An Analytics Tool for Exploring Scientific Software and Related Publications

Hoppe, Anett; Hagen, Jascha; Holzmann, Helge; Kniesel, Günter; Ewerth, Ralph

doi:10.1007/978-3-030-00066-0_27

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Methods for entity and relation extraction (see Section 2.3) can help to populate finegrained KGs with high coverage and entity linking approaches can link mentions in text with entities. For cross-modal linking, Singh et al [60] propose an approach to detect URLs to datasets in research articles automatically, while the Scientific Software Explorer [34] interlinks text passages in research articles with code fragments. To extract relevant information at sentence level, approaches for sentence classification in scientific text can be employed (see Section 2.3).…”

Section: (Semi-)automatic Approachesmentioning

confidence: 99%

Requirements Analysis for an Open Research Knowledge Graph

Brack,

Hoppe,

Stocker

et al. 2020

Preprint

Self Cite

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Current science communication has a number of drawbacks and bottlenecks which have been subject of discussion lately: Among others, the rising number of published articles makes it nearly impossible to get an overview of the state of the art in a certain field, or reproducibility is hampered by fixedlength, document-based publications which normally cannot cover all details of a research work. Recently, several initiatives have proposed knowledge graphs (KGs) for organising scientific information as a solution to many of the current issues. The focus of these proposals is, however, usually restricted to very specific use cases. In this paper, we aim to transcend this limited perspective by presenting a comprehensive analysis of requirements for an Open Research Knowledge Graph (ORKG) by (a) collecting daily core tasks of a scientist, (b) establishing their consequential requirements for a KG-based system, (c) identifying overlaps and specificities, and their coverage in current solutions. As a result, we map necessary and desirable requirements for successful KG-based science communication, derive implications and outline possible solutions.

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Section: (Semi-)automatic Approachesmentioning

confidence: 99%

Requirements Analysis for an Open Research Knowledge Graph

Brack,

Hoppe,

Stocker

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Authors can connect a result in the article produced by code to the corresponding code snippet by wrapping the relevant functions into tags. The system SciSoftX offers a similar functionality but also provides a UI for readers to examine the selected code and text in parallel [23]. To achieve that, authors create links between code snippets and the paragraph, which are then highlighted in the manuscript.…”

Section: Connecting Paper Code and Datamentioning

confidence: 99%

Creating Interactive Scientific Publications using Bindings

Konkol

Kray

Suleiman

2019

Proc. ACM Hum.-Comput. Interact.

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Many scientific publications report on computational results based on code and data, but even when code and data are published, the main text is usually provided in a separate, traditional format such as PDF. Since code, data, and text are not linked on a deep level, it is difficult for readers and reviewers to understand and retrace how the authors achieved a specific result that is reported in the main text, e.g. a figure, table, or number. In addition, to make use of new the opportunities afforded by data and code availability, such as re-running analyses with changed parameters, considerable effort is required. In order to overcome this issue and to enable more interactive publications that support scientists in more deeply exploring the reported results, we present the concept, implementation, and initial evaluation of bindings. A binding describes which data subsets, code lines, and parameters produce a specific result that is reported in the main text (e.g. as a figure, table, or number). Based on a prototypical implementation of these bindings, we propose a toolkit for authors to easily create interactive figures by connecting specific UI widgets (e.g. a slider) to parameters. In addition to inspecting code and data, readers can then manipulate the parameter and see how the results change. We evaluated the approach by applying it to a set of existing articles. The results provide initial evidence that the concept is feasible and applicable to many papers with moderate effort.

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“…Authors can connect a result in the article produced by code to the corresponding code snippet by wrapping the relevant functions into tags. The system SciSoftX offers similar functionality but also provides a UI for readers to examine the selected code and text in parallel (Hoppe et al, 2018). To achieve that, authors create links between code snippets and the paragraph, which are then highlighted in the manuscript.…”

Section: Connecting Paper Code and Datamentioning

confidence: 99%

Publishing Reproducible Geoscientific Papers: Status quo, benefits, and opportunities

Konkol¹

2019

Preprint

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Open reproducible research (ORR) is the practice of publishing the source code andthe datasets that are needed to produce the computational results reported in a paper.Since geoscientific articles often include geostatistical analyses and spatiotemporaldata, reproducibility should be a cornerstone of the computational geosciences butis rarely realized. In addition, the current way of publishing scientific outcomes, i.e.as static PDFs, does not adequately report on computational aspects. Thus, readerscannot fully understand how the authors came to the conclusions and how robustthese are to changes in the analysis. Consequently, it is difficult for reviewers tofollow the analysis steps, and for other researchers to reuse existing materials. Thisdissertation has two overarching goals to tackle these issues: First, it aims at assistingauthors in adhering to ORR principles to ensure high scientific standards. The secondgoal is to reap the benefits that come with papers supplemented by code and data. Toachieve these objectives, this thesis reports on five complementary studies to collectand analyze qualitative (i.e. through interviews and a focus group) and quantitativedata (i.e. through surveys and reproducibility studies). Based on these studies, thiswork provides four key contributions: First, it identifies obstacles that preventedgeoscientists from publishing ORR. To overcome these barriers, this dissertationsuggests concrete and directly applicable strategies. One of these strategies is theexecutable research compendium (ERC) which encapsulates the paper, code, data,and the entire software environment needed to produce the computational results.Based on that, this work presents the design and implementation of an ERC-basedworkflow. It allows authors to convey their computational methods and results byalso providing interactive access to code and data, and readers to deeply investigatethe computational analysis while reading the actual article, e.g. by changing theparameters of the analysis. Finally, this work describes the concept of a binding; abinding connects those code lines and data subsets that produce a specific result, e.g.a figure or number. By also considering user interface widgets (e.g. a slider), thisapproach allows readers to interactively manipulate the parameters of the analysisto see how these changes affect the result. To conclude, the contributions include (i)a set of obstacles which prevent geoscientists from publishing ORR, (ii) conceptsand tools to overcome the identified barriers, (iii) incentives and opportunities thatcome with attached code and data, and (iv) solutions to realize the incentives whicheventually result in a higher number of open and reproducible research.

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An Analytics Tool for Exploring Scientific Software and Related Publications

Cited by 6 publications

References 8 publications

Requirements Analysis for an Open Research Knowledge Graph

Requirements Analysis for an Open Research Knowledge Graph

Creating Interactive Scientific Publications using Bindings

Publishing Reproducible Geoscientific Papers: Status quo, benefits, and opportunities

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