| Path | Frage | Hilfstext | |||
|---|---|---|---|---|---|
| consultation/general | |||||
| consultation/general/topic-research_question | |||||
| consultation/general/topic-research_question/keywords | Please give some keywords describing the research question. | ||||
| consultation/general/topic-research_question/title | What is the main research question of the project? | ||||
| consultation/general/topic-research_field | |||||
| consultation/general/topic-research_field/name | Which persons or institutions are responsible for the project coordination? | ||||
| consultation/general/topic-research_field/research_field | Which research field(s) does this project belong to? | The list of disciplines follows the subject classification of the DFG (German Research Foundation). | |||
| consultation/general/project-partners-partner | |||||
| consultation/general/project-partners-partner/contact | Who is/are the contact person(s) for data management questions? | Please give the name and an email address. | |||
| consultation/general/project-partners-partner/rdm_policy | Does your institution have rules or guidelines for the handling of research data? If yes, please briefly outline them and refer to more detailed sources of information if necessary. Please also indicate, if the rules / guidelines are mandatory or optional. | More and more universities and scientific institutions adopt research data management policies. These contain, among other things, recommendations and / or demands concerning the handling of research data by researchers of the institution. Principles and guidelines on handling research data at Bielefeld University or the Research data policy of the Georg-August University Goettingen. |
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| consultation/general/project-partners-partner/name | Project partner | ||||
| consultation/general/funding-funder | |||||
| consultation/general/funding-funder/name | Who is funding the project? | ||||
| consultation/content-classification | |||||
| consultation/content-classification/data-dataset | |||||
| consultation/content-classification/data-dataset/description | What kind of dataset is it? | Please briefly describe the data type and / or the method used to create or collect the data, for example:
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| consultation/content-classification/data-existing_data | |||||
| consultation/content-classification/data-existing_data/creator_name | If re-used, who created the dataset? | ||||
| consultation/content-classification/data-existing_data/origin | Is the dataset being created or re-used? | ||||
| consultation/content-classification/data-reproducibility | |||||
| consultation/content-classification/data-reproducibility/reproducibility | Is the dataset reproducible in the sense that it could be created / collected anew in case it got lost? | Some data can, technically, be created anew at any time, as is the case with scientific experiments or digitised versions of analog objects (as long as the originals are still there and in good shape). However, this can consume a considerable amount of time and cost. With respect to long-term preservation, the effort of re-creation has to be weighed up against the effort of long-term preservation. Other data cannot be collected or created anew. Examples are all kinds of "time stamped" observations, be they from social science, astrophysics or any other discipline. Observations represent a certain phenomenon at a certain time and / or place and are therefore not repeatable. Their value for re-use as well as the loss in case of failed preservation is much higher than that of reproducible data. |
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| consultation/technical-classification | |||||
| consultation/technical-classification/data-volume | |||||
| consultation/technical-classification/data-volume/rate | How much data is produced per year? | Optional. This is only of concern if the data production rate reaches TB scale. | |||
| consultation/technical-classification/data-volume/volume | What is the actual or expected size of the dataset? | ||||
| consultation/technical-classification/data-formats | |||||
| consultation/technical-classification/data-formats/format | Which file formats are used? | When choosing a data format, one should consider the consequences for collaborative use, long-term preservation as well as re-use. It is advisable to prefer formats that are standardised, open, non-proprietary and well-established in the respective scholarly community. More criteria and detailed explanations can be found e.g. in the WissGrid-Leitfaden, pp. 22 f.). | |||
| consultation/data-usage | |||||
| consultation/data-usage/scenarios-usage | |||||
| consultation/data-usage/scenarios-usage/infrastructure | To what extent will infrastructure resources be required (e.g. CPU hours, bandwidth, storage space... etc.). | ||||
| consultation/data-usage/data-storage-and-security-storage | |||||
| consultation/data-usage/data-storage-and-security-storage/type | Where is the dataset stored during the project? | ||||
| consultation/data-usage/data-sharing-and-re-use-publication | |||||
| consultation/data-usage/data-sharing-and-re-use-publication/yesno | Will this dataset be published or shared? | ||||
| consultation/data-usage/collaborative-work-collaboration | |||||
| consultation/data-usage/collaborative-work-collaboration/yesno | Will the data be collaboratively used? | ||||
| consultation/metadata-and-referencing | |||||
| consultation/metadata-and-referencing/structure-granularity-and-referencing-structure | |||||
| consultation/metadata-and-referencing/structure-granularity-and-referencing-structure/structure | What is the structure of the data? How are the individual components of the dataset related to each other? How is the dataset related to other datasets used in the project? | ||||
| consultation/legal-and-ethics | |||||
| consultation/legal-and-ethics/sensitive-data-personal_data_yesno | |||||
| consultation/legal-and-ethics/sensitive-data-personal_data_yesno/yesno | Does this dataset contain personal data? | The handling and processing of personal data is regulated by law. The uniform application throughout the EU is based on the EU General Data Protection Regulation (GDPR). It allows for regulatory leeway at national level.
In Germany, this is regulated by the Federal Data Protection Act (BDSG), and for universities, the individual data protection laws of the individual federal states apply, e.g. the data protection law of North Rhine-Westphalia (DSG NRW). The european GDPR defines personal data as all information relating to an identified or identifiable natural person (Art. 4(1) GPDR). A person is identified if it is clearly identifiable to whom the data belongs. A person becomes identifiable if it can be identified by means of additional information. More information (in German only) can be found on the websites of the data protection officers of the UA Ruhr. |
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| consultation/legal-and-ethics/sensitive-data-personal_data | |||||
| consultation/legal-and-ethics/sensitive-data-personal_data/anonymization | Will the data be anonymised or pseudonymised? | ||||
| consultation/legal-and-ethics/sensitive-data-other | |||||
| consultation/legal-and-ethics/sensitive-data-other/yesno | Does this dataset contain sensitive data other than personal data? | Examples are data that contain trade or business secrets or geoinformation on endangered species. | |||
| consultation/legal-and-ethics/intellectual-property-rights-yesno | |||||
| consultation/legal-and-ethics/intellectual-property-rights-yesno/yesno | Does the project use and/or produce data that is protected by intellectual or industrial property rights? | Data or software can be subject to intellectual or industrial property rights. Applicable laws differ broadly even within EU.
According to the German copyright law (UrhG) works of literature, scholarship and the arts that can be regarded as a “personal intellectual creation” are protected by copyright. Copyright protection expires 70 years after the death of the copyright holder. Mere data, e.g. measured data or survey data, and metadata (except in some cases descriptive metadata) are not protected by copyright. § 2 of the UrhG lists the following kinds of protected works (list is not concluded):
According to § 3, copyright is also applicable to translations and other modifications or adaptions of a work if they are individual intellectual creations of the editor. Finally, according to § 4 copyright also extents to collected editions and database works. Collected editions are “collections of work, data or other independent elements that are individual intellectual creations based on the selection and arrangement of the elements”. Database works are defined as “collected editions, the elements of which are arranged in a systematic or methodical way and can be accessed individually by electronic means or in other ways”. Other relevant property rights can be trademarks, patents, utility models, plant variety rights protection, integrated circuit layout design protection, geographical indications or registered designs. |
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| consultation/storage-and-long-term-preservation | |||||
| consultation/storage-and-long-term-preservation/long-term-preservation-datasets | |||||
| consultation/storage-and-long-term-preservation/long-term-preservation-datasets/duration | How long will the data be stored? | ||||
| consultation/general/project-schedule-schedule | |||||
| consultation/general/project-schedule-schedule/project_duration | Project duration (month) | ||||
| consultation/general/other-requirements-yesno | |||||
| consultation/general/other-requirements-yesno/abstract | Are there requirements to the data management in the form of policies from ANY site? | ||||
| consultation/data-usage/data-sharing-and-re-use-interoperability | |||||
| consultation/data-usage/data-sharing-and-re-use/abstract | Are there restrictions accessing and re-using the data in general? | ||||
| consultation/metadata-and-referencing/metadata-dataset | |||||
| consultation/metadata-and-referencing/metadata-dataset/abstract | Which types of metadata are collected? Do you use any kind of standard, ontology or classification? | ||||