Relevante Forschungsdaten effektiv sammeln mit Content Aggregation

Der folgende Beitrag ist ein Auszug aus Accessing and Analysing Relevant Content in Today’s Information Chaos.

Content-Host-Aggregatoren liefern einfach Informationen direkt aus verschiedenen Quellen in einen Feed oder eine Anzeige. Bekannte Beispiele sind Google News oder Apple News, die Artikel aus Online-Medienquellen wie Reuters, ESPN und NPR auf einer einzigen Seite mit Schlagzeilen zusammenfassen.

Für Forscher:innen und andere Wissensarbeiter:innen, die Aggregatoren verwenden, kann das effektive Sammeln relevanter Daten angesichts der Breite des verfügbaren Materials und der verfügbaren Quellen überwältigend sein. In diesen Szenarien müssen Forscher und ihre Teams die immense Menge und Vielfalt an Daten durchkämmen, um die Erkenntnisse zu kuratieren, zu verstehen und anzuwenden.

Erfahren Sie in dem nachfolgenden Beitrag, der zuerst im Blog des CCC erschien, wie Content-Host-Aggregatoren Ihnen im Arbeitsalltag konkret weiterhelfen können.

Content aggregators fall into three distinct categories:

Content Hosts: Companies whose primary focus is to provide a hosting service for publishers. Quality and validity can be challenging as these hosts are not typically selective of the content displayed.

Gateway Hosts: Companies that index or categorize disparate content on other content host services. These services are generally subscription-based and host a collection of links to publishers’ full-text content by accumulating abstracts and indexing information. Libraries typically fall into this category.

Full-Text Aggregators: “Traditional” aggregators of licensed full-text content that encompass everything content and gateway hosts have, but without the subscriptions or creating full-text databases. They centralize access to full content licensing from the original source, which contributes to the validity of the sources and information being provided. Content curation, in addition to aggregation, provides another layer of expertise that leads to greater relevancy and trust in the search results. In particular, this capability provides users with just-in-time decision support.

Where it comes into play

Organizations looking to acquire a content aggregation and curation service should develop criteria to determine which service would best help their users while considering the following strategic questions:

How can we help drive decision making promptly with well-organized empirical data?
How can aggregated content efficiently become curated content?

Users are looking to optimize their workflow without jeopardizing the efficacy of search or losing relevant data in the process. Knowledge workers must be able to pull empirical information that directly relates to the research:

to amplify efficiency, allowing them to “fail fast” and start down a new path

to spark inspiration and new ideas, making connections from previously conducted documented work, and
to navigate their analysis seamlessly based on relevance.

Challenges and opportunities

While Google misses both an organization’s internal data and other licensed sources — and includes a lot of noise in its results, a more effective search tool employs both aggregation and personalization which work together to strike the right balance of relevant results. Working in tandem, aggregation and personalization provide a researcher with comprehensive information that isn’t overwhelming so they can more easily find content that’s relevant to their search. 