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Announcement

As of July 15th, Mendeley Data for Institutions becomes Digital Commons Data and Mendeley Data Monitor becomes Data Monitor. We continue to offer researchers Mendeley Data as an open data repository to create and share FAIR data when domain-specific or an institutional repository is not available to them. Learn more here.

Data Monitor

When doing an advanced search in Mendeley Data use the following information regarding syntax for different ways to search for data. Data Monitor is a corpus that is currently served through Mendeley Data.

Searching within fields

Use the following syntax to target one or more specific fields within a dataset by entering the desired field code and then placing the name in parenthesis following it. Note that the syntax field codes must be capitalized as below. For example, when searching by Author, type “AUTHOR(Jane Smith)”.
  • AUTHOR()
  • AUTHOR_ID()
  • ID()
  • DOI()
  • TITLE()
  • KEYWORDS()
  • INSTITUTION()
  • SOURCE()
  • SUBJECT_AREA()
  • INSTITUTION_ID()
  • IS_SUPPLEMENT_TO()
  • DATA_TYPE()
  • PUBLICATION_YEAR()

Note: Regarding the following field codes:

  • AUTHOR_ID() supports the following IDs: Mendeley User ID, Scopus User ID, ORCID and all user IDs supported by DataCite.
  • INSTITUTION_ID() supports the following IDs: Scopus Institution ID, Scival Institution ID, Mendeley Institution ID.
  • DATA_TYPE values must match (case sensitive) exactly one of the following:
    • AUDIO
    • CHEMICAL_STRUCTURES
    • COLLECTION
    • DATASET
    • DOCUMENT
    • EVENT
    • FILE_SET
    • GEO_DATA
    • IMAGE
    • INTERACTIVE_RESOURCE
    • MODEL
    • OTHER
    • PHYSICAL_OBJECT
    • SEQUENCING_DATA
    • SLIDES
    • SOFTWARE_CODE
    • TABULAR_DATA
    • TEXT
    • VIDEO
    • WORKFLOW
    • SOURCE() values must be an exact match (case sensitive). A list of Source IDs indexed by Data Monitor can be found here.

    Boolean Search Terms

    Additionally, DataSearch supports Boolean search terms. You may search for data on Data Monitor using AND, OR or NOT query terms. Field codes can also be used in any boolean query, which includes OR between normal and field code queries. Currently Data Monitor can process queries like these:
    • chip-seq drosophila AUTHOR(Doe)
    • chip-seq drosophila AUTHOR(Doe OR Hari)
    • chip-seq drosophila AUTHOR(Hari) AND INSTITUTION(University of Manchester)
    • chip-seq AND (drosophila OR “fruit fly”) AND ID(GEO4667)
    • (chip-seq drosophila AND AUTHOR(Doe)) OR AUTHOR(Doe AND Hari)
    • IS_SUPPLEMENT_TO(10.1016/j.dib.2015.10.003)
    • SOURCE(MENDELEY_DATA)
    • DATA_TYPE(IMAGE AND DATASET)
    • PUBLICATION_YEAR(2019 OR 2020 OR 2021)
    When no operator is included this is assumed to be an implicit OR'. If you want to perform an exact match of the text being provided by a Field Code, you can use Field Code modifiers. We offer two ways to do it:
    • FIELD CODE(“abcdfg”)
    • FIELD CODE({abcdfg})
    Operators (AND, OR and NOT) are not recognized inside a Field Code modifier. As such, queries using FIELD CODE(“xxxx OR yyyy”) will probably not retrieve the results one would expect. There are three ways to use operators inside a field code:
    • Using a Field Code (without any modifiers): AUTHOR(John OR Martha)
    • Splitting the operands into separate Field Codes with modifiers: AUTHOR({John}) OR AUTHOR({Martha})
    • Using double quotes in a field code modifier. This is accepted in order to provide backwards compatibility to very common queries that might have been used extensively: INSTITUTION(“University of Manchester” OR “University of Oxford”)

    Note: INSTITUTION({University of Manchester} OR {University of Oxford}) is not accepted! Use INSTITUTION({University of Manchester}) OR INSTITUTION({University of Oxford}) instead.

    It should be noted that using the “xxxx” construct (i.e. using double quotes to specify an exact text match in a search) is also allowed outside a Field Code. The behavior for such a query is expected. All words inside the double quotes are searched as they appear.

    Alternatively, the {xxxx} construct ((i.e. using curly braces to specify an exact text match in a search) is only accepted as a Field Code modifier and is not accepted in a free text search (as curly braces are not accepted characters for free text search).

    To conclude, here are some simple examples:

    • AUTHOR(“John Doe”) - will search for authors whose names have exactly the words John followed by Doe in any part of their names.
    • DOI({123456:1132/121(56)789}) - will search for the document that has a 123456:1132/121(56)789 DOI identifier.
    • ID(“1234.1224”) - will search for the document that has a 1234.1224 external identifier.
    • AUTHOR({John Doe OR Martha Hari}) - will search for authors whose names are John Doe OR Martha Hari in any part of their names (probably not finding anything).
    • AUTHOR({John Doe}) OR AUTHOR(“Martha Hari”) - will search for authors whose names have either the sequence John Doe or Martha Hari in any part of their names.
    • DATA_TYPE(*) AND PUBLICATION_YEAR(2008)

To begin, go to Mendeley Data and click Sign In in the top right section of the page. Upon logging in, the Mendeley Data homepage appears. Click Find Research Data. The Search page displays.

Note: While it is possible to perform a search without doing so, logging into Mendeley Data provides more metadata content. Data Monitor is a corpus that is currently served through Mendeley Data.

Enter keywords into the Search field, then click the Search icon (magnifying glass) or click Enter. To filter results, tick the desired checkboxes in the left column. You can filter by Data Type, Source Type, and Source. The number displayed behind each filter type indicates the number of results for that type.

Note: While you are able to make multiple selections from the Data Type option, you may only make one selection from the Source Type and Source options.

Search results appear in the right panel, and each results line item displays basic information such as Contributors, Date, Source, and more.

To view more detailed information, click the title of one of the results line items to expand it, where you will see in the left column under Details, one or more files associated with it.

Enabled by deep indexing, clicking on a file allows you to quickly preview its contents without having to open it. Also, you can verify that keywords in your original search terms are present inside a file, as indicated if a green check mark is next to it.

Note: It is not possible to preview the content of a zip file.

After previewing the results, if you decide this is what you are looking for, to access the full information to to download, cite or share a dataset click More Details/Go to source.

Advanced Search

You can perform an advanced search query by use syntax for different ways to search for data such as searching within fields and using Boolean search terms. For more information about syntax for an advanced search, simply click Advanced search help beneath the search field and then click What are the syntax criteria for an advanced search (Field codes and Boolean)? This will reference the FAQ associated with this topic that will help you complete the advanced search.

Upon signing into data.mendeley.com, the My Data page opens by default. For librarians who wish to monitor their institution’s datasets, click the Data Monitor tab at the top of the page. A list of datasets displays.

Is it possible to search with a DOI and find relevant data?

Users can search for a specific dataset by typing the precise DOI in the search box above the dataset list and by clicking the magnifying glass icon.

How do I filter what datasets appear?

To filter the list of results, use the filters in the left panel. You can filter by Publication Date, Added Date, Repositories or Data Types. You also can filter using a specific date range in by clicking the calendar icons to enter From and Until dates. Or, you may choose to select one of the radio buttons to filter by Anytime, Last 3 months, or Last 12 months.

To filter by Repository or Data Type enter search words in each of the filter’s respective text fields or select one or more checkboxes from each of the filter’s respective lists. You are also able to make multiple selections for each.

At the top of the left panel is the Institutional datasets drop-down menu. This allows you to make a selection to filter by the following:

  • All datasets (default setting) – this list shows all of your institution’s datasets.
  • Automatically excluded datasets – this list shows…
  • Manually excluded datasets –Once completely processed, this list shows all datasets that have been manually excluded using the Exclude feature in Data Monitor.
  • Pending additions – this list shows all datasets that were added using the Add feature in Data Monitor and are being processed.
  • Pending exclusions - this list shows all datasets that were excluded using the Exclude feature in Data Monitor and are being processed.

What other actions can I take with Data Monitor?

Once you have entered filters to generate the datasets you want to monitor, you can click the dataset title to view metadata including the description, the repository where it is located, contributors, the date it was published, the Dataset DOI/PID, and the types of data contained within it. To view the actual dataset, click the View dataset button or, if applicable, click the View article button to view the article.

How do I add datasets to my institution?

If you find it necessary to add datasets to your institution, from the menu at the top of the right panel, click Add. The Add datasets dialogue box opens, prompting you to add a dataset by copying the DOI or persistent identifier into the field, or by searching the Data Monitor corpus. Refer to Which data repositories are indexed in Data Monitor? to learn more about our dataset corpus.

Once a list of search results appears, click the + Add dataset button for the dataset(s) you wish to add. If you need to do an advanced search, please refer to help article How do I search for data, including advanced search options? and go to the section labeled Advanced Search. When you are finished adding the datasets you want, click the ‘x’ at the top right of the box to close it. The newly added dataset will appear on the list of Pending additions, found in the Institutional datasets drop-down menu and will show up in your institution’s dataset list as well as the showcase page in approximately twenty-four (24) hours.

Note: Only librarians with access to Data Monitor can add datasets, and only to their own institution.

How do I exclude datasets from my institution?

If necessary to exclude datasets from your institution you must first select what you want to exclude. From the list of results on the right panel, check one or more checkboxes next to the desired dataset. From the menu at the top of the right panel, click Exclude. The Exclude datasets dialogue box opens, prompting you to confirm that you want to exclude the dataset(s). Click the Exclude button to confirm. The excluded dataset will appear on the list of Pending exclusions, found in the Institutional datasets drop-down menu and will be removed from your institution’s dataset list as well as the showcase page in approximately twenty-four (24) hours. Once the exclusion is completely processed, it will appear on the list of Manually excluded datasets, found in the Institutional datasets drop-down menu.

Note: We do our best to represent the original datasets in the Data Monitor corpus. In some cases, when a dataset contains institutional affiliation information in its original metadata, this affiliation cannot be corrected in Data Monitor. If you think you found a potential error, we advise that you first check the original dataset and if corrections are needed submit your request to the repository where the dataset is hosted.

How do I export datasets?

You may export all datasets listed in your institution’s Data Monitor page by clicking Export All and then selecting the preferred format (Data as CSV or Data as XLSX) from the dropdown menu that appears. To export a list of selected datasets you must first select what you want to export. From the list of results on the right panel, check one or more checkboxes next to the desired dataset. Then click the Export Selected dropdown menu and then select your preferred file format. Save the file to a location of your choice as you normally would. This is helpful in allowing you to analyze the information about the datasets you exported.

Digital Commons Data

After logging to your institution’s Digital Commons Data repository instance, in the My Data click Collections. This is the point from which you can add a new collection. To add a new collection, click the + New Collection button. The New Collection dialogue box opens, prompting you to enter a Name and Description for the new collection. Then, click Create collection.

How do I add a dataset to a collection?

Now you will add items to your collection. Mainly you will add datasets, but you can also add articles or even other collections. To add a dataset, click + Add Dataset. This opens a Add datasets to [collection name] dialogue box, prompting you to enter keywords into the Find research data field.

Note: By default, the check box to only show results from your institution is checked. You can uncheck this if you choose to include datasets from sources outside your institution.

From the left panel, you can filter your search results by Data Types, Source Types, and Sources if you opted to deselect the default setting to only show datasets from your institution.

Note: If you need to perform and advanced search, simply click Advanced search help beneath the search field. This will reference the FAQ associated with this topic that will help you complete the advanced search.

Search results appear on the right panel of the window. To view more detailed information and to preview its files, click the title of a dataset. To add the dataset to your collection, click + Add to collection. This selection is now added to your new collection. Click the 'x' at the top right of the window to close it.

How do I edit a collection’s metadata?

You have the option to edit the metadata of your collection. Click Edit Metadata. The Edit Collection information dialogue box opens, allowing you to do the following:
  • Edit the name
  • Add or remove contributors
  • Add or remove categories and institutions
  • Edit the description

Note: Collections are not required to have any contributors.

Once you have made your edits, click Save. You may also add additional datasets or delete a dataset by clicking x Remove next to the dataset you want to delete.

How do I publish a collection?

Once you have created the collection, added datasets to it, and made any necessary edits, if you are ready to publish it, simply click Publish. A dialogue box appears, prompting you to confirm that you want to publish the collection. Click Publish to confirm.

Your collection now appears as a line item in the search results panel on the Collections page with a status of Published. Collections are also searchable and will appear in Data Monitor as well as on your institution's Digital Commons Data homepage.

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