorttitle = {The {{NOMAD}} Laboratory},
  author = {Draxl, Claudia and Scheffler, Matthias},
  date = {2019-05},
  journaltitle = {Journal of Physics: Materials},
  shortjournal = {J. Phys. Mater.},
  volume = {2},
  number = {3},
  pages = {036001},
  publisher = {{IOP Publishing}},
  issn = {2515-7639},
  doi = {10.1088/2515-7639/ab13bb},
  url = {https://dx.doi.org/10.1088/2515-7639/ab13bb},
  abstract = {The Novel Materials Discovery (NOMAD) Laboratory is a user-driven platform for sharing and exploiting computational materials science data. It accounts for the various aspects of data being a crucial raw material and most relevant to accelerate materials research and engineering. NOMAD, with the NOMAD Repository, and its code-independent and normalized form, the NOMAD Archive, comprises the worldwide largest data collection of this field. Based on its findable accessible, interoperable, reusable data infrastructure, various services are offered, comprising advanced visualization, the NOMAD Encyclopedia, and artificial-intelligence tools. The latter are realized in the NOMAD Analytics Toolkit. Prerequisite for all this is the NOMAD metadata, a unique and thorough description of the data, that are produced by all important computer codes of the community. Uploaded data are tagged by a persistent identifier, and users can also request a digital object identifier to make data citable. Developments and advancements of parsers and metadata are organized jointly with users and code developers. In this work, we review the NOMAD concept and implementation, highlight its orthogonality to and synergistic interplay with other data collections, and provide an outlook regarding ongoing and future developments.},
  langid = {english},
  note = {Sources: \url{https://gitlab.mpcdf.mpg.de/nomad-lab/nomad-FAIR}},
  file = {/home/daniel/Zotero/storage/HG2HI9AI/Draxl and Scheffler - 2019 - The NOMAD laboratory from data sharing to artific.pdf}
}

@article{fitschen_caosdbresearch_2019,
  title = {{{CaosDB}} — {{Research Data Management}} for {{Complex}}, {{Changing}}, and {{Automated Research Workflows}}},
  author = {Fitschen, Timm and Schlemmer, Alexander and Hornung, Daniel and family=Wörden, given=Henrik, prefix=tom, useprefix=true and Parlitz, Ulrich and Luther, Stefan},
  date = {2019-06},
  journaltitle = {Data},
  volume = {4},
  number = {2},
  pages = {83},
  publisher = {{Multidisciplinary Digital Publishing Institute}},
  issn = {2306-5729},
  doi = {10.3390/data4020083},
  url = {https://www.mdpi.com/2306-5729/4/2/83},
  urldate = {2023-01-18},
  abstract = {We present CaosDB, a Research Data Management System (RDMS) designed to ensure seamless integration of inhomogeneous data sources and repositories of legacy data in a FAIR way. Its primary purpose is the management of data from biomedical sciences, both from simulations and experiments during the complete research data lifecycle. An RDMS for this domain faces particular challenges: research data arise in huge amounts, from a wide variety of sources, and traverse a highly branched path of further processing. To be accepted by its users, an RDMS must be built around workflows of the scientists and practices and thus support changes in workflow and data structure. Nevertheless, it should encourage and support the development and observation of standards and furthermore facilitate the automation of data acquisition and processing with specialized software. The storage data model of an RDMS must reflect these complexities with appropriate semantics and ontologies while offering simple methods for finding, retrieving, and understanding relevant data. We show how CaosDB responds to these challenges and give an overview of its data model, the CaosDB Server and its easy-to-learn CaosDB Query Language. We briefly discuss the status of the implementation, how we currently use CaosDB, and how we plan to use and extend it.},
  issue = {2},
  langid = {english},
  keywords = {ACID,database,FAIR,RDMS,research data management},
  file = {/home/daniel/Zotero/storage/EV3JUYQI/Fitschen et al. - 2019 - CaosDB—Research Data Management for Complex, Chang.pdf}
}

@article{fitzpatrick_issuesreproducible_2019,
  title = {Issues in {{Reproducible Simulation Research}}},
  author = {Fitzpatrick, B. G.},
  date = {2019-01-01},
  journaltitle = {Bulletin of Mathematical Biology},
  shortjournal = {Bull Math Biol},
  volume = {81},
  number = {1},
  pages = {1--6},
  issn = {1522-9602},
  doi = {10.1007/s11538-018-0496-1},
  url = {https://doi.org/10.1007/s11538-018-0496-1},
  abstract = {In recent years, serious concerns have arisen about reproducibility in science. Estimates of the cost of irreproducible preclinical studies range from 28 billion USD per year in the USA alone (Freedman et al. in PLoS Biol 13(6):e1002165, 2015) to over 200 billion USD per year worldwide (Chalmers and Glasziou in Lancet 374:86–89, 2009). The situation in the social sciences is not very different: Reproducibility in psychological research, for example, has been estimated to be below 50\% as well (Open Science Collaboration in Science 349:6251, 2015). Less well studied is the issue of reproducibility of simulation research. A few replication studies of agent-based models, however, suggest the problem for computational modeling may be more severe than for laboratory experiments (Willensky and Rand in JASSS 10(4):2, 2007; Donkin et al. in Environ Model Softw 92:142–151, 2017; Bajracharya and Duboz in: Proceedings of the symposium on theory of modeling and simulation—DEVS integrative M\&S symposium, pp 6–11, 2013). In this perspective, we discuss problems of reproducibility in agent-based simulations of life and social science problems, drawing on best practices research in computer science and in wet-lab experiment design and execution to suggest some ways to improve simulation research practice.},
  langid = {english},
  keywords = {Agent-based models,Computational lab notebook,Simulation reproducibility,Test-driven development,Validation,Version control},
  file = {/home/daniel/Zotero/storage/EMS6TTJY/Fitzpatrick - 2019 - Issues in Reproducible Simulation Research.pdf}
}

@article{griss_identifyingnovel_2015,
  title = {Identifying Novel Biomarkers through Data Mining—{{A}} Realistic Scenario?},
  author = {Griss, Johannes and Perez-Riverol, Yasset and Hermjakob, Henning and Vizcaíno, Juan Antonio},
  date = {2015},
  journaltitle = {PROTEOMICS – Clinical Applications},
  volume = {9},
  number = {3-4},
  pages = {437--443},
  issn = {1862-8354},
  doi = {10.1002/prca.201400107},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/prca.201400107},
  abstract = {In this article we discuss the requirements to use data mining of published proteomics datasets to assist proteomics-based biomarker discovery, the use of external data integration to solve the issue of inadequate small sample sizes and finally, we try to estimate the probability that new biomarkers will be identified through data mining alone.},
  langid = {english},
  keywords = {Bioinformatics,Biomarker,Data mining,Databases,Mass spectrometry},
  file = {/home/daniel/Zotero/storage/B6PSDVNP/Griss et al. - 2015 - Identifying novel biomarkers through data mining—A.pdf;/home/daniel/Zotero/storage/EZBULLY8/prca.html}
}

@inproceedings{hannay_howscientists_2009,
  title = {How Do Scientists Develop and Use Scientific Software?},
  booktitle = {2009 {{ICSE Workshop}} on {{Software Engineering}} for {{Computational Science}} and {{Engineering}}},
  author = {Hannay, Jo Erskine and MacLeod, Carolyn and Singer, Janice and Langtangen, Hans Petter and Pfahl, Dietmar and Wilson, Greg},
  date = {2009-05},
  pages = {1--8},
  doi = {10.1109/SECSE.2009.5069155},
  abstract = {New knowledge in science and engineering relies increasingly on results produced by scientific software. Therefore, knowing how scientists develop and use software in their research is critical to assessing the necessity for improving current development practices and to making decisions about the future allocation of resources. To that end, this paper presents the results of a survey conducted online in October-December 2008 which received almost 2000 responses. Our main conclusions are that (1) the knowledge required to develop and use scientific software is primarily acquired from peers and through self-study, rather than from formal education and training; (2) the number of scientists using supercomputers is small compared to the number using desktop or intermediate computers; (3) most scientists rely primarily on software with a large user base; (4) while many scientists believe that software testing is important, a smaller number believe they have sufficient understanding about testing concepts; and (5) that there is a tendency for scientists to rank standard software engineering concepts higher if they work in large software development projects and teams, but that there is no uniform trend of association between rank of importance of software engineering concepts and project/team size.},
  eventtitle = {2009 {{ICSE Workshop}} on {{Software Engineering}} for {{Computational Science}} and {{Engineering}}},
  keywords = {Automatic testing,Computer science education,Knowledge engineering,Peer to peer computing,Resource management,Software engineering,Software standards,Software testing,Standards development,Supercomputers},
  file = {/home/daniel/Zotero/storage/3LCFNPA2/5069155.html}
}

@online{harris_sparqlquery_2013,
  title = {{{SPARQL}} 1.1 {{Query Language}}},
  author = {Harris, Steve and Seaborne, Andy},
  date = {2013-03-21},
  url = {https://www.w3.org/TR/2013/REC-sparql11-query-20130321/},
  urldate = {2023-07-12},
  file = {/home/daniel/Zotero/storage/A6QPYXIU/REC-sparql11-query-20130321.html}
}

@online{hartig_rdfconcepts_2023,
  title = {{{RDF}} 1.2 {{Concepts}} and {{Abstract Syntax}}},
  author = {Hartig, Olaf and Champin, Pierre-Antoine and Kellogg, Gregg},
  date = {2023-06-29},
  url = {https://www.w3.org/TR/2023/WD-rdf12-concepts-20230629/},
  urldate = {2023-07-12},
  file = {/home/daniel/Zotero/storage/V3AQJRD2/rdf12-concepts.html}
}

@article{higgins_considerationsimplementing_2022,
  title = {Considerations for Implementing Electronic Laboratory Notebooks in an Academic Research Environment},
  author = {Higgins, Stuart G. and Nogiwa-Valdez, Akemi A. and Stevens, Molly M.},
  date = {2022-02},
  journaltitle = {Nature Protocols},
  shortjournal = {Nat Protoc},
  volume = {17},
  number = {2},
  pages = {179--189},
  publisher = {{Nature Publishing Group}},
  issn = {1750-2799},
  doi = {10.1038/s41596-021-00645-8},
  url = {https://www.nature.com/articles/s41596-021-00645-8},
  urldate = {2023-01-20},
  abstract = {As research becomes predominantly digitalized, scientists have the option of using electronic laboratory notebooks to record and access entries. These systems can more readily meet volume, complexity, accessibility and preservation requirements than paper notebooks. Although the technology can yield many benefits, these can be realized only by choosing a system that properly fulfills the requirements of a given context. This review explores the factors that should be considered when introducing electronic laboratory notebooks to an academically focused research group. We cite pertinent studies and discuss our own experience implementing a system within a multidisciplinary research environment. We also consider how the required financial and time investment is shared between individuals and institutions. Finally, we discuss how electronic laboratory notebooks fit into the broader context of research data management. This article is not a product review; it provides a framework for both the initial consideration of an electronic laboratory notebook and the evaluation of specific software packages.},
  issue = {2},
  langid = {english},
  keywords = {Electronic lab notebooks (ELNs),ELN,Software},
  file = {/home/daniel/Zotero/storage/EGNYHYAR/Higgins et al. - 2022 - Considerations for implementing electronic laborat.pdf}
}

@article{higman_threecamps_2019,
  title = {Three Camps, One Destination: The Intersections of Research Data Management, {{FAIR}} and {{Open}}},
  shorttitle = {Three Camps, One Destination},
  author = {Higman, Rosie and Bangert, Daniel and Jones, Sarah},
  date = {2019-05-22},
  journaltitle = {Insights},
  volume = {32},
  number = {1},
  pages = {18},
  publisher = {{UKSG in association with Ubiquity Press}},
  issn = {2048-7754},
  doi = {10.1629/uksg.468},
  url = {http://insights.uksg.org/articles/10.1629/uksg.468/},
  urldate = {2023-01-18},
  abstract = {Open data, FAIR (findable, accessible, interoperable and reusable) and research data management (RDM)~are three overlapping but distinct concepts, each emphasizing different aspects of handling and sharing research data. They have different strengths in terms of informing and influencing how research data is treated, and there is much scope for enrichment of data if they are applied collectively. This paper explores the boundaries of each concept and where they intersect and overlap. As well as providing greater definitional clarity, this will help researchers to manage and share their data, and those supporting researchers, such as librarians and data stewards, to understand how these concepts can best be used in an advocacy setting. FAIR and open both focus on data sharing, ensuring content is made available in ways that promote access and reuse. Data management by contrast is about the stewardship of data from the point of conception onwards. It makes no assumptions about access, but is essential if data are to be meaningful to others. The concepts of FAIR and open are more noble aspirations and are, this paper argues, a useful way to engage researchers and encourage good data practices from the outset.},
  issue = {1},
  langid = {english},
  keywords = {{open data, FAIR, open science},RDM,Research data management},
  file = {/home/daniel/Zotero/storage/DFCYHT7Y/Higman et al. - 2019 - Three camps, one destination the intersections of.pdf}
}

@online{hms_eln_2023,
  title = {Electronic {{Lab Notebooks}}},
  author = {{Harvard Medical School, Boston, MA}},
  date = {2023},
  url = {https://datamanagement.hms.harvard.edu/collect-analyze/electronic-lab-notebooks},
  urldate = {2023-09-27},
  abstract = {Using an Electronic Lab Notebook An Electronic Lab Notebook (ELN) is a software tool that in its most basic form replicates an interface much like a page in a paper lab notebook. In an ELN you can enter protocols, observations, notes, and other data using your computer or mobile device. ELNs offer several advantages over traditional paper notebooks, including:},
  langid = {english},
  file = {/home/daniel/Zotero/storage/MG38XSB2/electronic-lab-notebooks.html}
}

@article{hruby_centralizedresearch_2013,
  title = {A Centralized Research Data Repository Enhances Retrospective Outcomes Research Capacity: A Case Report},
  shorttitle = {A Centralized Research Data Repository Enhances Retrospective Outcomes Research Capacity},
  author = {Hruby, Gregory William and McKiernan, James and Bakken, Suzanne and Weng, Chunhua},
  date = {2013-05-01},
  journaltitle = {Journal of the American Medical Informatics Association},
  shortjournal = {Journal of the American Medical Informatics Association},
  volume = {20},
  number = {3},
  pages = {563--567},
  issn = {1067-5027},
  doi = {10.1136/amiajnl-2012-001302},
  url = {https://doi.org/10.1136/amiajnl-2012-001302},
  abstract = {This paper describes our considerations and methods for implementing an open-source centralized research data repository (CRDR) and reports its impact on retrospective outcomes research capacity in the urology department at Columbia University. We performed retrospective pretest and post-test analyses of user acceptance, workflow efficiency, and publication quantity and quality (measured by journal impact factor) before and after the implementation. The CRDR transformed the research workflow and enabled a new research model. During the pre- and post-test periods, the department's average annual retrospective study publication rate was 11.5 and 25.6, respectively; the average publication impact score was 1.7 and 3.1, respectively. The new model was adopted by 62.5\% (5/8) of the clinical scientists within the department. Additionally, four basic science researchers outside the department took advantage of the implemented model. The average proximate time required to complete a retrospective study decreased from 12 months before the implementation to \&lt;6 months after the implementation. Implementing a CRDR appears to be effective in enhancing the outcomes research capacity for one academic department.},
  keywords = {advantages,CAISIS,centralized research data repository,research data management,research data repository},
  file = {/home/daniel/Zotero/storage/DLUIF6CS/Hruby et al. - 2013 - A centralized research data repository enhances re.pdf;/home/daniel/Zotero/storage/REJ74UBK/741943.html}
}

@article{kanza_electroniclab_2017,
  title = {Electronic Lab Notebooks: Can They Replace Paper?},
  shorttitle = {Electronic Lab Notebooks},
  author = {Kanza, Samantha and Willoughby, Cerys and Gibbins, Nicholas and Whitby, Richard and Frey, Jeremy Graham and Erjavec, Jana and Zupančič, Klemen and Hren, Matjaž and Kovač, Katarina},
  date = {2017-05-24},
  journaltitle = {Journal of Cheminformatics},
  shortjournal = {Journal of Cheminformatics},
  volume = {9},
  number = {1},
  pages = {31},
  issn = {1758-2946},
  doi = {10.1186/s13321-017-0221-3},
  url = {https://doi.org/10.1186/s13321-017-0221-3},
  abstract = {Despite the increasingly digital nature of society there are some areas of research that remain firmly rooted in the past; in this case the laboratory notebook, the last remaining paper component of an experiment. Countless electronic laboratory notebooks (ELNs) have been created in an attempt to digitise record keeping processes in the lab, but none of them have become a ‘key player’ in the ELN market, due to the many adoption barriers that have been identified in previous research and further explored in the user studies presented here. The main issues identified are the cost of the current available ELNs, their ease of use (or lack of it) and their accessibility issues across different devices and operating systems. Evidence suggests that whilst scientists willingly make use of generic notebooking software, spreadsheets and other general office and scientific tools to aid their work, current ELNs are lacking in the required functionality to meet the needs of the researchers. In this paper we present our extensive research and user study results to propose an ELN built upon a pre-existing cloud notebook platform that makes use of accessible popular scientific software and semantic web technologies to help overcome the identified barriers to adoption.},
  keywords = {barriers,Cloud,Electronic lab notebooks (ELNs),ELN,Notebooking software,Scientific software,Semantic web},
  file = {/home/daniel/Zotero/storage/3KVMULTR/Kanza et al. - 2017 - Electronic lab notebooks can they replace paper.pdf;/home/daniel/Zotero/storage/PLPASU76/s13321-017-0221-3.html}
}

@article{kennan_researchdata_2015,
  title = {Research {{Data Management Practices}}: {{A Snapshot}} in {{Time}}},
  shorttitle = {Research {{Data Management Practices}}},
  author = {Kennan, Mary Anne and Markauskaite, Lina},
  date = {2015-06-30},
  journaltitle = {International Journal of Digital Curation},
  volume = {10},
  number = {2},
  pages = {69--95},
  issn = {1746-8256},
  doi = {10.2218/ijdc.v10i2.329},
  url = {http://ijdc.net/index.php/ijdc/article/view/10.2.69},
  urldate = {2023-01-19},
  abstract = {There is increasing pressure from funders, publishers, the public, universities and other research organisations for researchers to improve their data management and sharing practices. However, little is known about researchers’ data management and sharing practices and concerns. The research reported in this paper seeks to address this by providing insight into the research data management and sharing practices of academics at ten universities in New South Wales, Australia. Empirical data was taken from a survey to which 760 academics responded, with 634 completing at least one section. Results showed that at the time of the survey there were a wide variety of research data in use, including analogue data, and that the challenges researchers faced in managing their data included finding safe and secure storage, particularly after project completion, but also during projects when data are used (and thus stored) on a wide variety of less-than-optimal temporary devices. Data sharing was not widely practiced and only a relatively small proportion of researchers had a research data management plan. Since the survey was completed much has changed: capacities and communities are being built around data management and sharing and policies, and guidelines are being constructed. Data storage and curation services are now more freely available. It will be interesting to observe how the findings of future studies compare with those reported here.},
  issue = {2},
  langid = {english},
  keywords = {curation,data management,DCC,digital curation,digital preservation,IJDC,International Journal of Digital Curation,preservation,research data management},
  file = {/home/daniel/Zotero/storage/P7JL39NX/Kennan and Markauskaite - 2015 - Research Data Management Practices A Snapshot in .pdf}
}

@article{khattak_changemanagement_2013,
  title = {Change Management in Evolving Web Ontologies},
  author = {Khattak, Asad Masood and Latif, Khalid and Lee, Sungyoung},
  date = {2013-01-01},
  journaltitle = {Knowledge-Based Systems},
  shortjournal = {Knowledge-Based Systems},
  volume = {37},
  pages = {1--18},
  issn = {0950-7051},
  doi = {10.1016/j.knosys.2012.05.005},
  url = {https://www.sciencedirect.com/science/article/pii/S0950705112001323},
  urldate = {2023-01-18},
  abstract = {Knowledge constantly grows in scientific discourse and is revised over time by different stakeholders, either collaboratively or through institutionalized efforts. The body of knowledge gets structured and refined as the Communities of Practice concerned with a field of knowledge develop a deeper understanding of the issues. As a result, the knowledge model moves from a loosely clustered terminology to a semi-formal or even formal ontology. Change history management in such evolving knowledge models is an important and challenging task. Different techniques have been introduced in the research literature to solve the issue. A comprehensive solution must address various multi-faceted issues, such as ontology recovery, visualization of change effects, and keeping the evolving ontology in a consistent state. More so because the semantics of changes and evolution behavior of the ontology are hard to comprehend. This paper introduces a change history management framework for evolving ontologies; developed over the last couple of years. It is a comprehensive and methodological framework for managing issues related to change management in evolving ontologies, such as versioning, provenance, consistency, recovery, change representation and visualization. The Change history log is central to our framework and is supported by a semantically rich and formally sound change representation scheme known as change history ontology. Changes are captured and then stored in the log in conformance with the change history ontology. The log entries are later used to revert ontology to a previous consistent state, and to visualize the effects of change on ontology during its evolution. The framework is implemented to work as a plug-in for ontology repositories, such as Joseki and ontology editors, such as Protege. The change detection accuracy of the proposed system Change Tracer has been compared with that of Changes Tab, Version Log Generator in Protege; Change Detection, and Change Capturing of NeOn Toolkit. The proposed system has shown better accuracy against the existing systems. A comprehensive evaluation of the methodology was designed to validate the recovery operations. The accuracy of Roll-Back and Roll-Forward algorithms was conducted using different versions of SWETO Ontology, CIDOC CRM Ontology, OMV Ontology, and SWRC Ontology. Experimental results and comparison with other approaches shows that the change management process of the proposed system is accurate, consistent, and comprehensive in its coverage.},
  langid = {english},
  keywords = {Change History Ontology,Change Navigation,flexible ontology,Ontology Change Management,Ontology Evolution,Ontology Recovery},
  file = {/home/daniel/Zotero/storage/KKM4QIY5/Khattak et al. - 2013 - Change management in evolving web ontologies.pdf;/home/daniel/Zotero/storage/CF3BGGN2/S0950705112001323.html}
}

@article{king_introductiondataverse_2007,
  title = {An {{Introduction}} to the {{Dataverse Network}} as an {{Infrastructure}} for {{Data Sharing}}},
  author = {King, Gary},
  date = {2007-11-01},
  journaltitle = {Sociological Methods \& Research},
  volume = {36},
  number = {2},
  pages = {173--199},
  publisher = {{SAGE Publications Inc}},
  issn = {0049-1241},
  doi = {10.1177/0049124107306660},
  url = {https://doi.org/10.1177/0049124107306660},
  abstract = {The author introduces a set of integrated developments in Web application software, networking, data citation standards, and statistical methods designed to increase scholarly recognition for data contributions; to put some of the universe of data and data-sharing practices on firmer ground; and to facilitate the public distribution of persistent, authorized, and verifiable data, with powerful and easy-to-use technology, even when the data are confidential or proprietary. The goal is to solve some of the political and sociological problems of data sharing via technological means, with the result intended to benefit both the scientific community and the sometimes apparently contradictory goals of individual researchers.},
  langid = {english},
  file = {/home/daniel/Zotero/storage/6C6RGFQV/King - 2007 - An Introduction to the Dataverse Network as an Inf.pdf}
}

@article{manghani_qualityassurance_2011,
  title = {Quality Assurance: {{Importance}} of Systems and Standard Operating Procedures},
  shorttitle = {Quality Assurance},
  author = {Manghani, Kishu},
  date = {2011},
  journaltitle = {Perspectives in Clinical Research},
  shortjournal = {Perspect Clin Res},
  volume = {2},
  number = {1},
  eprint = {21584180},
  eprinttype = {pmid},
  pages = {34--37},
  issn = {2229-3485},
  doi = {10.4103/2229-3485.76288},
  url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3088954/},
  urldate = {2023-07-11},
  abstract = {It is mandatory for sponsors of clinical trials and contract research organizations alike to establish, manage and monitor their quality control and quality assurance systems and their integral standard operating procedures and other quality documents to provide high-quality products and services to fully satisfy customer needs and expectations. Quality control and quality assurance systems together constitute the key quality systems. Quality control and quality assurance are parts of quality management. Quality control is focused on fulfilling quality requirements, whereas quality assurance is focused on providing confidence that quality requirements are fulfilled. The quality systems must be commensurate with the Company business objectives and business model. Top management commitment and its active involvement are critical in order to ensure at all times the adequacy, suitability, effectiveness and efficiency of the quality systems. Effective and efficient quality systems can promote timely registration of drugs by eliminating waste and the need for rework with overall financial and social benefits to the Company.},
  pmcid = {PMC3088954},
  file = {/home/daniel/Zotero/storage/EVX5W626/Manghani - 2011 - Quality assurance Importance of systems and stand.pdf}
}

@article{nicholson_analysismetadata_2020,
  title = {An Analysis of Metadata Reporting in Freshwater Environmental {{DNA}} Research Calls for the Development of Best Practice Guidelines},
  author = {Nicholson, Andrew and McIsaac, Daniel and MacDonald, Caitlin and Gec, Peter and Mason, B. Eric and Rein, William and Wrobel, Jordan and family=Boer, given=Mats, prefix=de, useprefix=true and Milián-García, Yoamel and Hanner, Robert H.},
  date = {2020},
  journaltitle = {Environmental DNA},
  volume = {2},
  number = {3},
  pages = {343--349},
  issn = {2637-4943},
  doi = {10.1002/edn3.81},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/edn3.81},
  abstract = {As environmental DNA (eDNA) becomes more widely used in research, it becomes increasingly important to have a standard set of reporting guidelines for metadata. The unique properties of eDNA combined with the physical characteristics of the surrounding environment produce highly varied sampling conditions which can influence how an organism is detected. There are also various ways of quantifying and identifying species using eDNA, from sampling and filtering methods to extraction and genetic analysis. It is important to report sufficient metadata to account for this variability and allow for replication of the study. We conducted a systematic review of 160 eDNA studies to determine which data are reported and to assess whether these studies can be replicated. Focusing solely on freshwater studies, we developed a rubric to evaluate each study on 53 criteria based on previous analyses of eDNA research. We found a trend in the data suggesting better reporting at a broad scale, and decreased reporting as categories become more specific. Many of the metrics found to be insufficiently reported are essential to replicability. Our goal is to identify gaps in metadata reporting and develop a framework for developing standard reporting guidelines for eDNA studies.},
  langid = {english},
  keywords = {environmental DNA,freshwater,metadata,replicability,standardization},
  file = {/home/daniel/Zotero/storage/S5RICQBI/Nicholson et al. - 2020 - An analysis of metadata reporting in freshwater en.pdf;/home/daniel/Zotero/storage/A5F2D223/edn3.html}
}

@article{nourani_clinicaltrial_2019,
  title = {Clinical {{Trial Data Management Software}}: {{A Review}} of the {{Technical Features}}},
  shorttitle = {Clinical {{Trial Data Management Software}}},
  author = {Nourani, Aynaz and Ayatollahi, Haleh and Dodaran, Masoud S.},
  date = {2019-09-01},
  journaltitle = {Reviews on Recent Clinical Trials},
  shortjournal = {Reviews on Recent Clinical Trials},
  volume = {14},
  number = {3},
  pages = {160--172},
  doi = {10.2174/1574887114666190207151500},
  abstract = {Background: Data management is an important, complex and multidimensional process in clinical trials. The execution of this process is very difficult and expensive without the use of information technology. A clinical data management system is software that is vastly used for managing the data generated in clinical trials. The objective of this study was to review the technical features of clinical trial data management systems. Methods: Related articles were identified by searching databases, such as Web of Science, Scopus, Science Direct, ProQuest, Ovid and PubMed. All of the research papers related to clinical data management systems which were published between 2007 and 2017 (n=19) were included in the study. Results: Most of the clinical data management systems were web-based systems developed based on the needs of a specific clinical trial in the shortest possible time. The SQL Server and MySQL databases were used in the development of the systems. These systems did not fully support the process of clinical data management. In addition, most of the systems lacked flexibility and extensibility for system development. Conclusion: It seems that most of the systems used in the research centers were weak in terms of supporting the process of data management and managing clinical trial's workflow. Therefore, more attention should be paid to design a more complete, usable, and high quality data management system for clinical trials. More studies are suggested to identify the features of the successful systems used in clinical trials.},
  keywords = {Case Report Forms (CRFs),clinical data management,clinical trial,data management,dms use sql,information technology,medical coding,systems software},
  file = {/home/daniel/Zotero/storage/2BQR95WN/RRCT-2.pdf}
}

@article{patiny_c6h6nmr_2018,
  title = {The {{C6H6 NMR}} Repository: {{An}} Integral Solution to Control the Flow of Your Data from the Magnet to the Public},
  shorttitle = {The {{C6H6 NMR}} Repository},
  author = {Patiny, Luc and Zasso, Michaël and Kostro, Daniel and Bernal, Andrés and Castillo, Andrés M. and Bolaños, Alejandro and Asencio, Miguel A. and Pellet, Norman and Todd, Matthew and Schloerer, Nils and Kuhn, Stefan and Holmes, Elaine and Javor, Sacha and Wist, Julien},
  date = {2018},
  journaltitle = {Magnetic Resonance in Chemistry},
  volume = {56},
  number = {6},
  pages = {520--528},
  issn = {1097-458X},
  doi = {10.1002/mrc.4669},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrc.4669},
  abstract = {NMR is a mature technique that is well established and adopted in a wide range of research facilities from laboratories to hospitals. This accounts for large amounts of valuable experimental data that may be readily exported into a standard and open format. Yet the publication of these data faces an important issue: Raw data are not made available; instead, the information is slimed down into a string of characters (the list of peaks). Although historical limitations of technology explain this practice, it is not acceptable in the era of Internet. The idea of modernizing the strategy for sharing NMR data is not new, and some repositories exist, but sharing raw data is still not an established practice. Here, we present a powerful toolbox built on recent technologies that runs inside the browser and provides a means to store, share, analyse, and interact with original NMR data. Stored spectra can be streamlined into the publication pipeline, to improve the revision process for instance. The set of tools is still basic but is intended to be extended. The project is open source under the Massachusetts Institute of Technology (MIT) licence.},
  langid = {english},
  keywords = {database,NMR spectroscopy,online repository,open science,processing suit},
  file = {/home/daniel/Zotero/storage/QPSRMXSX/Patiny et al. - 2018 - The C6H6 NMR repository An integral solution to c.pdf;/home/daniel/Zotero/storage/JRS3HGWT/mrc.html}
}

@article{poldrack_computationalinformatic_2019,
  title = {Computational and {{Informatic Advances}} for {{Reproducible Data Analysis}} in {{Neuroimaging}}},
  author = {Poldrack, Russell A. and Gorgolewski, Krzysztof J. and Varoquaux, Gaël},
  date = {2019},
  journaltitle = {Annual Review of Biomedical Data Science},
  volume = {2},
  number = {1},
  pages = {119--138},
  doi = {10.1146/annurev-biodatasci-072018-021237},
  url = {https://doi.org/10.1146/annurev-biodatasci-072018-021237},
  abstract = {The reproducibility of scientific research has become a point of critical concern. We argue that openness and transparency are critical for reproducibility, and we outline an ecosystem for open and transparent science that has emerged within the human neuroimaging community. We discuss the range of open data-sharing resources that have been developed for neuroimaging data, as well as the role of data standards (particularly the brain imaging data structure) in enabling the automated sharing, processing, and reuse of large neuroimaging data sets. We outline how the open source Python language has provided the basis for a data science platform that enables reproducible data analysis and visualization. We also discuss how new advances in software engineering, such as containerization, provide the basis for greater reproducibility in data analysis. The emergence of this new ecosystem provides an example for many areas of science that are currently struggling with reproducibility.},
  keywords = {containerization,machine learning,open science,Python,software engineering}
}

@incollection{radicchi_citationnetworks_2012,
  title = {Citation {{Networks}}},
  booktitle = {Models of {{Science Dynamics}}: {{Encounters Between Complexity Theory}} and {{Information Sciences}}},
  author = {Radicchi, Filippo and Fortunato, Santo and Vespignani, Alessandro},
  editor = {Scharnhorst, Andrea and Börner, Katy and family=Besselaar, given=Peter, prefix=van den, useprefix=true},
  date = {2012},
  series = {Understanding {{Complex Systems}}},
  pages = {233--257},
  publisher = {{Springer}},
  location = {{Berlin, Heidelberg}},
  doi = {10.1007/978-3-642-23068-4_7},
  url = {https://doi.org/10.1007/978-3-642-23068-4_7},
  abstract = {Bibliographic databases contain a huge amount of information on the dissemination of scientific knowledge and the relationships between papers, authors, and scientific work. Large-scale citation networks can be generated from these databases in order to provide a systems-level perspective on the processes at the root of the spreading of ideas, theories, and results in science. Citation networks are therefore one of the main proxies for our understanding of knowledge dynamics as well as invaluable systems for the quantitative analysis of the impact of specific scientific contributions, the emergence of technical and scientific areas, and the ranking of journals, institutions, and scientists. This chapter reviews recent developments made in the study of citation networks, ranging from empirical analyses of real systems and mathematical models of them, to the study of dynamic processes taking place in them and their potential applications. Furthermore, studying citation datasets with the tools of network theory opens new avenues towards a quantitative understanding of the dynamics of popularity with respect to papers, journals, and scientists, possibly leading to novel measures of impact and ranking.},
  isbn = {978-3-642-23068-4},
  langid = {english},
  keywords = {Bibliographic Database,Citation Count,Citation Network,Community Detection,Preferential Attachment}
}

@article{raptis_datamanagement_2019,
  title = {Data {{Management}} in {{Industry}} 4.0: {{State}} of the {{Art}} and {{Open Challenges}}},
  shorttitle = {Data {{Management}} in {{Industry}} 4.0},
  author = {Raptis, Theofanis P. and Passarella, Andrea and Conti, Marco},
  date = {2019-07-16},
  journaltitle = {IEEE Access},
  shortjournal = {IEEE Access},
  volume = {7},
  pages = {97052--97093},
  issn = {2169-3536},
  doi = {10.1109/ACCESS.2019.2929296},
  abstract = {Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This paper surveys the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future. As a first step, we extract important data properties (volume, variety, traffic, and criticality) and identify the corresponding data enabling technologies of diverse fundamental industrial use cases, based on practical applications. Second, we provide a detailed outline of recent industrial architectural designs with respect to their data management philosophy (data presence, data coordination, and data computation) and the extent of their distributiveness. Then, we conduct a holistic survey of the recent literature from which we derive a taxonomy of the latest advances in industrial data enabling technologies and data centric services, spanning all the way from the field level deep in the physical deployments, up to the cloud and applications level. Finally, motivated by the rich conclusions of this critical analysis, we identify interesting open challenges for future research. The concepts presented in this paper thematically cover the largest part of the industrial automation pyramid layers. Our approach is multidisciplinary, as the selected publications were drawn from two fields; the communications, networking and computation field, and the industrial, manufacturing, and automation field. This paper can help the readers to deeply understand how data management is currently applied in networked industrial environments, and select interesting open research opportunities to pursue.},
  eventtitle = {{{IEEE Access}}},
  keywords = {Automation,data management,Data management,industrial networks,industry,Industry 4.0,manufacturing,Manufacturing,Production,Robot sensing systems,Service robots},
  file = {/home/daniel/Zotero/storage/9S9SNF5V/Raptis et al. - 2019 - Data Management in Industry 4.0 State of the Art .pdf;/home/daniel/Zotero/storage/HL8HAFZE/Raptis et al. - 2019 - Data Management in Industry 4.0 State of the Art .pdf;/home/daniel/Zotero/storage/P7K9NKM8/8764545.html}
}

@article{schneider_ontologiesdata_2020,
  title = {Ontologies and {{Data Management}}: {{A Brief Survey}}},
  shorttitle = {Ontologies and {{Data Management}}},
  author = {Schneider, Thomas and Šimkus, Mantas},
  date = {2020-08-13},
  journaltitle = {KI - Künstliche Intelligenz},
  shortjournal = {KI - Künstliche Intelligenz},
  volume = {34},
  doi = {10.1007/s13218-020-00686-3},
  abstract = {Information systems have to deal with an increasing amount of data that is heterogeneous, unstructured, or incomplete. In order to align and complete data, systems may rely on taxonomies and background knowledge that are provided in the form of an ontology. This survey gives an overview of research work on the use of ontologies for accessing incomplete and/or heterogeneous data.},
  keywords = {flexible ontology},
  file = {/home/daniel/Zotero/storage/PJH53YPF/Schneider and Šimkus - 2020 - Ontologies and Data Management A Brief Survey.pdf}
}

@article{sefton_rocratemetadata_2023,
  title = {{{RO-Crate Metadata Specification}} 1.1.3},
  author = {Sefton, Peter and Ó Carragáin, Eoghan and Soiland-Reyes, Stian and Corcho, Oscar and Garijo, Daniel and Palma, Raul and Coppens, Frederik and Goble, Carole and Fernández, José M. and Chard, Kyle and Gomez-Perez, Jose Manuel and Crusoe, Michael R. and Eguinoa, Ignacio and Juty, Nick and Holmes, Kristi and Clark, Jason A. and Capella-Gutierrez, Salvador and Gray, Alasdair J. G. and Owen, Stuart and Williams, Alan R. and Tartari, Giacomo and Bacall, Finn and Thelen, Thomas and Ménager, Hervé and Rodríguez-Navas, Laura and Walk, Paul and {whitehead}, brandon and Wilkinson, Mark and Groth, Paul and Bremer, Erich and Castro, Leyla Jael and Sebby, Karl and Kanitz, Alexander and Trisovic, Ana and Kennedy, Gavin and Graves, Mark and Koehorst, Jasper and Leo, Simone and Portier, Marc and Brack, Paul and Ojsteršek, Milan and Droesbeke, Bert and Niu, Chenxu and Tanabe, Kosuke and Miksa, Tomasz and La Rosa, Marco and Decruw, Cedric and Czerniak, Andreas and Jay, Jeremy and Serra, Sergio and Siebes, Ronald and family=Witt, given=Shaun, prefix=de, useprefix=true and El Damaty, Shady and Lowe, Douglas and Li, Xuanqi and Gundersen, Sveinung and Radifar, Muhammad},
  date = {2023-04-26},
  publisher = {{Zenodo}},
  doi = {10.5281/zenodo.7867028},
  url = {https://zenodo.org/record/7867028},
  urldate = {2023-07-12},
  abstract = {Web-version: https://w3id.org/ro/crate/1.1 This document specifies a method, known as RO-Crate (Research Object Crate), of aggregating and describing research data with associated metadata. RO-Crates can aggregate and describe any resource including files, URI-addressable resources, or use other addressing schemes to locate digital or physical data. RO-Crates can describe data in aggregate and at the individual resource level, with metadata to aid in discovery, re-use and long term management of data. Metadata includes the ability to describe the context of data and the entities involved in its production, use and reuse. For example: who created it, using which equipment, software and workflows, under what licenses can it be re-used, where was it collected, and/or where is it about. RO-Crate uses JSON-LD to to express this metadata using linked data, describing data resources as well as contextual entities such as people, organizations, software and equipment as a series of linked JSON-LD objects - using common published vocabularies, chiefly schema.org. The core of RO-Crate is a JSON-LD file, the RO-Crate Metadata File, named ro-crate-metadata.json. This file contains structured metadata about the dataset as a whole (the Root Data Entity) and, optionally, about some or all of its files. This provides a simple way to, for example, assert the authors (e.g. people, organizations) of the RO-Crate or one its files, or to capture more complex provenance for files, such as how they were created using software and equipment. While providing the formal specification for RO-Crate, this document also aims to be a practical guide for software authors to create tools for generating and consuming research data packages, with explanation by examples.},
  langid = {english},
  keywords = {data packaging,JSON-LD,linked data,metadata,research object,schema.org},
  file = {/home/daniel/Zotero/storage/PULLTQCA/Sefton et al. - 2023 - RO-Crate Metadata Specification 1.1.3.pdf}
}

@article{segal_whensoftware_2005,
  title = {When {{Software Engineers Met Research Scientists}}: {{A Case Study}}},
  shorttitle = {When {{Software Engineers Met Research Scientists}}},
  author = {Segal, Judith},
  date = {2005-10-01},
  journaltitle = {Empirical Software Engineering},
  shortjournal = {Empir Software Eng},
  volume = {10},
  number = {4},
  pages = {517--536},
  issn = {1573-7616},
  doi = {10.1007/s10664-005-3865-y},
  url = {https://doi.org/10.1007/s10664-005-3865-y},
  abstract = {This paper describes a case study of software engineers developing a library of software components for a group of research scientists, using a traditional, staged, document-led methodology. The case study reveals two problems with the use of the methodology. The first is that it demands an upfront articulation of requirements, whereas the scientists had experience, and hence expectations, of emergent requirements; the second is that the project documentation does not suffice to construct a shared understanding. Reflecting on our case study, we discuss whether combining agile elements with a traditional methodology might have alleviated these problems. We then argue that the rich picture painted by the case study, and the reflections on methodology that it inspires, has a relevance that reaches beyond the original context of the study.},
  langid = {english},
  keywords = {agile methodologies,Case study,scientific software,software engineers,tailoring methodologies}
}

@article{silvello_semanticrepresentation_2017,
  title = {Semantic Representation and Enrichment of Information Retrieval Experimental Data},
  author = {Silvello, Gianmaria and Bordea, Georgeta and Ferro, Nicola and Buitelaar, Paul and Bogers, Toine},
  date = {2017-06-01},
  journaltitle = {International Journal on Digital Libraries},
  shortjournal = {Int J Digit Libr},
  volume = {18},
  number = {2},
  pages = {145--172},
  issn = {1432-1300},
  doi = {10.1007/s00799-016-0172-8},
  url = {https://doi.org/10.1007/s00799-016-0172-8},
  abstract = {Experimental evaluation carried out in international large-scale campaigns is a fundamental pillar of the scientific and technological advancement of information retrieval (IR) systems. Such evaluation activities produce a large quantity of scientific and experimental data, which are the foundation for all the subsequent scientific production and development of new systems. In this work, we discuss how to semantically annotate and interlink this data, with the goal of enhancing their interpretation, sharing, and reuse. We discuss the underlying evaluation workflow and propose a resource description framework model for those workflow parts. We use expertise retrieval as a case study to demonstrate the benefits of our semantic representation approach. We employ this model as a means for exposing experimental data as linked open data (LOD) on the Web and as a basis for enriching and automatically connecting this data with expertise topics and expert profiles. In this context, a topic-centric approach for expert search is proposed, addressing the extraction of expertise topics, their semantic grounding with the LOD cloud, and their connection to IR experimental data. Several methods for expert profiling and expert finding are analysed and evaluated. Our results show that it is possible to construct expert profiles starting from automatically extracted expertise topics and that topic-centric approaches outperform state-of-the-art language modelling approaches for expert finding.},
  langid = {english},
  keywords = {Experimental data,Expert search,Expertise profiling,Information retrieval evaluation,Resource description framework,Semantic enrichment},
  file = {/home/daniel/Zotero/storage/SEJ6MBL5/Silvello et al. - 2017 - Semantic representation and enrichment of informat.pdf}
}

@article{smith_dspaceopen_2003,
  title = {{{DSpace}}: {{An Open Source Dynamic Digital Repository}}},
  shorttitle = {{{DSpace}}},
  author = {Smith, MacKenzie and Barton, Mary and Bass, Mick and Branschofsky, Margret and McClellan, Greg and Stuve, Dave and Tansley, Robert and Walker, Julie Harford},
  date = {2003-01},
  publisher = {{Corporation for National Research Initiatives}},
  issn = {1082-9873},
  doi = {10.1045/january2003-smith},
  url = {https://dspace.mit.edu/handle/1721.1/29465},
  urldate = {2023-07-12},
  abstract = {For the past two years the Massachusetts Institute of Technology (MIT) Libraries and Hewlett-Packard Labs have been collaborating on the development of an open source system called DSpaceâ¢ that functions as a repository for the digital research and educational material produced by members of a research university or organization. Running such an institutionally-based, multidisciplinary repository is increasingly seen as a natural role for the libraries and archives of research and teaching organizations. As their constituents produce increasing amounts of original material in digital formats—much of which is never published by traditional means—the repository becomes vital to protect the significant assets of the institution and its faculty. The first part of this article describes the DSpace system including its functionality and design, and its approach to various problems in digital library and archives design. The second part discusses the implementation of DSpace at MIT, plans for federating the system, and issues of sustainability.},
  langid = {american},
  annotation = {Accepted: 2005-10-17T13:54:54Z}
}

@article{soiland-reyes_packagingresearch_2022,
  title = {Packaging Research Artefacts with {{RO-Crate}}},
  author = {Soiland-Reyes, Stian and Sefton, Peter and Crosas, Mercè and Castro, Leyla Jael and Coppens, Frederik and Fernández, José M. and Garijo, Daniel and Grüning, Björn and La Rosa, Marco and Leo, Simone and Ó Carragáin, Eoghan and Portier, Marc and Trisovic, Ana and RO-Crate Community and Groth, Paul and Goble, Carole},
  date = {2022-01-01},
  journaltitle = {Data Science},
  volume = {5},
  number = {2},
  pages = {97--138},
  publisher = {{IOS Press}},
  issn = {2451-8484},
  doi = {10.3233/DS-210053},
  url = {https://content.iospress.com/articles/data-science/ds210053},
  urldate = {2023-07-12},
  abstract = {An increasing number of researchers support reproducibility by including pointers to and descriptions of datasets, software and methods in their publications. However, scientific articles may be ambiguous, incomplete and difficult to process by autom},
  langid = {english},
  file = {/home/daniel/Zotero/storage/CBE2VSWC/Soiland-Reyes et al. - 2022 - Packaging research artefacts with RO-Crate.pdf}
}

@article{spreckelsen_guidelinesstandardized_2020,
  title = {Guidelines for a {{Standardized Filesystem Layout}} for {{Scientific Data}}},
  author = {Spreckelsen, Florian and Rüchardt, Baltasar and Lebert, Jan and Luther, Stefan and Parlitz, Ulrich and Schlemmer, Alexander},
  date = {2020-06},
  journaltitle = {Data},
  volume = {5},
  number = {2},
  pages = {43},
  publisher = {{Multidisciplinary Digital Publishing Institute}},
  issn = {2306-5729},
  doi = {10.3390/data5020043},
  url = {https://www.mdpi.com/2306-5729/5/2/43},
  urldate = {2023-01-18},
  abstract = {Storing scientific data on the filesystem in a meaningful and transparent way is no trivial task. In particular, when the data have to be accessed after their originator has left the lab, the importance of a standardized filesystem layout cannot be underestimated. It is desirable to have a structure that allows for the unique categorization of all kinds of data from experimental results to publications. They have to be accessible to a broad variety of workflows, e.g., via graphical user interface as well as via command line, in order to find widespread acceptance. Furthermore, the inclusion of already existing data has to be as simple as possible. We propose a three-level layout to organize and store scientific data that incorporates the full chain of scientific data management from data acquisition to analysis to publications. Metadata are saved in a standardized way and connect original data to analyses and publications as well as to their originators. A simple software tool to check a file structure for compliance with the proposed structure is presented.},
  issue = {2},
  langid = {english},
  keywords = {FAIR,file structure,filesystem layout,research data management},
  file = {/home/daniel/Zotero/storage/IE5EAETF/Spreckelsen et al. - 2020 - Guidelines for a Standardized Filesystem Layout fo.pdf}
}

@incollection{strozzi_scalableworkflows_2019,
  title = {Scalable {{Workflows}} and {{Reproducible Data Analysis}} for {{Genomics}}},
  booktitle = {Evolutionary {{Genomics}}: {{Statistical}} and {{Computational Methods}}},
  author = {Strozzi, Francesco and Janssen, Roel and Wurmus, Ricardo and Crusoe, Michael R. and Githinji, George and Di Tommaso, Paolo and Belhachemi, Dominique and Möller, Steffen and Smant, Geert and family=Ligt, given=Joep, prefix=de, useprefix=true and Prins, Pjotr},
  editor = {Anisimova, Maria},
  date = {2019},
  series = {Methods in {{Molecular Biology}}},
  pages = {723--745},
  publisher = {{Springer}},
  location = {{New York, NY}},
  doi = {10.1007/978-1-4939-9074-0_24},
  url = {https://doi.org/10.1007/978-1-4939-9074-0_24},
  abstract = {Biological, clinical, and pharmacological research now often involves analyses of genomes, transcriptomes, proteomes, and interactomes, within and between individuals and across species. Due to large volumes, the analysis and integration of data generated by such high-throughput technologies have become computationally intensive, and analysis can no longer happen on a typical desktop computer.},
  isbn = {978-1-4939-9074-0},
  langid = {english},
  keywords = {Big data,Bioconda,Bioinformatics,Cloud computing,Cluster computing,Common Workflow Language,CWL,Debian Linux,Evolutionary biology,GNU Guix,Guix Workflow Language,MPI,MrBayes,Nextflow,Parallelization,Snakemake,Virtual machine},
  file = {/home/daniel/Zotero/storage/2QFSBURA/Strozzi et al. - 2019 - Scalable Workflows and Reproducible Data Analysis .pdf}
}

@online{tomworden_linkaheadcrawler_2023,
  title = {{{LinkAhead}} / {{LinkAhead Crawler Cfoods}} / {{ELabFTW Cfood}} · {{GitLab}}},
  date = {2023-10-05},
  url = {https://gitlab.com/linkahead/crawler-extensions/elabftw-cfood},
  urldate = {2023-10-05},
  abstract = {This is a mirror of IndiScale's ELabFTW Cfood repo},
  langid = {english},
  organization = {{GitLab}},
  file = {/home/daniel/Zotero/storage/UPAVWMUY/elabftw-cfood.html}
}

@article{tremouilhac_chemotioneln_2017,
  title = {Chemotion {{ELN}}: An {{Open Source}} Electronic Lab Notebook for Chemists in Academia},
  shorttitle = {Chemotion {{ELN}}},
  author = {Tremouilhac, Pierre and Nguyen, An and Huang, Yu-Chieh and Kotov, Serhii and Lütjohann, Dominic Sebastian and Hübsch, Florian and Jung, Nicole and Bräse, Stefan},
  date = {2017-09-25},
  journaltitle = {Journal of Cheminformatics},
  shortjournal = {Journal of Cheminformatics},
  volume = {9},
  number = {1},
  pages = {54},
  issn = {1758-2946},
  doi = {10.1186/s13321-017-0240-0},
  url = {https://doi.org/10.1186/s13321-017-0240-0},
  abstract = {The development of an electronic lab notebook (ELN) for researchers working in the field of chemical sciences is presented. The web based application is available as an Open Source software that offers modern solutions for chemical researchers. The Chemotion ELN is equipped with the basic functionalities necessary for the acquisition and processing of chemical data, in particular the work with molecular structures and calculations based on molecular properties. The ELN supports planning, description, storage, and management for the routine work of organic chemists. It also provides tools for communicating and sharing the recorded research data among colleagues. Meeting the requirements of a state of the art research infrastructure, the ELN allows the search for molecules and reactions not only within the user’s data but also in conventional external sources as provided by SciFinder and PubChem. The presented development makes allowance for the growing dependency of scientific activity on the availability of digital information by providing Open Source instruments to record and reuse research data. The current version of the ELN has been using for over half of a year in our chemistry research group, serves as a common infrastructure for chemistry research and enables chemistry researchers to build their own databases of digital information as a prerequisite for the detailed, systematic investigation and evaluation of chemical reactions and mechanisms.},
  keywords = {Compound management,Digitalization,Electronic lab notebook,Open Source,Ruby on Rails},
  file = {/home/daniel/Zotero/storage/5W7DKEDC/Tremouilhac et al. - 2017 - Chemotion ELN an Open Source electronic lab noteb.pdf;/home/daniel/Zotero/storage/FUAJVSSP/s13321-017-0240-0.html}
}

@online{tutorial_crawler_2023,
  title = {Tutorial: {{Parameter}} File — {{LinkAhead Crawler}} 0.7.0 Documentation},
  date = {2023},
  url = {https://docs.indiscale.com/caosdb-crawler/tutorials/parameterfile.html#getting-started-with-the-cfood},
  urldate = {2023-07-12}
}

@article{tuyl_investigationnonacademic_2018,
  title = {Investigation of {{Non-Academic Data Management Practices}} to {{Inform Academic Research Data Management}}},
  author = {Tuyl, Steven Van and Whitmire, Amanda},
  date = {2018-10-31},
  journaltitle = {Research Ideas and Outcomes},
  volume = {4},
  pages = {e30829},
  publisher = {{Pensoft Publishers}},
  issn = {2367-7163},
  doi = {10.3897/rio.4.e30829},
  url = {https://riojournal.com/article/30829/},
  urldate = {2023-01-19},
  abstract = {In recent years, the academic research data management (RDM) community has worked closely with funding agencies, university administrators, and researchers to develop best practices for RDM. The RDM community, however, has spent relatively little time exploring best practices used in non-academic environments (industry, government, etc.) for management, preservation, and sharing of data. In this poster, we present the results of a project wherein we approached a number of non-academic corporations and institutions to discuss how data is managed in those organizations and discern what the academic RDM community could learn from non-academic RDM practices. We conducted interviews with 10-20 companies including tech companies, government agencies, and consumer retail corporations. We present the results in the form of user stories, common themes from interviews, and summaries of areas where the RDM community might benefit from further understanding of non-academic data management practices.},
  langid = {english},
  keywords = {data management,industry},
  file = {/home/daniel/Zotero/storage/84287A9X/Tuyl and Whitmire - 2018 - Investigation of Non-Academic Data Management Prac.pdf}
}

@article{vrandecic_wikidatafree_2014,
  title = {Wikidata: A Free Collaborative Knowledgebase},
  shorttitle = {Wikidata},
  author = {Vrandečić, Denny and Krötzsch, Markus},
  date = {2014-09-23},
  journaltitle = {Communications of the ACM},
  shortjournal = {Commun. ACM},
  volume = {57},
  number = {10},
  pages = {78--85},
  issn = {0001-0782, 1557-7317},
  doi = {10.1145/2629489},
  url = {https://dl.acm.org/doi/10.1145/2629489},
  abstract = {This collaboratively edited knowledgebase provides a common source of data for Wikipedia, and everyone else.},
  langid = {english},
  file = {/home/daniel/Zotero/storage/EZWHVXF3/Vrandečić and Krötzsch - 2014 - Wikidata a free collaborative knowledgebase.pdf}
}

@article{wilkinson_fairguiding_2016,
  title = {The {{FAIR Guiding Principles}} for Scientific Data Management and Stewardship},
  author = {Wilkinson, Mark D. and Dumontier, Michel and family=Aalbersberg, given=IJsbrand Jan, given-i={{IJ}}J and Appleton, Gabrielle and Axton, Myles and Baak, Arie and Blomberg, Niklas and Boiten, Jan-Willem and family=Silva Santos, given=Luiz Bonino, prefix=da, useprefix=true and Bourne, Philip E. and Bouwman, Jildau and Brookes, Anthony J. and Clark, Tim and Crosas, Mercè and Dillo, Ingrid and Dumon, Olivier and Edmunds, Scott and Evelo, Chris T. and Finkers, Richard and Gonzalez-Beltran, Alejandra and Gray, Alasdair J. G. and Groth, Paul and Goble, Carole and Grethe, Jeffrey S. and Heringa, Jaap and family=Hoen, given=Peter A. C., prefix=’t, useprefix=true and Hooft, Rob and Kuhn, Tobias and Kok, Ruben and Kok, Joost and Lusher, Scott J. and Martone, Maryann E. and Mons, Albert and Packer, Abel L. and Persson, Bengt and Rocca-Serra, Philippe and Roos, Marco and family=Schaik, given=Rene, prefix=van, useprefix=true and Sansone, Susanna-Assunta and Schultes, Erik and Sengstag, Thierry and Slater, Ted and Strawn, George and Swertz, Morris A. and Thompson, Mark and family=Lei, given=Johan, prefix=van der, useprefix=true and family=Mulligen, given=Erik, prefix=van, useprefix=true and Velterop, Jan and Waagmeester, Andra and Wittenburg, Peter and Wolstencroft, Katherine and Zhao, Jun and Mons, Barend},
  date = {2016-03-15},
  journaltitle = {Scientific Data},
  shortjournal = {Sci Data},
  volume = {3},
  number = {1},
  pages = {160018},
  publisher = {{Nature Publishing Group}},
  issn = {2052-4463},
  doi = {10.1038/sdata.2016.18},
  url = {https://www.nature.com/articles/sdata201618},
  urldate = {2021-11-22},
  abstract = {There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.},
  issue = {1},
  langid = {english},
  keywords = {Publication characteristics,Research data},
  annotation = {Bandiera\_abtest: a Cg\_type: Nature Research Journals Primary\_atype: Comments \& Opinion Subject\_term: Publication characteristics;Research data Subject\_term\_id: publication-characteristics;research-data},
  file = {/home/daniel/Zotero/storage/HE5QCDCI/Wilkinson et al. - 2016 - The FAIR Guiding Principles for scientific data ma.pdf;/home/daniel/Zotero/storage/SJ2ZC5FI/sdata201618.html}
}

@article{wilson_softwarecarpentry_2006,
  title = {Software {{Carpentry}}: {{Getting Scientists}} to {{Write Better Code}} by {{Making Them More Productive}}},
  shorttitle = {Software {{Carpentry}}},
  author = {Wilson, G.},
  date = {2006-11},
  journaltitle = {Computing in Science \& Engineering},
  volume = {8},
  number = {6},
  pages = {66--69},
  issn = {1558-366X},
  doi = {10.1109/MCSE.2006.122},
  abstract = {For the past years, my colleagues and I have developed a one-semester course that teaches scientists and engineers the "common core" of modern software development. Our experience shows that an investment of 150 hours-25 of lectures and the rest of practical work-can improve productivity by roughly 20 percent. That's one day a week, one less semester in a master's degree, or one less year for a typical PhD. The course is called software carpentry, rather than software engineering, to emphasize the fact that it focuses on small-scale and immediately practical issues. All of the material is freely available under an open-source license at www.swc.scipy.org and can be used both for self-study and in the classroom. This article describes what the course contains, and why},
  eventtitle = {Computing in {{Science}} \& {{Engineering}}},
  keywords = {computation in undergraduate education,Computer science,continuing education,Debugging,Ethics,Java,Open source software,Physics,physics education,Portable computers,Programming profession,software engineering,Teamwork,World Wide Web},
  file = {/home/daniel/Zotero/storage/X67TS8Q3/1717319.html}
}

@inproceedings{winn_opendata_2013,
  title = {Open Data and the Academy: An Evaluation of {{CKAN}} for Research Data Management},
  shorttitle = {Open Data and the Academy},
  author = {Winn, Joss},
  date = {2013-05},
  location = {{Cologne}},
  url = {http://eprints.lincoln.ac.uk/id/eprint/9778/},
  urldate = {2023-07-12},
  abstract = {This paper offers a full and critical evaluation of the open source CKAN software (http://ckan.org) for use as a Research Data Management (RDM) tool within a university environment. It presents a case study of CKAN's implementation and use at the University of Lincoln, UK, and highlights its strengths and current weaknesses as an institutional Research Data Management tool. The author draws on his prior experience of implementing a mixed media Digital Asset Management system (DAM), Institutional Repository (IR) and institutional Web Content Management System (CMS), to offer an outline proposal for how CKAN can be used effectively for data analysis, storage and publishing in academia. This will be of interest to researchers, data librarians, and developers, who are responsible for the implementation of institutional RDM infrastructure. This paper is presented as part of the dissemination activities of the Jisc-funded Orbital project (http://orbital.blogs.lincoln.ac.uk)},
  eventtitle = {{{IASSIST}} 2013},
  langid = {english},
  file = {/home/daniel/Zotero/storage/J5V7BMCH/Winn - 2013 - Open data and the academy an evaluation of CKAN f.pdf;/home/daniel/Zotero/storage/PJQNY5WA/9778.html}
}
