FAQ

When doing an advanced search in Mendeley Data, use the following information regarding syntax for different ways to search for 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
• TITLE()
• INSTITUTION()
• INSTITUTION_ID()
• ID()
• DOI()
• KEYWORDS
• SUBJECT_AREA
• IS_SUPPLEMENT_TO

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.

Boolean Search Terms

Additionally, DataSearch supports Boolean search terms. You may search for data on DataSearch 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 DataSearch 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)

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 extensibly: 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.

To begin, go to data.mendeley.com 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.

Enter keywords into the Search field, then click the Search icon (magnifying glass) or click Enter. To filter results, check the desired check boxes in the left column. You can filter by Data Type, Repository Type, and Source.

Note: While you are able to make multiple selections from the Data Type option, you may only make one selection from the Repository Type and Source options. Also, if you select Dataset or Text from the Data Type option, it will automatically default the Repository Type to Data Repository and if you select Slides or Geospatial Data from the Data Type option, it will automatically default the Repository Type to Article Repository. The number displayed behind each filter type indicates the number of results for that type.

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: Although it is possible to upload a zip file, you cannot preview its contents. You will need to download the zip file to view its contents.

After previewing the results, if you decide this is what you are looking for, then you can access full information by clicking either More Details or Go to source, depending on what you are viewing.

For example, depending on the Source, clicking Go to source allows you to download, cite, share, or export the content, and clicking More Information opens the home page of a dataset and allows you to download the files and have full metadata access.

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.

After logging in at data.mendeley.com, click the main tab, Datasets. Then, click My 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 search window, 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 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.

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.

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: for instructions on adding and removing contributors, refer to “How do I draft and edit a dataset?” and go to section “How do I add or remove contributors?”. 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 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, click Publish once you are ready to publish it. 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 “My Collections” page with a status of “Published”. Collections are also searchable and will appear in the Find Research Data section of Mendeley Data as well as on your institution's homepage.

Upon signing into data.mendeley.com, the Datasets homepage opens by default. Click My Datasets. The My Datasets page displays a list of all the datasets for the institution with which you are affiliated. For librarians who wish to monitor their institution’s datasets (when they are published as well as the repositories where they are located), click the Data Monitor tab at the top of the page. A list of datasets displays.

Note: Your user role must have the appropriate privileges in order for the Data Monitor tab to appear.

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

Yes, with the DOI() field code users can search for datasets by DOI. With the IS_SUPPLEMENT_TO() field code users can search for datasets that are supplements to a publication identified by a DOI. Boolean operators apply to both fields, so you can do DOI(a OR b OR c) and IS_SUPPLEMENT_TO(a OR b OR c…). See also How do I search for data, including advanced search options? for more information.

How do I filter what datasets appear?

To filter the list of results, use the filters in the left panel. You can filter by date of publication and enter a specific date range. Click 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.

Additional filters include Repositories and Data type. Simply enter search words in each of the filter’s respective text fields or select one or more check boxes from each of the filter’s respective lists, of which the Repository list is in descending order (repository with most datasets at the top). You are also able to make multiple selections for each.

At the top of the left panel is the Institutional datasets dropdown 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 Mendeley DataSearch database. Refer to [Which data repositories are indexed in Mendeley Data Search?] (https://data.mendeley.com/faq#find-data-18-indexing-repositories) 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 How do I search for data, including advanced search options? and go to section “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 dropdown 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 check boxes 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 dropdown 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” dropdown menu.

Note: We do our best to represent the original datasets in the Mendeley Data Monitor corpus. In some cases, when a dataset contains institutional affiliation information in its original metadata, this affiliation cannot be corrected in Mendeley 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.