You can now upload your research data on Mendeley when you submit your paper on SSRN.
SSRN is a research paper repository specializing in social sciences, including economics, law, corporate governance, and humanities. It is a great way to share your work and read the work of other researchers.
Mendeley started as a reference manager and is now also an academic social network and a research data repository through Mendeley Data. SSRN and Mendeley are both edited by Elsevier.
Recently, SSRN added a feature to help researchers like you upload their research data on Mendeley while they post their research paper. Then, the data will be linked to the published paper and be citable so the researcher can receive credit if another researcher uses it.
If you are interested in this new feature, next time you log in, while you post your paper on SSRN, just click on Upload research data and you will be redirected to Mendeley Data.
It is a good opportunity to capitalize on your work. Letting other researchers accessyour data can help them validate your research and increase your own confidence in your work.
Do you have a Persistent Identifier (or PID for short)?
You maybe use or heard about DOIs (digital object identifiers), an identifiers that can be used to find articles or journals and will always give access to the resource, unlike an URL that can break and sometimes lead to an error message. This type of identifiers exists also for a person.
The ORCID ID
You may have a homonym (even one in the same field of research than you) or you name can appear differently depending on the publisher or website. This can make difficult to attribute your work correctly. ORCID (Open Researcher and Contributor Identifier) lets you create your own personal identifier that can be useful for two main reasons:
It improves the attribution and discoverability of your work
It is compatible with 71 publishers (including Elservier, Wiley, Taylor & Francis and Emerald) and help you with the article application
How to register
Creating an ORCID ID is free, easy and quick, just click here and follow the steps.
The ORCID ID is not the only personal identifier out there, e.g. Clarivate provide the possibility to create a Researcher ID. The good news is that you do not have to choose between them, if you already have a PID but wishes to create an ORCID ID you can easily link you two (or more) identifiers.
Thanks to a new partnership between Clarivate and Impactstory, it is now possible to research and access to Open Access articles using Web of Science!
What’s is Web of Science?
Web of Science is a citation database that let you search for information about articles on a particular topic, or from a author, editor and even funding agency. You can create email alerts of you search and be informed when one of your article is cited.
What’s new on Web of Science?
Web of Science will now enable you to access Gold and Green Open Access journals and articles, it could be the Accepted Version Manuscript or the Published Version. With a preference to the publisher’s Gold version.
How can I do that?
The Library subscribe to the Web of Science, you can access it here.
Clarivate published a 5 minutes video on this subject, you can view it here:
Horizon 2020 is the biggest EU Research and Innovation programme ever with nearly €80 billion of funding available over 7 years (2014 to 2020).
Here is a three minute animation clip which will give you a general overview of the programme specifics:
Open access to scientific peer reviewed publications has been anchored as an underlying principle in the Horizon 2020 and is explained in the Regulation and the Rules of Participation as well as through the relevant provisions in the grant agreement (see Horizon 2020 Annotated Model Grant Agreement, October 2015 with information about open access on the pages 216-219).
A new element in Horizon 2020 is the use of Data Management Plans (DMPs) detailing what data the project will generate, whether and how it will be exploited or made accessible for verification and re-use, and how it will be curated and preserved. The use of a Data Management Plan is required for projects participating in the Open Research Data Pilot.
Ask the library to know more about the Guidelines on Open Access to Scientific Publications and Research Data in Horizon 2020 and the Guidelines on Data Management in Horizon 2020.
As for JISC, most of the activities involved are: naming files so you can find them quickly; keeping track of different versions, and deleting those not needed; backing up valuable data and controlling who has access to your data.
Apart from this very interesting and useful guide, JISC recommends the following training programmes available online, mostly originating from Jisc funding:
Mantra – a free online course designed for researchers or others who manage digital data as part of a research project
TraD – includes a blended learning course for those in (or expecting to be in) research data management support roles
RDMRose – an open educational resource for information professionals on research data management
Sharing of scholarly articles is widespread and increasing. The Beyond Downloads project (Elsevier) looks at scholars’ sharing behavior and what download counts are missing to better measure the reach —and impact — of a library’s resources.
This is an example of the answer to the question:
Find out more responses from 1,000 faculty members, researchers and PhD/master’s students.
Forrester’s Playbook framework organizes Forrester research content and services with a lifecycle approach.
Each Playbook comprises an Executive Overview and 12 reports with integrated tools and templates. In addition to the core research, the Playbook experience can be customized with global data, peer communities, and analyst engagements:
Data-driven insights into changing behaviors
Collaboration with peers at other companies who are facing or have faced similar challenges.
Time with analysts through structured workshops, one-on-one advisory sessions, or deeper consulting support.
Here are press articles and blog posts you might be interested to read:
Elsevier stopped me doing my research on Chris H.J. Hartgerink’s Notebook, November 16, 2015.
Chris H.J. Hartgerink presents himself as “a statistician interested in detecting potentially problematic research such as data fabrication, which results in unreliable findings and can harm policy-making, confound funding decisions, and hampers research progress.”
He explains that he has downloaded30,000items from the PsychologyElsevierScienceDirectdatabase toconduct searcheson text mining but “Elsevier notified my university that this was a violation of the access contract, that this could be considered stealing of content.”
We recommend you read the comments at the end of the post, which deal with the Elsevier API vs the “normal web service” and which were posted by Elsevier representatives and other researchers.
Semantic Scholar is a new service for scientific literature search and discovery, focusing on semantics and textual understanding.
This search engine allows users to find key papers about a topic or to produce a list of important citations or results in a given paper. It also serves as a resource and test bed for research in AI.
This search engine unveiled on 2 November by the non-profit Allen Institute for Artificial Intelligence (AI2) in Seattle, Washington, is working towards an understanding of a paper’s content: “We’re trying to get deep into the papers and be fast and clean and usable,” says Oren Etzioni, chief executive officer of AI2.”No one can keep up with the explosive growth of scientific literature. Which papers are most relevant? Which are considered the highest quality? Is anyone else working on this specific or related problem? Now, researchers can begin to answer these questions in seconds, speeding research and solving big problems faster.”
The product is currently limited to searching about 3 million open-access papers in computer science. But the AI2 team aims to broaden that to other fields within a year.
Using machine reading and vision methods, Semantic Scholar crawls the web, finding all PDFs of publically available scientific papers on computer science topics, extracting both text and diagrams/captions, and indexing it all for future contextual retrieval. Using natural language processing, the system identifies the top papers, extracts filtering information and topics, and sorts by what type of paper and how influential its citations are. It provides the scientist with a simple user interface (optimized for mobile) that maps to academic researchers’ expectations. Filters such as topic, date of publication, author and where published are built in. It includes smart, contextual recommendations for further keyword filtering as well.