Ivan Herman

Extracellular enzymes are involved in the fungal pathogenesis in plants. Currently, culture media, data analyses, and data report related to extracellular enzymes produced in vitro conditions are different and therefore, lack standardization. This work aimed to compare the culture media cited on the literature (normal) with the potato-dextrose-agar (PDA) medium combined with a specific compound to produce extracellular enzymes through three soilborne phytopathogenic fungi (F. solani f. sp. passiflorae, S. rolfsii, and R. solani AG-4 HGI), as well as to analyze and report enzyme data based on five different criteria. The assay was randomized, with three factors (culture media, isolates, and enzymes) and six repetitions. The studied enzymes were amylase (AM), carboxymethylcellulase (CMCase), lipase (LP), laccase (LC), catalase (CT), and gelatinase (GT). The normal media detected more enzymes and was more precise compared to the PDA medium plus specific compound. The criteria that calculated the area of the circular crown of AM, CMCase, LP, and LC and measured the intensity (0 = absence, up to 4 = intense) of CT and GT adopting note scale were the best to evaluate and report the results of the enzymes. We suggest the normal media culture to study enzyme production, as well as the criteria mentioned to assess and report the data related to enzyme activities.

This report documents the program and the outcomes of Dagstuhl Perspectives Workshop 11331 “The Future of Research Communication”. The purpose of the workshop was to bring together researchers from these different disciplines, whose core research goal is changing the formats, standards, and means by which we communicate science.

Reproducibility and reusability of research results is an important concern in scientific communication and science policy. A foundational element of reproducibility and reusability is the open and persistently available presentation of research data. However, many common approaches for primary data publication in use today do not achieve sufficient long-term robustness, openness, accessibility or uniformity. Nor do they permit comprehensive exploitation by modern Web technologies. This has led to several authoritative studies recommending uniform direct citation of data archived in persistent repositories. Data are to be considered as first-class scholarly objects, and treated similarly in many ways to cited and archived scientific and scholarly literature. Here we briefly review the most current and widely agreed set of principle-based recommendations for scholarly data citation, the Joint Declaration of Data Citation Principles (JDDCP). We then present a framework for operationalizing the JDDCP; and a set of initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data. The main target audience for the common implementation guidelines in this article consists of publishers, scholarly organizations, and persistent data repositories, including technical staff members in these organizations. But ordinary researchers can also benefit from these recommendations. The guidance provided here is intended to help achieve widespread, uniform human and machine accessibility of deposited data, in support of significantly improved verification, validation, reproducibility and re-use of scholarly/scientific data.

Reproducibility and reusability of research results is an important concern in scientific communication and science policy. A foundational element of reproducibility and reusability is the open and persistently available presentation of research data. However, many common approaches for primary data publication in use today do not achieve sufficient long-term robustness, openness, accessibility or uniformity. Nor do they permit comprehensive exploitation by modern Web technologies. This has led to several authoritative studies recommending uniform direct citation of data archived in persistent repositories. Data are to be considered as first-class scholarly objects, and treated similarly in many ways to cited and archived scientific and scholarly literature. Here we briefly review the most current and widely agreed set of principle-based recommendations for scholarly data citation, the Joint Declaration of Data Citation Principles (JDDCP). We then present a framework for operationalizing the JDDCP; and a set of initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data. The main target audience for the common implementation guidelines in this article consists of publishers, scholarly organizations, and persistent data repositories, including technical staff members in these organizations. But ordinary researchers can also benefit from these recommendations. The guidance provided here is intended to help achieve widespread, uniform human and machine accessibility of deposited data, in support of significantly improved verification, validation, reproducibility and re-use of scholarly/scientific data.

Reproducibility and reusability of research results is an important concern in scientific communication and science policy. A foundational element of reproducibility and reusability is the open and persistently available presentation of research data. However, many common approaches for primary data publication in use today do not achieve sufficient long-term robustness, openness, accessibility or uniformity. Nor do they permit comprehensive exploitation by modern Web technologies. This has led to several authoritative studies recommending uniform direct citation of data archived in persistent repositories. Data are to be considered as first-class scholarly objects, and treated similarly in many ways to cited and archived scientific and scholarly literature. Here we briefly review the most current and widely agreed set of principle-based recommendations for scholarly data citation, the Joint Declaration of Data Citation Principles (JDDCP). We then present a framework for operationalizing the JDDCP; and a set of initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data. The main target audience for the common implementation guidelines in this article consists of publishers, scholarly organizations, and persistent data repositories, including technical staff members in these organizations. But ordinary researchers can also benefit from these recommendations. The guidance provided here is intended to help achieve widespread, uniform human and machine accessibility of deposited data, in support of significantly improved verification, validation, reproducibility and re-use of scholarly/scientific data.

Construit sur la base de technologies existantes (protocole HTTP (HyperText Transfert Protocol), identifiant URI (Uniform Resource Identifier), qui désigne de manière unique un document sur le Web...), le Web sémantique, par une participation toujours plus active de la communauté des internautes, constitue une nouvelle étape dans la logique de partage qui caractérise le Web actuel.