Category: dataset

CORE + GROBID: Structured Text from 34 Million Scientific Documents (and counting)

We very recently surveyed our CORE members to ask what was most important to them and we received wide-ranging feedback. The CORE dashboard provides a range of tools for our data providers and their repository managers and users. Much of the feedback we received was regarding providing additional or enhanced tools for managing repository content via the dashboard. For example, metadata validation and enrichment tools were regarded as highly important.

Interestingly however, what was most important was making repository content machine-readable. This is closely linked to identifying funding information and rights-retention strategies. Ensuring content is machine-readable allows for the extraction of far richer information from full-text documents than that available in the metadata alone. In the U.S., the recent OSPT memo on ‘Ensuring Free, Immediate, and Equitable Access to Federally Funded Research‘ includes machine-readability as a required component of the archiving and deposition of federally funded research. read more...

Using open access research in our battle against misinformation

Our society is facing significant challenges due to the widespread misinformation, in particular on social media, substantially influencing public opinion. As a result, we are seeing a lot of demand for innovative text processing methods to fact check and provide an automatic assessment of trustworthiness and credibility. Machine learning and natural language processing have started to be widely used to address this problem. 

While scientific papers have been traditionally seen as a source of mostly trustworthy information, their use within automated tools in the fight against misinformation, such as related to vaccine effectiveness or climate changes, has been rather limited. read more...

Partnership Announcement: Cypris and CORE

We’re delighted to announce a new partnership between CORE and Cypris, a leading AI-driven, market intelligence platform that connects research & development (R&D) teams with innovation data and trends in their field.

The partnership will provide Cypris with unlimited access to over 210 million open access articles to further enhance their platform and regularly add live market data to provide R&D teams with the most up-to-date research in their fields of interest.

Continue reading this news on the Jisc Research Blog. read more...

Flowcite Expands its Knowledge Library with 210 Million Research Papers from CORE

Flowcite has teamed up with CORE, the world’s largest aggregator of open access research papers. The partnership will provide Flowcite users with free and unlimited access to millions of open access research papers from the CORE database.

CORE is delighted to partner with Flowcite and progress our aligned goals to make open research content available to all. By connecting our innovative solutions we continue to evolve the way research is being completed and increase the discoverability and usage of all research outputs.” Dr Petr Knoth, CORE Founder. read more...

CORE becomes the world’s largest open access aggregator (or how about them stats 2018 edition)

This was another productive year for the CORE team; our content providers have increased, along with our metadata and full text records. This makes CORE the world’s largest open access aggregator

. More specifically, over the last 3 months CORE had more than 25 million users, tripling our usage compared to 2017. According to read more...

Increasing the Speed of Harvesting with On Demand Resource Dumps

 

I am currently working with Martin Klein, Matteo Cancellieri and Herbert Van de Sompel on a project funded by the European Open Science Cloud Pilot that aims to test and benchmark ResourceSync against OAI-PMH in a range of scenarios. The objective is to perform a quantitative evaluation that could then be used as evidence to convince data providers to adopt ResourceSync. During this work, we have encountered a problem related to the scalability of ResourceSync and developed a solution to it in the form of an On Demand Resource Dump. The aim of this blog post is to explain the problem, how we arrived to the solution and how the solution works.

The problem

One of the scenarios we have been exploring deals with a situation where the resources to be synchronised are metadata files of a small data size (typically from a few bytes to several kilobytes). Coincidentally, this scenario is very common for metadata in repositories of academic manuscripts, research data (e.g. descriptions of images), cultural heritage, etc.

The problem is related to the issue that while most OAI-PMH implementations typically deliver 100-1000 responses per one HTTP request, ResourceSync is designed in a way that requires resolving each resource individually. We have identified and confirmed by testing that for repositories with larges numbers of metadata items, this can have a very significant impact on the performance of harvesting, as the overhead of the HTTP request is considerable compared to the size of the metadata record.

More specifically, we have run tests over a sample of 357 repositories. The results of these tests show that while the speed of OAI-PMH harvesting ranges from 30-520 metadata records per second, depending largely on the repository platform, the speed of harvesting by ResourceSync is somewhere in the range of only 4 metadata records per second for harvesting the same content using existing ResourceSync client/server implementations and sequential downloading strategy. We are preparing a paper on this, so I am not going to disclose the exact details of the analysis at this stage.

As ResourceSync has been created to overcome many of the problems of OAI-PMH, such as:

  • being too flexible in terms of support for incremental harvesting, resulting in inconsistent implementations of this feature across data providers,
  • some of its implementations being unstable and less suitable for exchanging large quantities of metadata and
  • being only designed for metadata transfer, omitting the much needed support for content exchange

it is important that Resource Sync performs well under all common scenarios, including the one we are dealing with.

Can Resource Dumps be the solution?

An obvious option for solving the problem that is already offered by ResourceSync are Resource Dumps. While a Resource Dump can speed up harvesting to levels far exceeding those of OAI-PMH, it creates some considerable extra complexity on the side of the server. The key problem is that it creates the necessity to periodically package the data as a Resource Dump, which basically means running a batch process to produce a compressed (zip) file containing the resources.

The number of Resource Dumps a source needs to maintain is equal to the number of Capability Lists it maintains times the size of the Resource Dump Index. The minimum practical operational size of a Resource Dump Index is 2. This is to ensure we don’t remove a dump currently being downloaded by a client during the creation of a new dump. As we have observed that a typical repository may contain about 250 OAI-PMH sets (Capability Lists in the ResourceSync terminology), this implies the need for a significant data duplication and requirements on period creation of Resource Dumps if a source chose to use Resource Dumps as part of the harvesting process.

On Demand Resource Dumps

To deal with the problem, we suggest an extension of ResourceSync that will support the concept of an On Demand Resource Dump. An On Demand Resource Dump is a Resource Dump which is created, as the name suggests, whenever a client asks for it. More specifically, a client can scan through the list of resources presented in a Resource List or a Change List (without resolving them individually) and request from the source to package any set of the resources as a Resource Dump. This approach speeds up and saves processing on the side of both the source as well as the client. Our initial tests show that this enables ResourceSync to perform as well as OAI-PMH in the metadata only harvesting scenario when requests are sent sequentially (the most extreme scenario for ResourceSync). However, as ResourceSync requests can be parallelised, as opposed to OAI-PMH (due to the reliance of OAI-PMH on the resumption token), this makes ResourceSync a clear winner.

In the rest of this post, I will explain how this works and how it could be integrated with the ResourceSync specification.

There are basically 3 steps:

  1. defining that the server supports an on-demand Resource Dump,
  2. sending a POST request to the on-demand dump endpoint and
  3. receiving a response from the server that 100% conforms to the Resource Dump specification.

I will first introduce steps 2 and 3 and then I will come back to step 1.

Step 2: sending a POST request to the On Demand dump endpoint

We have defined an endpoint at https://core.ac.uk/datadump . You can POST it a list of resource identifiers (which can be discovered in a Resource List). In the example below, I am using curl to send it a list of resource identifiers in JSON which I want to get resolved. Obviously, the approach is not limited to JSON, it can be used for any resource listed in a Resource List regardless of its type. Try it by executing the code below in your terminal.

curl -d ‘[“https://core.ac.uk/api-v2/articles/get/42138752″,”https://core.ac.uk/api-v2/articles/get/32050″]‘ -H “Content-Type: application/json” https://core.ac.uk/datadump -X POST > on-demand-resource-dump.zip read more...

CORE’s Open Access content has reached the Moon! (or how about them stats 2017 edition)

For yet another year (see previous years 2016, 2015) CORE has been really productive; the number of  our content providers has increased and we have now more open access full text and metadata records than ever.

Our services are also growing steadily and we would like to thank the community for using the CORE API and CORE Datasets.

We also offer other services, such as the CORE Repositories Dashboard, CORE Publisher Connector and the CORE Recommender. We received great feedback with regards to the CORE Recommender, with George Macgregor, Institutional Repository Manager at Strathclyde University, reporting:

We are thrilled that this year CORE made it to the moon. Our next destination is Venus.

The CORE Team wishes you Merry Christmas and a Prosperous New Year!

* Note: Special thanks to Matteo Cancellieri for creating the graphics in this blog post.

CORE now offers 5 millions of open access full-text research papers

CORE is thrilled to announce that it currently provides 5 millions of open access full-text papers.

CORE’s data providers from around the world

“In the last year, we have managed to scale up our harvesting process. This enabled us to significantly increase the amount of open access content we can offer to our users. With more and more open access content being made available by data providers, thanks to recent open access policies, CORE now also captures and provides access to a higher percentage of global research literature ”, says CORE’s founder, Dr Petr Knoth.

With 66 million metadata records and 5 million full-text, from 102 countries, in 52 different languages, CORE becomes now the world’s largest full-text open access aggregator. CORE embraces the vibrant collections of both institutional and disciplinary repositories, while its large volume of scholarly outputs ranges from scientific research papers, to grey literature and from Master’s to Doctoral thesis. In addition, it is a metasearch for the all the open access peer-reviewed scientific journal articles published in open access journals. read more...

CORE’s open access and text mining services – 2016 growth (or, how about them stats – 2016 edition)

The past year has been productive for the CORE team; the number of harvested repositories and our open access content, both in metadata and full-text, has massively increased. (You can see last year’s blog post with our 2015 achievements in numbers here.)

There was also progress with regards to our services; the number of our API users was almost doubled in 2016, we have now about 200 registered CORE Dashboard users, and this past October we released a new version of our recommender and updated our dataset.

Around this time of the year, the joyful Christmas spirit of the CORE team increases along with our numbers.  Thus, we decided to recalculate how far are the CORE research outputs – if we had printed them – from reaching the moon (last year we made it to 1/3 of the way).

We are thrilled to see that this year we got CORE even closer to the moon! We would also like to thank all our data providers, who have helped us reaching this goal.

Fear not, we will never print all our research outputs, we believe that their mission is to be discoverable on the web as open access. Plus we love trees.

Merry Christmas from the CORE Team!

* Note: Special thanks to Matteo Cancellieri for creating the CORE graphics.